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Abstract The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission was launched on 31st January 2015, with the aim of providing global soil moisture maps at 9 km spatial resolution by combining L-band radar and radiometer observations. However, after the SMAP radar became inoperable, NASA decided to utilize the Sentinel 1A/1B C-band SAR data in its place. The new version of baseline brightness temperature (Tb) downscaling algorithm for SMAP is tested using L-band airborne data to evaluate the capabilities of the C-band Sentinel-1A SAR relative to L-band radar data in downscaling the SMAP Tb for achieving high resolution brightness temperature. In this study, the downscaling algorithm used L-band airborne Synthetic Aperture Radar (SAR) backscatter (σ) collected from the fifth Soil Moisture Active Passive Experiment (SMAPEx-5) in south-eastern Australia to downscale 36 km L-band SMAP radiometer Tb pixels to 3 km and 9 km. The downscaling results were then compared with the published results using Sentinel-1A C-band backscatter, and evaluated against airborne 1 km resolution L-band passive microwave brightness temperature collected from SMAPEx-5. The results show that for vertical polarization the average Root Mean Square Error (RMSE) of downscaled Tb when compared with reference airborne Tb across 4 days at 9 km resolution were 4.9 K for L-band and 6.0 K for C-band, and increased to 9.3 K for L-band and 9.6 K for C-band at 3 km spatial resolution. Moreover, the correlation coefficient (R) of downscaled and reference Tb across the 4 days was 0.92 for L-band and 0.88 for C-band at 9 km, decreasing to 0.75 for L-band and 0.72 for C-band at 3 km spatial resolution. Accordingly, the RMSE increased and the correlation coefficient decreased when using C-band radar data in place of that at L-band. However, overall there is expected to be only a slight decrease in performance of the downscaling algorithm by using the Sentinel 1A data in place of the SMAP radar.

Surface currents and ocean swell are measured using an HF radar with a compact cross-loop antenna design. This unique direction-finding radar has been widely used for long-term monitoring and for coastal oceanography applications over the last ten years. Numerous studies have evaluated errors associated with these devices under a host of environmental and seasonal conditions, and reliable comparisons between HF radar surface current measurements and those from other technologies indicate a range of 0.08 to 0.15 ms−1, while internal error estimates that are made using the spread of data values in a time series or spectrum from the radar systems generally lead to errors of around 0.2 ms−1. These error estimates are typically based on manufacturer-recommended operating parameters that can include up to 25 specific parameters or assumptions made about the data. In particular, one of the dominant parameters in computing ocean surface currents from SeaSonde devices is the averaging time of both the power spectra and the computed radial components of the surface current vectors. This paper explores the relative effect of temporal averaging for two SeaSonde stations inWestern Australia. By analysing 31 days of radial data, we evaluate the statistical characteristics of noise in the spectra and determine the limits to the assumption that it represents a stationary ensemble of independent samples. The improvement in accuracy as we integrate over different time intervals from 10 to 180 minutes is determined by these characteristics. These results are applied to error analysis for the radial components of surface currents and compared with the errors in the gridded values of the radial components. Finally, the effects of calibrated and uncalibrated antenna patterns on the radial components is evaluated in the context of the temporal and spatial errors.

© 2018 IEEE. Fingerprinting method is one of the preferred method used for indoor localization using Wi-Fi signals because of its low complexity and its cost effectiveness. This paper proposes an indoor localization algorithm using fingerprinting method that is suitable for an indoor IoT application. The proposed algorithm combines the location estimates from two different approaches, deterministic and probabilistic, to estimate the target location. The proposed algorithm was tested for different conditions: Stationary and moving IoT targets, line-of-sight and non-line-of-sight indoor environments. The results showed the proposed combined algorithm performed better in terms of localization accuracy, precision and robustness than deterministic and probabilistic methods individually and similar past research.

The COVID-19 pandemic has spurred significant changes in the fields of economic development, social issues, everyday life, etc. Activities that used to depend on face-to-face communication were firstly suspended and then shifted to new forms of communication. This includes the public participation process in urban and spatial planning. Therefore, this study explores the new domain developed in urban and spatial planning with regard to public participation and surmises future realms in the post-pandemic era. On the occasion of the virtual collaboration platform Cyber Agora organized by the ISOCARP (International Society of City and Regional Planners), chosen participants got together virtually to share, discuss, and compare their practical knowledge in public participation before and during COVID-19. In addition, they addressed the potential benefits of shifting from traditional to virtual participation and potential benefits in the post-COVID-19 era. Considering the collected data and understanding them in the light of the available literature, this study concludes that the application of a combined approach (using both traditional and virtual modes of participation) is recommended because it would enable a larger number and higher diversity of participants. The study also elaborates particular modes of virtual participation with the pros and cons of their use in a particular context.

AbstractCritical transitions in ecosystem states are often sudden and unpredictable. Consequently, there is a concerted effort to identify measurable early warning signals (EWS) for these important events. Aquatic ecosystems provide an opportunity to observe critical transitions due to their high sensitivity and rapid response times. Using palaeoecological techniques, we can measure properties of time series data to determine if critical transitions are preceded by any measurable ecosystem metrics, that is, identify EWS. Using a suite of palaeoenvironmental data spanning the last 2,400 years (diatoms, pollen, geochemistry, and charcoal influx), we assess whether a critical transition in diatom community structure was preceded by measurable EWS. Lake Vera, in the temperate rain forest of western Tasmania, Australia, has a diatom community dominated by Discostella stelligera and undergoes an abrupt compositional shift at ca. 820 cal yr BP that is concomitant with increased fire disturbance of the local vegetation. This shift is manifest as a transition from less oligotrophic acidic diatom flora (Achnanthidium minutissimum, Brachysira styriaca, and Fragilaria capucina) to more oligotrophic acidic taxa (Frustulia elongatissima, Eunotia diodon, and Gomphonema multiforme). We observe a marked increase in compositional variance and rate‐of‐change prior to this critical transition, revealing these metrics are useful EWS in this system. Interestingly, vegetation remains complacent to fire disturbance until after the shift in the diatom community. Disturbance taxa invade and the vegetation system experiences an increase in both compositional variance and rate‐of‐change. These trends imply an approaching critical transition in the vegetation and the probable collapse of the local rain forest system.

The paper analyses the legally established practice of agriculture has been forced out of the urban environment as land value increases with higher population densities. It’s stated, that cities and surrounding urban environments have grown dependent upon regional areas and industrial agricultural practices to provide food for their increasing populations. Most commonly, urban agriculture is practiced by third world nations as a first line of defence against hunger and malnutrition or as poverty alleviation in times of economic stress. This paper argues that the practice of urban agriculture contributes to vital environmental recovery necessary in this, the geological age of the Anthropocene. As human activity continues to impact the functioning of earth systems at the planetary scale, we must actively assist nature to recover rather than assume that our existing environmental protection and conservation strategies are effective in preserving the natural environment.

This paper examines the lack of recognition and devaluing of the work of Australian farm women by examining the Australian Bureau of Agricultural and Resource Eco nomics (ABARE) report, Women on Farms (Gooday 1995). The paper argues that the work of ABARE and the Australian Bureau of Statistics (ABS) is fundamentally flawed by their definition of what constitutes valid work and by their perception that farm family labour can be differentiated by gender such that the work of men is accorded greater value while the work of women is reduced or ignored. By examining the nature of farm family labour, analysing the notions of work and by incorporating a radical fem inist framework to this analysis, this paper challenges ABS and ABARE to re-examine their position on the issue of work.