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4 Research products

  • Rural Digital Europe
  • 2013-2022
  • Doctoral thesis
  • National Science Foundation

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Raturi, Ankita;

    Agriculture is a critical component of the human food system. Its coupling to the success of human societies and its impact on the environment is nontrivial. Varied efforts -- including new regulations, certifications, techniques and software -- exist to assess and improve the sustainability of agriculture. Multiple stakeholders in a fragmented field, with tensions and pulls in different directions, results in a duplication of efforts and disconnected data and processes.To explore the challenges that exist in modeling sustainable agriculture, I characterize environmental assessment as a modeling process, and secondly, characterize sustainable agricultural systems as a type of complex adaptive system. Framing the assessment process and system of interest in this manner permits the application of various techniques from software engineering, systems analysis, and human-computer interaction to tease apart the core issues and to subsequently respond to these challenges through design.First, I present an analysis of the capacity of Life Cycle Assessment (a formal and quantitative environmental assessment technique) to represent small- to medium-scale sustainability-oriented farms. Then, I described a qualitative field study, in which I visited 16 farms across California, interviewing sustainability-oriented farmers, and collecting samples of farm data. The goal of this study was to uncover how and why farmers model farms in practice, the nature and availability of farm data, and the experiences of farmers with various environmental assessment techniques.The findings of these two studies resulted in the articulation of domain-specific modeling requirements. These include: creating selective and partial system models, knitting together qualitative and quantitative data in system models, capturing both spatial and temporal structures, and all of this through models that are abstract yet grounded in real farm data.Building on these studies, I present MoSS: a framework to enable the Modeling of Sustainable Systems. MoSS consists of three parts: an abstract model, domain-specific elements to allow for modeling agricultural systems, and model 'perspectives' that allow for the assessment of the environmental performance of the system. I conducted a scenario-based evaluation of MoSS to assess its ability to express the varying dynamism and complexity of sustainable agricultural systems. MoSS addresses the core challenges involved in modeling sustainable agriculture, providing a consistent mechanism to capture the essence of farms.MoSS represents a step forward in grounded information design for sustainable agriculture, paving the way for the design of information management and environmental assessment tools that more closely meet the needs of small- to medium-scale farms and farmers. Through the work presented in this dissertation, I have also demonstrated how one may engage in applied and interdisciplinary software engineering research to support sustainable development.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ eScholarship - Unive...arrow_drop_down
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    Authors: Lin, Jeng-Hau;

    The entangled guardbands in terms of timing specification and energy budget ensure a system against faults, but the guardbands, meanwhile, impede the advance of a higher throughput and energy efficiency. To combat the over-designed guardbands in a system carrying out deep learning inference, we dive into the algorithmic demands and understand that the resource deficiency and hardware variation are the major reasons of the need of conservative guardbands. In modern convolutional neural networks (CNNs), the number of arithmetic operations for the inference could exceed tens of billions, which requires a sophisticated buffering mechanism to balance between resource utilization and throughput. In this case, the over-designed guardbands can seriously hinder system performance. On the other hand, timing errors can be incurred by the hardware variations including momentary voltage droops resulted from simultaneous switching noises, a gradually decreasing voltage level due to a limited battery, and the slow electron mobility incurred by the system power dissipation into heat. The timing errors propagating in a network can be a snowball in the beginning but ends up with a catastrophe in terms of a significant accuracy degradation.Knowing the need of guardbands originates from resource deficiency and timing errors, this dissertation focuses on cross-layer solutions to the problems of the high algorithmic demands incurred by deep learning methods and error vulnerability due to hardware variations. We begin with reviewing the methods and technologies proposed in the literature including weight encoding, filter decomposition, network pruning, efficient structure design, and precision quantizing. In the implementation of an FPGA accelerator for extreme-case quantization, binarized neural networks (BNN), we have realized more possible optimizations can be applied. Then, we extend BNN on the algorithmic layer with the binarized separable filters and proposed BCNNw/SF. Although the quantization and approximation benefit hardware efficiency to a certain extent, the optimal reduction or compression rate is still limited by the core of the conventional deep learning methods -- convolution. We, thus, introduce the local binary pattern (LBP) to deep learning because of LBP's low complexity yet high effectiveness. We name the new algorithm LBPNet, in which the feature maps are created with a similar fashion of the traditional LBP using comparisons. Our LBPNet can be trained with the forward-backward propagation algorithm to extract useful features for image classification. LBPNet accelerators have been implemented and optimized to verify their classification performance, processing throughput, and energy efficiency. We also demonstrate the error immunity of LBPNet to be the strongest compared with the subject MLP, CNN, and BCNN models since the classification accuracy of the LBPNet is decreased by only 10% and all the other models lose the classification ability when the timing error rate exceeds 0.01.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ eScholarship - Unive...arrow_drop_down
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  • Authors: Lasseur, Rémy;

