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description Publicationkeyboard_double_arrow_right Article 2023 NetherlandsPublisher:MDPI AG Funded by:FCT | SFRH/BD/135923/2018FCT| SFRH/BD/135923/2018Authors: Ana Tarrafa Silva; Ana Pereira Roders; Teresa Cunha Ferreira; Ivan Nevzgodin;Ana Tarrafa Silva; Ana Pereira Roders; Teresa Cunha Ferreira; Ivan Nevzgodin;doi: 10.3390/land12051040
The growing complexity of managing the sustainable development of cities stresses the need for interdisciplinary approaches, with a stronger articulation between different fields. The integration between heritage conservation and spatial planning has already been addressed in recent literature, ranging from a traditional sectorial perspective towards more cooperative and coordinated initiatives, occasionally resulting in integrated policies. Nevertheless, the lack of institutional and policy articulation remains among the most frequent critical governance issues unsolved. This paper unveils the integration degrees between heritage conservation and spatial planning policies in Amsterdam (The Netherlands) and Ballarat (Australia), acknowledged for local and upper governmental initiatives, such as the Belvedere Memorandum and the Imagine Ballarat project, placing both at the forefront of the roadmap to this policy integration. In-depth semi-structured interviews with municipal officials in both cities reveal that, while policy integration is aimed at, implementation remains challenging. Both cities’ heritage conservation and spatial planning fields keep operating in parallel, often in conflict, and with different perspectives on the cultural heritage commonly managed. By identifying local technicians’ challenges, this research demonstrates that policy integration between heritage conservation and spatial planning is an ongoing process that demands more effective articulation towards more sustainable and resilient cities. Heritage & Architecture
NARCIS; TU Delft Rep... arrow_drop_down NARCIS; TU Delft Repository; LandArticle . 2023LandOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/12/5/1040/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land12051040&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 9visibility views 9 download downloads 5 Powered bymore_vert NARCIS; TU Delft Rep... arrow_drop_down NARCIS; TU Delft Repository; LandArticle . 2023LandOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/12/5/1040/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land12051040&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 United Kingdom, NetherlandsPublisher:MDPI AG Funded by:UKRI | UK Status, Change and Pro..., FCT | LA 1, EC | SUPER-GUKRI| UK Status, Change and Projections of the Environment (UK-SCaPE) ,FCT| LA 1 ,EC| SUPER-GArlete S. Barneze; Mohamed Abdalla; Jeanette Whitaker; Niall P. McNamara; Nicholas J. Ostle;Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.
NARCIS; Research@WUR arrow_drop_down Agronomy; NERC Open Research ArchiveOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy12123055&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down Agronomy; NERC Open Research ArchiveOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy12123055&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 Italy, Netherlands, PortugalPublisher:MDPI AG Funded by:FCT | SFRH/BD/147883/2019, UKRI | The Intelligent Automatio..., EC | UNALABFCT| SFRH/BD/147883/2019 ,UKRI| The Intelligent Automation of Contract Analysis of Collateral Warranties ,EC| UNALABElena Di Pirro; Rúben Mendes; Teresa Fidélis; Lorenzo Sallustio; Peter Roebeling; Marco Marchetti; Bruno Lasserre;doi: 10.3390/land11081254
handle: 11695/116610
European countries recently prepared recovery and resilience plans (RRPs) to recover from the pandemic crisis and reach climate neutrality. Nature-Based Solutions (NBS) are recognized as crucial drivers to fostering climate transition while addressing other challenges. Accordingly, RRPs offer the opportunity to promote the adoption of NBS. This article assesses the NBS embeddedness in the policy discourse of Italian and Portuguese RRPs and how they are considered to meet climate–and related environmental–targets. We conducted a discourse analysis based on two steps, (i) a quantitative analysis to classify different nature-related terms into four categories—biophysical elements, general environmental concepts, threats and challenges, and NBS—and estimate their frequency in the text; (ii) a qualitative analysis to understand the relationship between the categories of challenges and NBS as well as the dedicated investments. The results show that NBS are barely mentioned, with a frequency in the texts for the NBS category of 0.04% and 0.01%, respectively, in Italian and Portuguese RRPs. Narratives are mainly built around general concepts such as resilience and sustainability with nature scarcely considered as an ex novo solution to meet challenges. Notwithstanding, Italy invests 330 M in the implementation of urban forests, while in Portugal, no specific NBS interventions have been considered so far. To date, both countries are primarily orienting the climate transition toward reducing emissions instead of combining these measures with multifunctional NBS to address environmental and socio-economic challenges.
Archivio Istituziona... arrow_drop_down Archivio Istituzionale della Ricerca - Università degli Studi del Molise; Research@WUR; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-445X/11/8/1254/pdfRepositório Institucional da Universidade de AveiroArticle . 2022Data sources: Repositório Institucional da Universidade de Aveiroadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11081254&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 5 citations 5 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Archivio Istituziona... arrow_drop_down Archivio Istituzionale della Ricerca - Università degli Studi del Molise; Research@WUR; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-445X/11/8/1254/pdfRepositório Institucional da Universidade de AveiroArticle . 2022Data sources: Repositório Institucional da Universidade de Aveiroadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11081254&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 United Kingdom, NetherlandsPublisher:Elsevier BV Funded by:FCT | LA 1, UKRI | Data Science of the Natur...FCT| LA 1 ,UKRI| Data Science of the Natural EnvironmentAuthors: Peter M. Atkinson; A. Stein; C. Jeganathan;Peter M. Atkinson; A. Stein; C. Jeganathan;This paper summarizes the development and application of spatial statistical models in satellite optical remote sensing. The paper focuses on the development of a conceptual model that includes the measurement and sampling processes inherent in remote sensing. We organized this paper into five main sections: introducing the basis of remote sensing, including measurement and sampling; spatial variation, including variation through the object-based data model; advances in spatial statistical modelling; machine learning and explainable AI; a hierarchical ontological model of the nature of remotely sensed scenes. The paper finishes with a summary. We conclude that optical remote sensing provides an important source of data and information for the development of spatial statistical techniques that, in turn, serve as powerful tools to obtain important information from the images.
Lancaster EPrints; S... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.spasta.2022.100646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 4 citations 4 popularity Top 10% influence Average impulse Average Powered by BIP!visibility 8visibility views 8 download downloads 4 Powered bymore_vert Lancaster EPrints; S... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.spasta.2022.100646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 NetherlandsPublisher:MDPI AG Funded by:FCT | CESAM, FCT | COVID/BD/151924/2021, FCT | CESAM +2 projectsFCT| CESAM ,FCT| COVID/BD/151924/2021 ,FCT| CESAM ,FCT| CESAM ,FCT| SFRH/BD/131148/2017Mohamed Henriques; Teresa Catry; João Ricardo Belo; Theunis Piersma; Samuel Pontes; José Pedro Granadeiro;Migratory shorebirds are notable consumers of benthic invertebrates on intertidal sediments. The distribution and abundance of shorebirds will strongly depend on their prey and on landscape and sediment features such as mud and surface water content, topography, and the presence of ecosystem engineers. An understanding of shorebird distribution and ecology thus requires knowledge of the various habitat types which may be distinguished in intertidal areas. Here, we combine Sentinel-1 and Sentinel-2 imagery and a digital elevation model (DEM), using machine learning techniques to map intertidal habitat types of importance to migratory shorebirds and their benthic prey. We do this on the third most important non-breeding area for migratory shorebirds in the East Atlantic Flyway, in the Bijagós Archipelago in West Africa. Using pixel-level random forests, we successfully mapped rocks, shell beds, and macroalgae and distinguished between areas of bare sediment and areas occupied by fiddler crabs, an ecosystem engineer that promotes significant bioturbation on intertidal flats. We also classified two sediment types (sandy and mixed) within the bare sediment and fiddler crab areas, according to their mud content. The overall classification accuracy was 82%, and the Kappa Coefficient was 73%. The most important predictors were elevation, the Sentinel-2-derived water and moisture indexes, and Sentinel-1 VH band. The association of Sentinel-2 with Sentinel-1 and a DEM produced the best results compared to the models without these variables. This map provides an overall picture of the composition of the intertidal habitats in a site of international importance for migratory shorebirds. Most of the intertidal flats of the Bijagós Archipelago are covered by bare sandy sediments (59%), and ca. 22% is occupied by fiddler crabs. This likely has significant implications for the spatial arrangement of the shorebird and benthic invertebrate communities due to the ecosystem engineering by the fiddler crabs, which promotes two vastly different intertidal species assemblages. This large-scale mapping provides an important product for the future monitoring of this high biodiversity area, particularly for ecological research related to the distribution and feeding ecology of the shorebirds and their prey. Such information is key from a conservation and management perspective. By delivering a successful and comprehensive mapping workflow, we contribute to the filling of the current knowledge gap on the application of remote sensing and machine learning techniques within intertidal areas, which are among the most challenging environments to map using remote sensing techniques.