    Societal changes over the last century have strongly affected the majority of ecosystem dynamics. Our society is facing a complex paradox: how to maintain decent livelihoods for the world population while limiting negative effects of human activities on ecosystems? The concept of ecosystem services has been proposed to contribute to the solving of this paradox and it holds strong expectations. My PhD research aims at assessing the contribution of ecosystem services mapping to the definition of patterns and drivers of landscape multifunctionality.Chapter I analyses the spatial associations between the agricultural production service and four regulating services over the agricultural lands of the Rhône-Alpes region (France). This work allows us to insist on the ways trade-off and synergies between ecosystem services are defined as well as on the characterization of bundles of ecosystem services. Furthermore, taking advantage of the "ecological niches” concept usually applied to biodiversity, we assess spatial matching between the supply of ecosystem services and the socio-ecological specificities of associated areas, i.e. their social-ecological niche. Our results highlight a large variability concerning associations between agricultural production and regulating services, which illustrates the strong influence of farming practices (e.g., in terms of intensity) in defining the strength of associations between multiple services. In addition, we raised the issue of the robustness of standard statistical analyses to consistently identify bundles of ecosystem services.Chapter II assesses the influence of spatial resolution of modeled data on ecosystem services mapping. To this end, we compare the maps used in the first chapter with high spatial resolution data provided at Grenoble area scale (in the context of the ESNET project). Based on this comparison, we discuss the limits of models used to map ecosystem services.To improve the mapping of ecosystem services supplied by agricultural areas, we propose, in chapter III, a remote sensing-based approach to map agricultural land uses at high resolution on Grenoble region. Simultaneous use of MODIS and Rapideye satellite data allows us to determine cropping successions for 5 years at farming plot scale. These spatially explicit data significantly improved our abilities to map agricultural productions and may be used to map several other ecosystem services.To complete the third chapter, chapter IV gives a synthesis of remote sensing approaches that could be used to map ecosystem services, focusing on methods that are not linked to land uses identification. Based on a wide panel of ecosystem services mapping studies, we highlight data currently needed to map ecosystem services. Then we bridge these needs and the potential of remote sensing approaches for ecosystem services modelers.; Les mutations de la société au cours du dernier siècle ont de fortes répercussions sur le fonctionnement de la majorité des écosystèmes. Notre société fait face à un paradoxe complexe défini par la nécessité de satisfaire des conditions de vie décentes d’une population mondiale croissante tout en limitant les impacts négatifs sur les écosystèmes. Le concept de service écosystémique a été proposé pour accompagner la résolution de ce paradoxe et de nombreuses attentes reposent sur ce concept. Mon travail de thèse a pour objectifs d’évaluer les apports actuels de la cartographie des services écosystémiques pour caractériser les patrons spatiaux et déterminants de la multifonctionnalité des territoires.Dans le chapitre I nous proposons une analyse des associations entre le service de production agricole et quatre services de régulation au niveau des surfaces agricoles de la région Rhône-Alpes (France). Ce travail nous permet de revenir sur la définition des compromis et synergies entre services écosystémiques aussi bien que sur le concept de bouquet de services écosystèmiques. Par ailleurs, en s’inspirant du concept de niche écologique pour les espèces, nous évaluons l’adéquation spatiale entre la fourniture de services écosystèmiques et les caractéristiques socio-écologiques des milieux (i.e. leur niche socio-écologique). Nos résultats révèlent une grande variabilité dans les associations entre le service de production agricole et les services de régulation. Cette observation souligne le poids des modalités de gestion agricole dans l’orientation des associations entre services écosystèmiques. Par ailleurs, nous soulevons de nombreuses interrogations vis-à-vis de la robustesse des analyses courantes des bouquets de services écosystèmiques.L’influence de la résolution spatiale des données de modélisation sur la cartographie des services écosystèmiques est évaluée dans le chapitre II. Pour cela nous comparons les cartes utilisées dans le premier chapitre avec les informations apportées par un projet de cartographie de services écosystèmiques à haute résolution spatiale sur la région de Grenoble (projet ESNET). Cette analyse alimente une réflexion sur les limites des modèles utilisés pour cartographier les services écosystémiques.Dans le but d’améliorer la modélisation des services écosystémiques fournis par les terres agricoles, nous développons dans le chapitre III, une approche basée sur la télédétection pour cartographier l’utilisation des terres agricoles dans la région de Grenoble. L’utilisation conjointe de données satellitaires MODIS et RapidEye nous permet de déterminer les successions culturales sur 5 années à la résolution de la parcelle agricole. Validée par les données du registre parcellaire graphique, l’utilisation de ces données spatialement explicites améliore significativement notre capacité de cartographie de la production agricole et pourrait être utilisée pour cartographier de nombreux autres services écosystèmiques.Alors que le chapitre III est focalisé sur l’utilisation de la télédétection pour la cartographie de l’utilisation des terres agricoles, le chapitre IV propose une synthèse des autres utilisations des données de télédétection pouvant potentiellement contribuer à la modélisation des services écosystémiques. Ce travail est une mise en correspondance entre les capacités des approches de télédétection et les besoins des modélisateurs de services écosystémiques, sur la base d’une analyse bibliographique d’un large panel d’études de cartographie des services écosystémiques