NARCIS; Remote Sensi... arrow_drop_down NARCIS; Remote SensingArticle . 2022Remote SensingOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-4292/14/14/3260/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs14143260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Remote Sensi... arrow_drop_down NARCIS; Remote SensingArticle . 2022Remote SensingOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-4292/14/14/3260/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs14143260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 Netherlands, PortugalPublisher:CSIRO Publishing Funded by:FCT | SFRH/BD/146356/2019FCT| SFRH/BD/146356/2019Vieira, D. C. S.; Basso, M.; Nunes, João Pedro; Keizer, J. J.; Baartman, J. E. M.;doi: 10.1071/wf21005
handle: 10451/53572
Recently burnt areas typically reveal strong to extreme hydrological responses, as a consequence of loss of protective soil cover and heating-induced changes in topsoil properties. Soil water repellency (SWR) has frequently been referred to as one of the explanatory variables for fire-enhanced surface runoff generation but this has been poorly demonstrated, especially at the catchment scale. This study employs a process-based modelling approach to better understand the relevance of SWR in the hydrological response of a small, entirely burnt catchment in central Portugal, in particular by comparing hydrological events under contrasting initial conditions of dry vs wet soils. The OpenLISEM model was applied to a selection of 16 major rainfall runoff events that occurred during the first 2 post-fire years. The automatic calibration procedure resulted in good model performance, but it worsened for validation events. Furthermore, uncertainty analysis revealed an elevated sensitivity of OpenLISEM to event-specific conditions, especially for predicting the events’ total and peak flows. Also, predicted spatial patterns in runoff poorly agreed with the runoff observed in microplots. Model performance improved when events were separated by dry and wet initial moisture conditions, particularly for wet conditions, suggesting the role of variables other than initial soil moisture.
NARCIS; Research@WUR arrow_drop_down Universidade de Lisboa: Repositório.ULArticle . 2022License: CC BY NC NDData sources: Universidade de Lisboa: Repositório.ULadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1071/wf21005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 36visibility views 36 download downloads 31 Powered bymore_vert NARCIS; Research@WUR arrow_drop_down Universidade de Lisboa: Repositório.ULArticle . 2022License: CC BY NC NDData sources: Universidade de Lisboa: Repositório.ULadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1071/wf21005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 United Kingdom, NetherlandsPublisher:MDPI AG Funded by:FCT | LA 1, UKRI | Sustainable Use of Natura...FCT| LA 1 ,UKRI| Sustainable Use of Natural Resources to Improve Human Health and Support Economic Development (SUNRISE)Rebecca L. Rowe; Cahyo Prayogo; Simon Oakley; Kurniatun Hairiah; Meine van Noordwijk; Karuniawan Puji Wicaksono; Syahrul Kurniawan; Alice Fitch; Edi Dwi Cahyono; Didik Suprayogo; Niall P. McNamara;doi: 10.3390/land11050671
The Indonesian state forest managers have accepted farmer-managed coffee agroforestry in their estates as part of their social forestry program. Access by local farming communities to state-owned plantation forestry supports public motivation to maintain forest cover. However, balancing the expectations and needs of forest managers with those of the local farming communities is not easy. Coffee yields in Indonesia are lower than those of neighboring countries, suggesting that there is scope for improvement. Here we describe an experimental research platform developed through an international collaboration between the Universitas Brawijaya (UB), the UK Centre for Ecology and Hydrology (UKCEH), and smallholder coffee farmers to explore options for improving pine-coffee agroforestry systems within existing regulations. Located in a former state-owned pine production forest on the slopes of the stratovolcano, Mount Arjuna, in the Malang Regency of East Java, the research platform has seven instrumented research plots (40 × 60 m2), where agronomic practices can be trialed. The aim of the platform is to support the development of sustainable agronomic practices to improve the profitability of coffee agroforestry and thus the livelihood of low-income rural communities. Current trials are focused on improving coffee yields and include pine canopy trimming, fertilizers, and coffee pruning trials, with links to the development of socio-economic and environmental models. Whilst it is too early to assess the full impacts on yields, a survey of farmers demonstrated a positive attitude to canopy pruning, although with some concern over labor cost. The initial ecosystem modelling has highlighted the benefits of coffee agroforestry in balancing environmental and economic benefits. Here we provide a detailed description of the site, the current trials, and the modelling work, with the hope of highlighting opportunities for future collaboration and innovation.
NARCIS; Research@WUR arrow_drop_down NERC Open Research Archive; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/11/5/671/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11050671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 popularity Top 10% influence Average impulse Average Powered by BIP!visibility 27visibility views 27 download downloads 16 Powered bymore_vert NARCIS; Research@WUR arrow_drop_down NERC Open Research Archive; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/11/5/671/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11050671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 United Kingdom, United Kingdom, NetherlandsPublisher:MDPI AG Funded by:FCT | LA 1FCT| LA 1Libo Wang; Ce Zhang; Rui Li; Chenxi Duan; Xiaoliang Meng; Peter M. Atkinson;Assigning geospatial objects with specific categories at the pixel level is a fundamental task in remote sensing image analysis. Along with the rapid development of sensor technologies, remotely sensed images can be captured at multiple spatial resolutions (MSR) with information content manifested at different scales. Extracting information from these MSR images represents huge opportunities for enhanced feature representation and characterisation. However, MSR images suffer from two critical issues: (1) increased scale variation of geo-objects and (2) loss of detailed information at coarse spatial resolutions. To bridge these gaps, in this paper, we propose a novel scale-aware neural network (SaNet) for the semantic segmentation of MSR remotely sensed imagery. SaNet deploys a densely connected feature network (DCFFM) module to capture high-quality multi-scale context, such that the scale variation is handled properly and the quality of segmentation is increased for both large and small objects. A spatial feature recalibration (SFRM) module was further incorporated into the network to learn intact semantic content with enhanced spatial relationships, where the negative effects of information loss are removed. The combination of DCFFM and SFRM allows SaNet to learn scale-aware feature representation, which outperforms the existing multi-scale feature representation. Extensive experiments on three semantic segmentation datasets demonstrated the effectiveness of the proposed SaNet in cross-resolution segmentation.