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    Authors: Schaffer-Smith, Danica J.;

    Over 50% of Western Hemisphere shorebird species are in decline due to ongoing habitat loss and degradation. Many shorebird species require flooded habitat to rest and feed during migratory movements spanning thousands of miles between breeding and wintering grounds every spring and fall. In particular, shorebirds require shallowly flooded habitat (water depth We analyzed water extent dynamics across the Sacramento Valley of California, a globally important shorebird stopover site, for a 1983-2015 Landsat time series, and evaluated the effect of climate on water extent. Satellite measurements of surface water offer promise for understanding wetland habitat availability at broad spatial and temporal scales. A range of methods can detect open water from imagery, including supervised classification approaches and thresholds for spectral bands and indices. Thresholds provide a time advantage; however, there is no universally superior index, nor single best threshold for all instances. We used random forest to model the presence or absence of water from >6,200 reference pixels, and derived an optimal water probability threshold for our study area using receiver operating characteristic curves. An optimized mid-infrared (1.5–1.7 µm) threshold identified open water in the Sacramento Valley of California at 30-m resolution with an average of 90% producer’s accuracy, comparable to approaches that require more intensive user input. SLC-off Landsat 7 imagery was integrated by applying a customized interpolation that mapped water in missing data gaps with 99% user’s accuracy. On average we detected open water on ~26,000 ha (~3% of the study area) in early April at the peak of shorebird migration, while water extent increased five-fold after the migration rush. Over the last three decades, late March water extent declined by ~1,300 ha per year, primarily due to changes in the extent and timing of agricultural flood-irrigation. Water within shorebird habitats was significantly associated with an index of water availability at the peak of migration. Our approach can be used to optimize thresholds for time series analysis and near-real-time mapping in other regions, and requires only marginally more time than generating a confusion matrix. Two dimensional representations of flooded habitat are insufficient to capture dynamic changes within the narrow water depth range that is effectively accessible to migratory shorebirds. We developed a method to quantify shallow water habitat distributions in inland non-tidal wetlands, and assessed how water management practices have affected the amount of shorebird habitat in Sacramento National Wildlife Refuge Complex (SNWRC), California. We produced water depth distributions and modeled optimal habitat (Attempting to model the response of a community of shorebird species to flooded habitat dynamics from local to landscape scale necessitates a rich dataset including field observations of shorebird habitat use as well as information regarding regional habitat conditions over multiple time periods. Bringing together these data sources results in several challenges for classical statistical approaches, including overdispersion, fixed and random effects due to repeated measures, irregular temporal intervals, and missing data. We investigated how spring migration habitat use by 19 shorebird species at 327 wetland survey locations across SNWRC responded to flooded habitat fluctuations at multiple spatial scales from 1997-2015 using a generalized joint attribute modelling approach. In this analysis, we integrated shorebird census records and habitat conditions documented in the field with a suite of landscape-level habitat measurements derived from satellite imagery, as well as water availability, water allocation and land use information. We found that abundance by species peaked in late March and early April at SNWRC. Shorebird abundance responded positively to the amount of flooded habitat at a given wetland survey location. The total amount of water detected was the most important landscape habitat measure; shorebirds were less likely to be observed at high abundance at SNWRC wetlands when greater flooded habitat extent was present on the surrounding landscape. We found that human land and water management were influential drivers of shorebird habitat use. Water allocation information and reservoir storage resulted in better model fit (i.e., lower DIC) than including measures of surface water availability or drought conditions. Furthermore, the amount of landscape flooded habitat on agricultural land produced a better fit than considering all flooded habitat, or flooded habitat detected in wetlands. We found that the most relevant scale for measuring landscape flooded habitat was within 2-10 km of wetland survey locations; this distance could be a useful guideline for monitoring habitat conditions and targeting creation of supplemental habitat to bolster the existing wetland network in the Sacramento Valley.

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    IndraStra Global
    Doctoral thesis . 2018
    Data sources: IndraStra Global
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      IndraStra Global
      Doctoral thesis . 2018
      Data sources: IndraStra Global
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4 Research products
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Raturi, Ankita;

    Agriculture is a critical component of the human food system. Its coupling to the success of human societies and its impact on the environment is nontrivial. Varied efforts -- including new regulations, certifications, techniques and software -- exist to assess and improve the sustainability of agriculture. Multiple stakeholders in a fragmented field, with tensions and pulls in different directions, results in a duplication of efforts and disconnected data and processes.To explore the challenges that exist in modeling sustainable agriculture, I characterize environmental assessment as a modeling process, and secondly, characterize sustainable agricultural systems as a type of complex adaptive system. Framing the assessment process and system of interest in this manner permits the application of various techniques from software engineering, systems analysis, and human-computer interaction to tease apart the core issues and to subsequently respond to these challenges through design.First, I present an analysis of the capacity of Life Cycle Assessment (a formal and quantitative environmental assessment technique) to represent small- to medium-scale sustainability-oriented farms. Then, I described a qualitative field study, in which I visited 16 farms across California, interviewing sustainability-oriented farmers, and collecting samples of farm data. The goal of this study was to uncover how and why farmers model farms in practice, the nature and availability of farm data, and the experiences of farmers with various environmental assessment techniques.The findings of these two studies resulted in the articulation of domain-specific modeling requirements. These include: creating selective and partial system models, knitting together qualitative and quantitative data in system models, capturing both spatial and temporal structures, and all of this through models that are abstract yet grounded in real farm data.Building on these studies, I present MoSS: a framework to enable the Modeling of Sustainable Systems. MoSS consists of three parts: an abstract model, domain-specific elements to allow for modeling agricultural systems, and model 'perspectives' that allow for the assessment of the environmental performance of the system. I conducted a scenario-based evaluation of MoSS to assess its ability to express the varying dynamism and complexity of sustainable agricultural systems. MoSS addresses the core challenges involved in modeling sustainable agriculture, providing a consistent mechanism to capture the essence of farms.MoSS represents a step forward in grounded information design for sustainable agriculture, paving the way for the design of information management and environmental assessment tools that more closely meet the needs of small- to medium-scale farms and farmers. Through the work presented in this dissertation, I have also demonstrated how one may engage in applied and interdisciplinary software engineering research to support sustainable development.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ eScholarship - Unive...arrow_drop_down
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    Authors: Lin, Jeng-Hau;