Remote Sensing; NERC... arrow_drop_down Remote Sensing; NERC Open Research Archive; Lancaster EPrintsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYarXiv.org e-Print ArchiveOther literature type . Preprint . 2021Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2021License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs13245015&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 11 citations 11 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 16visibility views 16 download downloads 33 Powered bymore_vert Remote Sensing; NERC... arrow_drop_down Remote Sensing; NERC Open Research Archive; Lancaster EPrintsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYarXiv.org e-Print ArchiveOther literature type . Preprint . 2021Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2021License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs13245015&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 NetherlandsPublisher:MDPI AG Funded by:FCT | SFRH/BD/147117/2019FCT| SFRH/BD/147117/2019Authors: André Silva Pinto de Aguiar; Sandro Augusto Magalhães; Filipe Neves dos Santos; Luís M. Castro; +4 AuthorsAndré Silva Pinto de Aguiar; Sandro Augusto Magalhães; Filipe Neves dos Santos; Luís M. Castro; Tatiana M. Pinho; João Valente; Rui C. Martins; José Boaventura-Cunha;The agricultural sector plays a fundamental role in our society, where it is increasingly important to automate processes, which can generate beneficial impacts in the productivity and quality of products. Perception and computer vision approaches can be fundamental in the implementation of robotics in agriculture. In particular, deep learning can be used for image classification or object detection, endowing machines with the capability to perform operations in the agriculture context. In this work, deep learning was used for the detection of grape bunches in vineyards considering different growth stages: the early stage just after the bloom and the medium stage where the grape bunches present an intermediate development. Two state-of-the-art single-shot multibox models were trained, quantized, and deployed in a low-cost and low-power hardware device, a Tensor Processing Unit. The training input was a novel and publicly available dataset proposed in this work. This dataset contains 1929 images and respective annotations of grape bunches at two different growth stages, captured by different cameras in several illumination conditions. The models were benchmarked and characterized considering the variation of two different parameters: the confidence score and the intersection over union threshold. The results showed that the deployed models could detect grape bunches in images with a medium average precision up to 66.96%. Since this approach uses low resources, a low-cost and low-power hardware device that requires simplified models with 8 bit quantization, the obtained performance was satisfactory. Experiments also demonstrated that the models performed better in identifying grape bunches at the medium growth stage, in comparison with grape bunches present in the vineyard after the bloom, since the second class represents smaller grape bunches, with a color and texture more similar to the surrounding foliage, which complicates their detection.
NARCIS; Research@WUR arrow_drop_down AgronomyOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4395/11/9/1890/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy11091890&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 33 citations 33 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down AgronomyOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4395/11/9/1890/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy11091890&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 Netherlands, France, Italy, France, FrancePublisher:MDPI AG Funded by:FCT | LA 1, EC | CropBooster-P, UKRI | Cost-driven process redes...FCT| LA 1 ,EC| CropBooster-P ,UKRI| Cost-driven process redesign, automation and scale-out for commercial manufacture of REX-001 therapyJeremy Harbinson; Martin A. J. Parry; Jess Davies; Norbert Rolland; Francesco Loreto; Ralf Wilhelm; Karin Metzlaff; René Klein Lankhorst;The realization of the full objectives of international policies targeting global food security and climate change mitigation, including the United Nation’s Sustainable Development Goals, the Paris Climate Agreement COP21 and the European Green Deal, requires that we (i) sustainably increase the yield, nutritional quality and biodiversity of major crop species, (ii) select climate-ready crops that are adapted to future weather dynamic and (iii) increase the resource use efficiency of crops for sustainably preserving natural resources. Ultimately, the grand challenge to be met by agriculture is to sustainably provide access to sufficient, nutritious and diverse food to a worldwide growing population, and to support the circular bio-based economy. Future-proofing our crops is an urgent issue and a challenging goal, involving a diversity of crop species in differing agricultural regimes and under multiple environmental drivers, providing versatile crop-breeding solutions within wider socio-economic-ecological systems. This goal can only be realized by a large-scale, international research cooperation. We call for international action and propose a pan-European research initiative, the CropBooster Program, to mobilize the European plant research community and interconnect it with the interdisciplinary expertise necessary to face the challenge. International audience