    The entangled guardbands in terms of timing specification and energy budget ensure a system against faults, but the guardbands, meanwhile, impede the advance of a higher throughput and energy efficiency. To combat the over-designed guardbands in a system carrying out deep learning inference, we dive into the algorithmic demands and understand that the resource deficiency and hardware variation are the major reasons of the need of conservative guardbands. In modern convolutional neural networks (CNNs), the number of arithmetic operations for the inference could exceed tens of billions, which requires a sophisticated buffering mechanism to balance between resource utilization and throughput. In this case, the over-designed guardbands can seriously hinder system performance. On the other hand, timing errors can be incurred by the hardware variations including momentary voltage droops resulted from simultaneous switching noises, a gradually decreasing voltage level due to a limited battery, and the slow electron mobility incurred by the system power dissipation into heat. The timing errors propagating in a network can be a snowball in the beginning but ends up with a catastrophe in terms of a significant accuracy degradation.Knowing the need of guardbands originates from resource deficiency and timing errors, this dissertation focuses on cross-layer solutions to the problems of the high algorithmic demands incurred by deep learning methods and error vulnerability due to hardware variations. We begin with reviewing the methods and technologies proposed in the literature including weight encoding, filter decomposition, network pruning, efficient structure design, and precision quantizing. In the implementation of an FPGA accelerator for extreme-case quantization, binarized neural networks (BNN), we have realized more possible optimizations can be applied. Then, we extend BNN on the algorithmic layer with the binarized separable filters and proposed BCNNw/SF. Although the quantization and approximation benefit hardware efficiency to a certain extent, the optimal reduction or compression rate is still limited by the core of the conventional deep learning methods -- convolution. We, thus, introduce the local binary pattern (LBP) to deep learning because of LBP's low complexity yet high effectiveness. We name the new algorithm LBPNet, in which the feature maps are created with a similar fashion of the traditional LBP using comparisons. Our LBPNet can be trained with the forward-backward propagation algorithm to extract useful features for image classification. LBPNet accelerators have been implemented and optimized to verify their classification performance, processing throughput, and energy efficiency. We also demonstrate the error immunity of LBPNet to be the strongest compared with the subject MLP, CNN, and BCNN models since the classification accuracy of the LBPNet is decreased by only 10% and all the other models lose the classification ability when the timing error rate exceeds 0.01.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ eScholarship - Unive...arrow_drop_down
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  • Authors: Lasseur, Rémy;