NARCIS; Research@WUR arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8301437Data sources: PubMed CentralBiologyArticle . 2021 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2079-7737/10/7/690/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/biology10070690&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 11 citations 11 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8301437Data sources: PubMed CentralBiologyArticle . 2021 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2079-7737/10/7/690/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/biology10070690&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article 2023 NetherlandsPublisher:MDPI AG Funded by:FCT | SFRH/BD/135923/2018FCT| SFRH/BD/135923/2018Authors: Ana Tarrafa Silva; Ana Pereira Roders; Teresa Cunha Ferreira; Ivan Nevzgodin;Ana Tarrafa Silva; Ana Pereira Roders; Teresa Cunha Ferreira; Ivan Nevzgodin;doi: 10.3390/land12051040
The growing complexity of managing the sustainable development of cities stresses the need for interdisciplinary approaches, with a stronger articulation between different fields. The integration between heritage conservation and spatial planning has already been addressed in recent literature, ranging from a traditional sectorial perspective towards more cooperative and coordinated initiatives, occasionally resulting in integrated policies. Nevertheless, the lack of institutional and policy articulation remains among the most frequent critical governance issues unsolved. This paper unveils the integration degrees between heritage conservation and spatial planning policies in Amsterdam (The Netherlands) and Ballarat (Australia), acknowledged for local and upper governmental initiatives, such as the Belvedere Memorandum and the Imagine Ballarat project, placing both at the forefront of the roadmap to this policy integration. In-depth semi-structured interviews with municipal officials in both cities reveal that, while policy integration is aimed at, implementation remains challenging. Both cities’ heritage conservation and spatial planning fields keep operating in parallel, often in conflict, and with different perspectives on the cultural heritage commonly managed. By identifying local technicians’ challenges, this research demonstrates that policy integration between heritage conservation and spatial planning is an ongoing process that demands more effective articulation towards more sustainable and resilient cities. Heritage & Architecture
NARCIS; TU Delft Rep... arrow_drop_down NARCIS; TU Delft Repository; LandArticle . 2023LandOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/12/5/1040/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land12051040&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 9visibility views 9 download downloads 5 Powered bymore_vert NARCIS; TU Delft Rep... arrow_drop_down NARCIS; TU Delft Repository; LandArticle . 2023LandOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/12/5/1040/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land12051040&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 United Kingdom, NetherlandsPublisher:MDPI AG Funded by:UKRI | UK Status, Change and Pro..., FCT | LA 1, EC | SUPER-GUKRI| UK Status, Change and Projections of the Environment (UK-SCaPE) ,FCT| LA 1 ,EC| SUPER-GArlete S. Barneze; Mohamed Abdalla; Jeanette Whitaker; Niall P. McNamara; Nicholas J. Ostle;Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.
NARCIS; Research@WUR arrow_drop_down Agronomy; NERC Open Research ArchiveOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy12123055&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down Agronomy; NERC Open Research ArchiveOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy12123055&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 Italy, Netherlands, PortugalPublisher:MDPI AG Funded by:FCT | SFRH/BD/147883/2019, UKRI | The Intelligent Automatio..., EC | UNALABFCT| SFRH/BD/147883/2019 ,UKRI| The Intelligent Automation of Contract Analysis of Collateral Warranties ,EC| UNALABElena Di Pirro; Rúben Mendes; Teresa Fidélis; Lorenzo Sallustio; Peter Roebeling; Marco Marchetti; Bruno Lasserre;doi: 10.3390/land11081254
handle: 11695/116610
European countries recently prepared recovery and resilience plans (RRPs) to recover from the pandemic crisis and reach climate neutrality. Nature-Based Solutions (NBS) are recognized as crucial drivers to fostering climate transition while addressing other challenges. Accordingly, RRPs offer the opportunity to promote the adoption of NBS. This article assesses the NBS embeddedness in the policy discourse of Italian and Portuguese RRPs and how they are considered to meet climate–and related environmental–targets. We conducted a discourse analysis based on two steps, (i) a quantitative analysis to classify different nature-related terms into four categories—biophysical elements, general environmental concepts, threats and challenges, and NBS—and estimate their frequency in the text; (ii) a qualitative analysis to understand the relationship between the categories of challenges and NBS as well as the dedicated investments. The results show that NBS are barely mentioned, with a frequency in the texts for the NBS category of 0.04% and 0.01%, respectively, in Italian and Portuguese RRPs. Narratives are mainly built around general concepts such as resilience and sustainability with nature scarcely considered as an ex novo solution to meet challenges. Notwithstanding, Italy invests 330 M in the implementation of urban forests, while in Portugal, no specific NBS interventions have been considered so far. To date, both countries are primarily orienting the climate transition toward reducing emissions instead of combining these measures with multifunctional NBS to address environmental and socio-economic challenges.
Archivio Istituziona... arrow_drop_down Archivio Istituzionale della Ricerca - Università degli Studi del Molise; Research@WUR; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-445X/11/8/1254/pdfRepositório Institucional da Universidade de AveiroArticle . 2022Data sources: Repositório Institucional da Universidade de Aveiroadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11081254&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 5 citations 5 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Archivio Istituziona... arrow_drop_down Archivio Istituzionale della Ricerca - Università degli Studi del Molise; Research@WUR; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-445X/11/8/1254/pdfRepositório Institucional da Universidade de AveiroArticle . 2022Data sources: Repositório Institucional da Universidade de Aveiroadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11081254&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 United Kingdom, NetherlandsPublisher:Elsevier BV Funded by:FCT | LA 1, UKRI | Data Science of the Natur...FCT| LA 1 ,UKRI| Data Science of the Natural EnvironmentAuthors: Peter M. Atkinson; A. Stein; C. Jeganathan;Peter M. Atkinson; A. Stein; C. Jeganathan;This paper summarizes the development and application of spatial statistical models in satellite optical remote sensing. The paper focuses on the development of a conceptual model that includes the measurement and sampling processes inherent in remote sensing. We organized this paper into five main sections: introducing the basis of remote sensing, including measurement and sampling; spatial variation, including variation through the object-based data model; advances in spatial statistical modelling; machine learning and explainable AI; a hierarchical ontological model of the nature of remotely sensed scenes. The paper finishes with a summary. We conclude that optical remote sensing provides an important source of data and information for the development of spatial statistical techniques that, in turn, serve as powerful tools to obtain important information from the images.
Lancaster EPrints; S... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.spasta.2022.100646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 4 citations 4 popularity Top 10% influence Average impulse Average Powered by BIP!visibility 8visibility views 8 download downloads 4 Powered bymore_vert Lancaster EPrints; S... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.spasta.2022.100646&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 NetherlandsPublisher:MDPI AG Funded by:FCT | CESAM, FCT | COVID/BD/151924/2021, FCT | CESAM +2 projectsFCT| CESAM ,FCT| COVID/BD/151924/2021 ,FCT| CESAM ,FCT| CESAM ,FCT| SFRH/BD/131148/2017Mohamed Henriques; Teresa Catry; João Ricardo Belo; Theunis Piersma; Samuel Pontes; José Pedro Granadeiro;Migratory shorebirds are notable consumers of benthic invertebrates on intertidal sediments. The distribution and abundance of shorebirds will strongly depend on their prey and on landscape and sediment features such as mud and surface water content, topography, and the presence of ecosystem engineers. An understanding of shorebird distribution and ecology thus requires knowledge of the various habitat types which may be distinguished in intertidal areas. Here, we combine Sentinel-1 and Sentinel-2 imagery and a digital elevation model (DEM), using machine learning techniques to map intertidal habitat types of importance to migratory shorebirds and their benthic prey. We do this on the third most important non-breeding area for migratory shorebirds in the East Atlantic Flyway, in the Bijagós Archipelago in West Africa. Using pixel-level random forests, we successfully mapped rocks, shell beds, and macroalgae and distinguished between areas of bare sediment and areas occupied by fiddler crabs, an ecosystem engineer that promotes significant bioturbation on intertidal flats. We also classified two sediment types (sandy and mixed) within the bare sediment and fiddler crab areas, according to their mud content. The overall classification accuracy was 82%, and the Kappa Coefficient was 73%. The most important predictors were elevation, the Sentinel-2-derived water and moisture indexes, and Sentinel-1 VH band. The association of Sentinel-2 with Sentinel-1 and a DEM produced the best results compared to the models without these variables. This map provides an overall picture of the composition of the intertidal habitats in a site of international importance for migratory shorebirds. Most of the intertidal flats of the Bijagós Archipelago are covered by bare sandy sediments (59%), and ca. 22% is occupied by fiddler crabs. This likely has significant implications for the spatial arrangement of the shorebird and benthic invertebrate communities due to the ecosystem engineering by the fiddler crabs, which promotes two vastly different intertidal species assemblages. This large-scale mapping provides an important product for the future monitoring of this high biodiversity area, particularly for ecological research related to the distribution and feeding ecology of the shorebirds and their prey. Such information is key from a conservation and management perspective. By delivering a successful and comprehensive mapping workflow, we contribute to the filling of the current knowledge gap on the application of remote sensing and machine learning techniques within intertidal areas, which are among the most challenging environments to map using remote sensing techniques.
NARCIS; Remote Sensi... arrow_drop_down NARCIS; Remote SensingArticle . 2022Remote SensingOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-4292/14/14/3260/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs14143260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 9 citations 9 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Remote Sensi... arrow_drop_down NARCIS; Remote SensingArticle . 2022Remote SensingOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-4292/14/14/3260/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs14143260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 Netherlands, PortugalPublisher:CSIRO Publishing Funded by:FCT | SFRH/BD/146356/2019FCT| SFRH/BD/146356/2019Vieira, D. C. S.; Basso, M.; Nunes, João Pedro; Keizer, J. J.; Baartman, J. E. M.;doi: 10.1071/wf21005
handle: 10451/53572
Recently burnt areas typically reveal strong to extreme hydrological responses, as a consequence of loss of protective soil cover and heating-induced changes in topsoil properties. Soil water repellency (SWR) has frequently been referred to as one of the explanatory variables for fire-enhanced surface runoff generation but this has been poorly demonstrated, especially at the catchment scale. This study employs a process-based modelling approach to better understand the relevance of SWR in the hydrological response of a small, entirely burnt catchment in central Portugal, in particular by comparing hydrological events under contrasting initial conditions of dry vs wet soils. The OpenLISEM model was applied to a selection of 16 major rainfall runoff events that occurred during the first 2 post-fire years. The automatic calibration procedure resulted in good model performance, but it worsened for validation events. Furthermore, uncertainty analysis revealed an elevated sensitivity of OpenLISEM to event-specific conditions, especially for predicting the events’ total and peak flows. Also, predicted spatial patterns in runoff poorly agreed with the runoff observed in microplots. Model performance improved when events were separated by dry and wet initial moisture conditions, particularly for wet conditions, suggesting the role of variables other than initial soil moisture.