    Societal changes over the last century have strongly affected the majority of ecosystem dynamics. Our society is facing a complex paradox: how to maintain decent livelihoods for the world population while limiting negative effects of human activities on ecosystems? The concept of ecosystem services has been proposed to contribute to the solving of this paradox and it holds strong expectations. My PhD research aims at assessing the contribution of ecosystem services mapping to the definition of patterns and drivers of landscape multifunctionality.Chapter I analyses the spatial associations between the agricultural production service and four regulating services over the agricultural lands of the Rhône-Alpes region (France). This work allows us to insist on the ways trade-off and synergies between ecosystem services are defined as well as on the characterization of bundles of ecosystem services. Furthermore, taking advantage of the "ecological niches” concept usually applied to biodiversity, we assess spatial matching between the supply of ecosystem services and the socio-ecological specificities of associated areas, i.e. their social-ecological niche. Our results highlight a large variability concerning associations between agricultural production and regulating services, which illustrates the strong influence of farming practices (e.g., in terms of intensity) in defining the strength of associations between multiple services. In addition, we raised the issue of the robustness of standard statistical analyses to consistently identify bundles of ecosystem services.Chapter II assesses the influence of spatial resolution of modeled data on ecosystem services mapping. To this end, we compare the maps used in the first chapter with high spatial resolution data provided at Grenoble area scale (in the context of the ESNET project). Based on this comparison, we discuss the limits of models used to map ecosystem services.To improve the mapping of ecosystem services supplied by agricultural areas, we propose, in chapter III, a remote sensing-based approach to map agricultural land uses at high resolution on Grenoble region. Simultaneous use of MODIS and Rapideye satellite data allows us to determine cropping successions for 5 years at farming plot scale. These spatially explicit data significantly improved our abilities to map agricultural productions and may be used to map several other ecosystem services.To complete the third chapter, chapter IV gives a synthesis of remote sensing approaches that could be used to map ecosystem services, focusing on methods that are not linked to land uses identification. Based on a wide panel of ecosystem services mapping studies, we highlight data currently needed to map ecosystem services. Then we bridge these needs and the potential of remote sensing approaches for ecosystem services modelers.; Les mutations de la société au cours du dernier siècle ont de fortes répercussions sur le fonctionnement de la majorité des écosystèmes. Notre société fait face à un paradoxe complexe défini par la nécessité de satisfaire des conditions de vie décentes d’une population mondiale croissante tout en limitant les impacts négatifs sur les écosystèmes. Le concept de service écosystémique a été proposé pour accompagner la résolution de ce paradoxe et de nombreuses attentes reposent sur ce concept. Mon travail de thèse a pour objectifs d’évaluer les apports actuels de la cartographie des services écosystémiques pour caractériser les patrons spatiaux et déterminants de la multifonctionnalité des territoires.Dans le chapitre I nous proposons une analyse des associations entre le service de production agricole et quatre services de régulation au niveau des surfaces agricoles de la région Rhône-Alpes (France). Ce travail nous permet de revenir sur la définition des compromis et synergies entre services écosystémiques aussi bien que sur le concept de bouquet de services écosystèmiques. Par ailleurs, en s’inspirant du concept de niche écologique pour les espèces, nous évaluons l’adéquation spatiale entre la fourniture de services écosystèmiques et les caractéristiques socio-écologiques des milieux (i.e. leur niche socio-écologique). Nos résultats révèlent une grande variabilité dans les associations entre le service de production agricole et les services de régulation. Cette observation souligne le poids des modalités de gestion agricole dans l’orientation des associations entre services écosystèmiques. Par ailleurs, nous soulevons de nombreuses interrogations vis-à-vis de la robustesse des analyses courantes des bouquets de services écosystèmiques.L’influence de la résolution spatiale des données de modélisation sur la cartographie des services écosystèmiques est évaluée dans le chapitre II. Pour cela nous comparons les cartes utilisées dans le premier chapitre avec les informations apportées par un projet de cartographie de services écosystèmiques à haute résolution spatiale sur la région de Grenoble (projet ESNET). Cette analyse alimente une réflexion sur les limites des modèles utilisés pour cartographier les services écosystémiques.Dans le but d’améliorer la modélisation des services écosystémiques fournis par les terres agricoles, nous développons dans le chapitre III, une approche basée sur la télédétection pour cartographier l’utilisation des terres agricoles dans la région de Grenoble. L’utilisation conjointe de données satellitaires MODIS et RapidEye nous permet de déterminer les successions culturales sur 5 années à la résolution de la parcelle agricole. Validée par les données du registre parcellaire graphique, l’utilisation de ces données spatialement explicites améliore significativement notre capacité de cartographie de la production agricole et pourrait être utilisée pour cartographier de nombreux autres services écosystèmiques.Alors que le chapitre III est focalisé sur l’utilisation de la télédétection pour la cartographie de l’utilisation des terres agricoles, le chapitre IV propose une synthèse des autres utilisations des données de télédétection pouvant potentiellement contribuer à la modélisation des services écosystémiques. Ce travail est une mise en correspondance entre les capacités des approches de télédétection et les besoins des modélisateurs de services écosystémiques, sur la base d’une analyse bibliographique d’un large panel d’études de cartographie des services écosystémiques

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    Authors: Schaffer-Smith, Danica J.;

    Over 50% of Western Hemisphere shorebird species are in decline due to ongoing habitat loss and degradation. Many shorebird species require flooded habitat to rest and feed during migratory movements spanning thousands of miles between breeding and wintering grounds every spring and fall. In particular, shorebirds require shallowly flooded habitat (water depth We analyzed water extent dynamics across the Sacramento Valley of California, a globally important shorebird stopover site, for a 1983-2015 Landsat time series, and evaluated the effect of climate on water extent. Satellite measurements of surface water offer promise for understanding wetland habitat availability at broad spatial and temporal scales. A range of methods can detect open water from imagery, including supervised classification approaches and thresholds for spectral bands and indices. Thresholds provide a time advantage; however, there is no universally superior index, nor single best threshold for all instances. We used random forest to model the presence or absence of water from >6,200 reference pixels, and derived an optimal water probability threshold for our study area using receiver operating characteristic curves. An optimized mid-infrared (1.5–1.7 µm) threshold identified open water in the Sacramento Valley of California at 30-m resolution with an average of 90% producer’s accuracy, comparable to approaches that require more intensive user input. SLC-off Landsat 7 imagery was integrated by applying a customized interpolation that mapped water in missing data gaps with 99% user’s accuracy. On average we detected open water on ~26,000 ha (~3% of the study area) in early April at the peak of shorebird migration, while water extent increased five-fold after the migration rush. Over the last three decades, late March water extent declined by ~1,300 ha per year, primarily due to changes in the extent and timing of agricultural flood-irrigation. Water within shorebird habitats was significantly associated with an index of water availability at the peak of migration. Our approach can be used to optimize thresholds for time series analysis and near-real-time mapping in other regions, and requires only marginally more time than generating a confusion matrix. Two dimensional representations of flooded habitat are insufficient to capture dynamic changes within the narrow water depth range that is effectively accessible to migratory shorebirds. We developed a method to quantify shallow water habitat distributions in inland non-tidal wetlands, and assessed how water management practices have affected the amount of shorebird habitat in Sacramento National Wildlife Refuge Complex (SNWRC), California. We produced water depth distributions and modeled optimal habitat (Attempting to model the response of a community of shorebird species to flooded habitat dynamics from local to landscape scale necessitates a rich dataset including field observations of shorebird habitat use as well as information regarding regional habitat conditions over multiple time periods. Bringing together these data sources results in several challenges for classical statistical approaches, including overdispersion, fixed and random effects due to repeated measures, irregular temporal intervals, and missing data. We investigated how spring migration habitat use by 19 shorebird species at 327 wetland survey locations across SNWRC responded to flooded habitat fluctuations at multiple spatial scales from 1997-2015 using a generalized joint attribute modelling approach. In this analysis, we integrated shorebird census records and habitat conditions documented in the field with a suite of landscape-level habitat measurements derived from satellite imagery, as well as water availability, water allocation and land use information. We found that abundance by species peaked in late March and early April at SNWRC. Shorebird abundance responded positively to the amount of flooded habitat at a given wetland survey location. The total amount of water detected was the most important landscape habitat measure; shorebirds were less likely to be observed at high abundance at SNWRC wetlands when greater flooded habitat extent was present on the surrounding landscape. We found that human land and water management were influential drivers of shorebird habitat use. Water allocation information and reservoir storage resulted in better model fit (i.e., lower DIC) than including measures of surface water availability or drought conditions. Furthermore, the amount of landscape flooded habitat on agricultural land produced a better fit than considering all flooded habitat, or flooded habitat detected in wetlands. We found that the most relevant scale for measuring landscape flooded habitat was within 2-10 km of wetland survey locations; this distance could be a useful guideline for monitoring habitat conditions and targeting creation of supplemental habitat to bolster the existing wetland network in the Sacramento Valley.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IndraStra Globalarrow_drop_down
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    IndraStra Global
    Doctoral thesis . 2018
    Data sources: IndraStra Global
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IndraStra Globalarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      IndraStra Global
      Doctoral thesis . 2018
      Data sources: IndraStra Global
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