NARCIS; Research@WUR arrow_drop_down Universidade de Lisboa: Repositório.ULArticle . 2022License: CC BY NC NDData sources: Universidade de Lisboa: Repositório.ULadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1071/wf21005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 36visibility views 36 download downloads 31 Powered bymore_vert NARCIS; Research@WUR arrow_drop_down Universidade de Lisboa: Repositório.ULArticle . 2022License: CC BY NC NDData sources: Universidade de Lisboa: Repositório.ULadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1071/wf21005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022 United Kingdom, NetherlandsPublisher:MDPI AG Funded by:FCT | LA 1, UKRI | Sustainable Use of Natura...FCT| LA 1 ,UKRI| Sustainable Use of Natural Resources to Improve Human Health and Support Economic Development (SUNRISE)Rebecca L. Rowe; Cahyo Prayogo; Simon Oakley; Kurniatun Hairiah; Meine van Noordwijk; Karuniawan Puji Wicaksono; Syahrul Kurniawan; Alice Fitch; Edi Dwi Cahyono; Didik Suprayogo; Niall P. McNamara;doi: 10.3390/land11050671
The Indonesian state forest managers have accepted farmer-managed coffee agroforestry in their estates as part of their social forestry program. Access by local farming communities to state-owned plantation forestry supports public motivation to maintain forest cover. However, balancing the expectations and needs of forest managers with those of the local farming communities is not easy. Coffee yields in Indonesia are lower than those of neighboring countries, suggesting that there is scope for improvement. Here we describe an experimental research platform developed through an international collaboration between the Universitas Brawijaya (UB), the UK Centre for Ecology and Hydrology (UKCEH), and smallholder coffee farmers to explore options for improving pine-coffee agroforestry systems within existing regulations. Located in a former state-owned pine production forest on the slopes of the stratovolcano, Mount Arjuna, in the Malang Regency of East Java, the research platform has seven instrumented research plots (40 × 60 m2), where agronomic practices can be trialed. The aim of the platform is to support the development of sustainable agronomic practices to improve the profitability of coffee agroforestry and thus the livelihood of low-income rural communities. Current trials are focused on improving coffee yields and include pine canopy trimming, fertilizers, and coffee pruning trials, with links to the development of socio-economic and environmental models. Whilst it is too early to assess the full impacts on yields, a survey of farmers demonstrated a positive attitude to canopy pruning, although with some concern over labor cost. The initial ecosystem modelling has highlighted the benefits of coffee agroforestry in balancing environmental and economic benefits. Here we provide a detailed description of the site, the current trials, and the modelling work, with the hope of highlighting opportunities for future collaboration and innovation.
NARCIS; Research@WUR arrow_drop_down NERC Open Research Archive; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/11/5/671/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11050671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 2 citations 2 popularity Top 10% influence Average impulse Average Powered by BIP!visibility 27visibility views 27 download downloads 16 Powered bymore_vert NARCIS; Research@WUR arrow_drop_down NERC Open Research Archive; LandOther literature type . Article . 2022 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-445X/11/5/671/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/land11050671&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 United Kingdom, United Kingdom, NetherlandsPublisher:MDPI AG Funded by:FCT | LA 1FCT| LA 1Libo Wang; Ce Zhang; Rui Li; Chenxi Duan; Xiaoliang Meng; Peter M. Atkinson;Assigning geospatial objects with specific categories at the pixel level is a fundamental task in remote sensing image analysis. Along with the rapid development of sensor technologies, remotely sensed images can be captured at multiple spatial resolutions (MSR) with information content manifested at different scales. Extracting information from these MSR images represents huge opportunities for enhanced feature representation and characterisation. However, MSR images suffer from two critical issues: (1) increased scale variation of geo-objects and (2) loss of detailed information at coarse spatial resolutions. To bridge these gaps, in this paper, we propose a novel scale-aware neural network (SaNet) for the semantic segmentation of MSR remotely sensed imagery. SaNet deploys a densely connected feature network (DCFFM) module to capture high-quality multi-scale context, such that the scale variation is handled properly and the quality of segmentation is increased for both large and small objects. A spatial feature recalibration (SFRM) module was further incorporated into the network to learn intact semantic content with enhanced spatial relationships, where the negative effects of information loss are removed. The combination of DCFFM and SFRM allows SaNet to learn scale-aware feature representation, which outperforms the existing multi-scale feature representation. Extensive experiments on three semantic segmentation datasets demonstrated the effectiveness of the proposed SaNet in cross-resolution segmentation.
Remote Sensing; NERC... arrow_drop_down Remote Sensing; NERC Open Research Archive; Lancaster EPrintsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYarXiv.org e-Print ArchiveOther literature type . Preprint . 2021Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2021License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs13245015&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 11 citations 11 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 16visibility views 16 download downloads 33 Powered bymore_vert Remote Sensing; NERC... arrow_drop_down Remote Sensing; NERC Open Research Archive; Lancaster EPrintsOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYarXiv.org e-Print ArchiveOther literature type . Preprint . 2021Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2021License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/rs13245015&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 NetherlandsPublisher:MDPI AG Funded by:FCT | SFRH/BD/147117/2019FCT| SFRH/BD/147117/2019Authors: André Silva Pinto de Aguiar; Sandro Augusto Magalhães; Filipe Neves dos Santos; Luís M. Castro; +4 AuthorsAndré Silva Pinto de Aguiar; Sandro Augusto Magalhães; Filipe Neves dos Santos; Luís M. Castro; Tatiana M. Pinho; João Valente; Rui C. Martins; José Boaventura-Cunha;The agricultural sector plays a fundamental role in our society, where it is increasingly important to automate processes, which can generate beneficial impacts in the productivity and quality of products. Perception and computer vision approaches can be fundamental in the implementation of robotics in agriculture. In particular, deep learning can be used for image classification or object detection, endowing machines with the capability to perform operations in the agriculture context. In this work, deep learning was used for the detection of grape bunches in vineyards considering different growth stages: the early stage just after the bloom and the medium stage where the grape bunches present an intermediate development. Two state-of-the-art single-shot multibox models were trained, quantized, and deployed in a low-cost and low-power hardware device, a Tensor Processing Unit. The training input was a novel and publicly available dataset proposed in this work. This dataset contains 1929 images and respective annotations of grape bunches at two different growth stages, captured by different cameras in several illumination conditions. The models were benchmarked and characterized considering the variation of two different parameters: the confidence score and the intersection over union threshold. The results showed that the deployed models could detect grape bunches in images with a medium average precision up to 66.96%. Since this approach uses low resources, a low-cost and low-power hardware device that requires simplified models with 8 bit quantization, the obtained performance was satisfactory. Experiments also demonstrated that the models performed better in identifying grape bunches at the medium growth stage, in comparison with grape bunches present in the vineyard after the bloom, since the second class represents smaller grape bunches, with a color and texture more similar to the surrounding foliage, which complicates their detection.
NARCIS; Research@WUR arrow_drop_down AgronomyOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4395/11/9/1890/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy11091890&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 33 citations 33 popularity Top 1% influence Top 10% impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down AgronomyOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4395/11/9/1890/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/agronomy11091890&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 Netherlands, France, Italy, France, FrancePublisher:MDPI AG Funded by:FCT | LA 1, EC | CropBooster-P, UKRI | Cost-driven process redes...FCT| LA 1 ,EC| CropBooster-P ,UKRI| Cost-driven process redesign, automation and scale-out for commercial manufacture of REX-001 therapyJeremy Harbinson; Martin A. J. Parry; Jess Davies; Norbert Rolland; Francesco Loreto; Ralf Wilhelm; Karin Metzlaff; René Klein Lankhorst;The realization of the full objectives of international policies targeting global food security and climate change mitigation, including the United Nation’s Sustainable Development Goals, the Paris Climate Agreement COP21 and the European Green Deal, requires that we (i) sustainably increase the yield, nutritional quality and biodiversity of major crop species, (ii) select climate-ready crops that are adapted to future weather dynamic and (iii) increase the resource use efficiency of crops for sustainably preserving natural resources. Ultimately, the grand challenge to be met by agriculture is to sustainably provide access to sufficient, nutritious and diverse food to a worldwide growing population, and to support the circular bio-based economy. Future-proofing our crops is an urgent issue and a challenging goal, involving a diversity of crop species in differing agricultural regimes and under multiple environmental drivers, providing versatile crop-breeding solutions within wider socio-economic-ecological systems. This goal can only be realized by a large-scale, international research cooperation. We call for international action and propose a pan-European research initiative, the CropBooster Program, to mobilize the European plant research community and interconnect it with the interdisciplinary expertise necessary to face the challenge. International audience
NARCIS; Research@WUR arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8301437Data sources: PubMed CentralBiologyArticle . 2021 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2079-7737/10/7/690/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/biology10070690&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 11 citations 11 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert NARCIS; Research@WUR arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8301437Data sources: PubMed CentralBiologyArticle . 2021 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2079-7737/10/7/690/pdfadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/biology10070690&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu