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Although satellite-based soil moisture products are useful at regional and global scales, they do not meet the needs of users who require high-resolution information for applications such as precision agriculture or catchment hydrologic modeling. The advent of uncrewed aerial systems (UASs) has opened new opportunities for bridging this need. We offer one of the very first validation studies on a dry-down event captured by a novel L-band radiometer onboard a Black Swift Technologies fixed-wing S2 UAS. A fallow cornfield at the Beltsville Agricultural Research Center was selected as a study area to validate volumetric soil moisture estimates in mid-April. By leveraging a comparable radiative transfer model to that of soil moisture active passive and soil moisture ocean salinity derived products, brightness temperature retrievals from this sensor are shown to successfully capture a week of dry-down poststorm event, as validated by HydraGO probe estimates (calibrated with gravimetric samples) and a nearby soil climate analysis network station. However, with a reported spatially averaged bias of −0.107 m3/m3 (compared to calibrated moisture values) and an ubRMSE of 0.028 m3/m3 potential concerns remain regarding the sensor calibration, vegetation and surface roughness corrections, and georeferencing. Nevertheless, given the potential of UAS for on-demand, high-resolution soil moisture retrievals, this collaborative effort provides critical feedback for informing future applications and improvements in the field of passive microwave remote sensing.

Abstract Background The identification and mapping of at-risk populations at a lower administrative level than the district are prerequisites for the planning, resource allocation and design of impactful control intervention measures. Thus, the objective of the current study was to conduct sub-district precision mapping of soil-transmitted helminthiasis (STH) and schistosomiasis in 29 districts of north-western Tanzania using the current recommended World Health Organization criteria. Methods A cross-sectional survey was conducted in 145 schools between March and May 2021. A urine filtration technique was used for the quantification of Schistosoma haematobium eggs, whereas quantification of Schistosoma mansoni and STH eggs was done using the Kato–Katz technique. Microhaematuria was examined using a urine dipstick. Results The overall prevalences of any STH and schistosome infections were 9.3% [95% confidence interval (95%CI) 8.6–9.9] and 14.6% (95%CI 13.9–15.4), respectively. The overall prevalence of S. mansoni was 8.7% (95%CI 8.1–9.3), and 36.4%, 41.6%, and 21.9% of the children had low, moderate, and heavy infections, respectively. The overall prevalence of S. haematobium was 6.1% (95%CI 5.5–6.5), and 71.7% and 28.3% of the infected children had light and heavy intensity infections, respectively. The prevalence of microhaematuria was 7.3% (95%CI 6.7–7.8), with males having the highest prevalence (8.4%, P

Soil salinity is one of the more serious problems that cause soil degradation, particularly in semi-arid and arid regions. In agricultural lands, it threatens plant growth and productivity, which requires specific management decisions for various inputs, such as fertilizers. Accurate prediction and mapping of soil salinity have become possible through remote sensing techniques. The focus of this research is to derive soil salinity from spectral indices measured from different bands of sentinel-2 satellite in order to delineate management zones (MZs). Four spectral salinity indices were used for the purpose of this study, using blue, green, red, and NIR bands in different combinations. Exponential regression best describes the relationship between salinity indices and soil electrical conductivity (EC) through groundtruthing. The results indicate that salinity indices 2 ( B l u e × R e d G r e e n ) and 4 ( G r e e n + R e d 2 ) (SI2 and SI4) outperformed the other indices and could describe 70% and 71% of the variability in soil EC with prediction models of: S o i l E C = 0.319 e 0.0007 × S I 2 and S o i l E C = 0.3418 e 0.0006 × S I 4 , respectively. The generated models were validated by normalized root mean square error and the d coefficient of agreement. The results of the best-fit models were 16.5% and 0.86 for SI2 and 16.7% and 0.84 for SI4, respectively. The box-and-whiskers diagram proposed that the field can be divided into four soil EC-dependent groups, which are considered MZs to support a variety of management decisions. This study shows that through sentinel-2 multispectral imagery, the spatial variability of soil salinity can be mapped and used as a basis for MZs within the studied region. [ABSTRACT FROM AUTHOR]

Background: The identification and mapping of at-risk populations at a lower administrative level than the district are prerequisites for the planning, resource allocation and design of impactful control intervention measures. Thus, the objective of the current study was to conduct sub-district precision mapping of soil-transmitted helminthiasis (STH) and schistosomiasis in 29 districts of north-western Tanzania using the current recommended World Health Organization criteria. Methods: A cross-sectional survey was conducted in 145 schools between March and May 2021. A urine filtration technique was used for the quantification of Schistosoma haematobium eggs, whereas quantification of Schistosoma mansoni and STH eggs was done using the Kato–Katz technique. Microhaematuria was examined using a urine dipstick. Results: The overall prevalences of any STH and schistosome infections were 9.3% [95% confidence interval (95%CI) 8.6–9.9] and 14.6% (95%CI 13.9–15.4), respectively. The overall prevalence of S. mansoni was 8.7% (95%CI 8.1–9.3), and 36.4%, 41.6%, and 21.9% of the children had low, moderate, and heavy infections, respectively. The overall prevalence of S. haematobium was 6.1% (95%CI 5.5–6.5), and 71.7% and 28.3% of the infected children had light and heavy intensity infections, respectively. The prevalence of microhaematuria was 7.3% (95%CI 6.7–7.8), with males having the highest prevalence (8.4%, P < 0.001). The prevalences of Trichuris trichiura, Ascaris lumbricoides and hookworm were, respectively, 1.3% (95%CI 0.1–1.5), 2.9% (95%CI 2.5–3.3) and 6.2% (95%CI 5.7–6.7). Most of the children infected with STH had light to moderate intensities of infection. The overall prevalence of co-infection with STH and schistosomiasis was 19.1%. The prevalence of schistosomiasis (P < 00.1) and STH (P < 0.001) varied significantly between schools and sub-districts. Schistosoma mansoni and S. haematobium were observed in 60 and 71 schools, respectively, whereas any STH was observed in 49 schools. In schools where schistosomiasis was observed, prevalence was < 10% in 90.8% of them, and ranged from ≥ 10% to < 50% in the other 9.2%. In schools where any STH was observed, the prevalence was < 10% in 87.7% of them. Conclusions: The data reported here show that schistosomiasis and STH are widely distributed around Lake Victoria. In most of the schools where schistosomiasis and STH occurred the transmission thresholds were low. These data are important and need to be taken into consideration when decisions are made on the implementation of the next round of mass chemotherapies for schistosomiasis and STH in Tanzania. [ABSTRACT FROM AUTHOR]

Bacillus anthracis, the causative agent of anthrax, is a spore‐forming bacterium that primarily affects herbivorous livestock, wildlife and humans exposed to direct contact with infected animal carcasses or products. To date, there are a limited number of studies that have delineated the potential global distribution of anthrax, despite the importance of the disease from both an economic and public health standpoint. This study compiled occurrence data (n = 874) of confirmed human and animal cases from 1954 to 2021 in 94 countries. Using an ensemble ecological niche model framework, we developed updated maps of the global predicted ecological suitability of anthrax to measure relative risk at multiple scales of analysis, including a model for circumpolar regions. Additionally, we produced maps quantifying the disease transmission risk associated with anthrax to cattle, sheep and goat populations. Environmental suitability for B. anthracis globally is concentred throughout Eurasia, sub‐Saharan Africa, the Americas, Southeast Asia, Australia and Oceania. Suitable environments for B. anthracis at the circumpolar scale extend above the Arctic Circle into portions of Russia, Canada, Alaska and northern Scandinavia. Environmental factors driving B. anthracis suitability globally include vegetation, land surface temperature, soil characteristics, primary climate conditions and topography. At the circumpolar scale, suitability is influenced by soil factors, topography and the derived climate characteristics. The greatest risk to livestock is concentrated within the Indian subcontinent, Australia, Anatolia, the Caucasus region, Central Asia, the European Union, Argentina, Uruguay, China, the United States, Canada and East Africa. This study expands on previous work by providing enhanced knowledge of the potential spatial distribution of anthrax in the Southern Hemisphere, sub‐Saharan Africa, Asia and circumpolar regions of the Northern Hemisphere. We conclude that these updated maps will provide pertinent information to guide disease control programs, inform policymakers and raise awareness at the global level to lessen morbidity and mortality among animals and humans located in environmentally suitable areas. [ABSTRACT FROM AUTHOR]

Soil acidification is a major and growing concern in many cropping regions globally. Whilst spatial variability in acidification is a common consideration in the management of soil health and fertility at sub-paddock scale, insufficient focus has been directed toward the identification of this variability. Suitability of portable visible near infrared reflectance (vis–NIR) spectroscopy was assessed in this study as a potential technique to achieve rapid, precise, inexpensive and spatially specific quantification of key soil parameters to inform lime requirements. Spectral fingerprints were taken using a 1 ha grid sampling approach, with four sampling protocols investigated as follows, scans: (i) directly on cleared soil surfaces; (ii) on 0–100 mm undisturbed cores; (iii) on dried 0–100 mm cores; and finally (iv) on dried, ground, sieved and mixed cores. Data was analysed using a partial least squares regression (PLSR) model to identify the strength of linear relationship between reference chemistry data and predictions derived from spectral readings. Lime requirement maps using vis–NIR predictions were then theoretically compared against traditional aggregated sampling patterns while considering the trade-offs between accuracy, economics and agronomy associated with the identification of spatial variability. The vis–NIR measurements demonstrated moderate predictive capabilities in field for determining pH (R2 = 0.3–0.5) and liming requirements (R2 = 0.5–0.6) rapidly at high spatial resolution. Vis–NIR in field mapping techniques, which enable the use of site specific management of soil resources, were found to positively redirect lime resources from alkaline areas toward acidic areas of the paddock, resulting in minimal difference to overall expenditure on lime purchase and potential for increased agronomic benefits over the long-term. Further spectral library development, calibration, and research on in-field sampling methods is recommended. [ABSTRACT FROM AUTHOR]

Background: Fine-scale mapping of schistosomiasis to guide micro-targeting of interventions will gain importance in elimination settings, where the heterogeneity of transmission is often pronounced. Novel mobile applications offer new opportunities for disease mapping. We provide a practical introduction and documentation of the strengths and shortcomings of GPS-based household identification and participant recruitment using tablet-based applications for fine-scale schistosomiasis mapping at sub-district level in a remote area in Pemba, Tanzania. Methods: A community-based household survey for urogenital schistosomiasis assessment was conducted from November 2020 until February 2021 in 20 small administrative areas in Pemba. For the survey, 1400 housing structures were prospectively and randomly selected from shapefile data. To identify pre-selected structures and collect survey-related data, field enumerators searched for the houses' geolocation using the mobile applications Open Data Kit (ODK) and MAPS.ME. The number of inhabited and uninhabited structures, the median distance between the pre-selected and recorded locations, and the dropout rates due to non-participation or non-submission of urine samples of sufficient volume for schistosomiasis testing was assessed. Results: Among the 1400 randomly selected housing structures, 1396 (99.7%) were identified by the enumerators. The median distance between the pre-selected and recorded structures was 5.4 m. A total of 1098 (78.7%) were residential houses. Among them, 99 (9.0%) were dropped due to continuous absence of residents and 40 (3.6%) households refused to participate. In 797 (83.1%) among the 959 participating households, all eligible household members or all but one provided a urine sample of sufficient volume. Conclusions: The fine-scale mapping approach using a combination of ODK and an offline navigation application installed on tablet computers allows a very precise identification of housing structures. Dropouts due to non-residential housing structures, absence, non-participation and lack of urine need to be considered in survey designs. Our findings can guide the planning and implementation of future household-based mapping or longitudinal surveys and thus support micro-targeting and follow-up of interventions for schistosomiasis control and elimination in remote areas. Trial registration ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493 [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the main applications of UAVs (Uncrewed Aerial Vehicles) is precise mapping; however, most of the studies are specialized either on rapid-mapping without focusing on characteristic point localization, or point positioning without concentrating upon the real-time or high accuracy. In this study, an active localization method for GNSS (Global Navigation Satellite System)-degraded environments is proposed using a custom-built UAV as an aerial geodetic total station platform. The UAV equipped with an RTK (Real-time-Kinematics)-GNSS receiver and an optimized gimbal that carries an optical sensor and a laser range-finder, is able to autonomously detect, track and localize fiducial targets, using the UAV's orientation and position, exporting their coordinates in WGS 84 geodetic reference system during the flight. The system has been validated with a significant number of experiments in various environments with increasing difficulty, providing a three-dimensional error in a range of 4–15 cm. • Implementation of an aerial surveying framework. • Real-time precise localization method for GNSS-degraded environments. • Autonomous target detection and tracking. • Mobile application for the design and control of the localization method in the field. • System evaluation in various GNSS-degraded environments. [ABSTRACT FROM AUTHOR]

Photogrammetric processing is available in various software solutions and can easily deliver 3D pointclouds as accurate as 1 pixel. Certain applications, e.g., very accurate shape reconstruction in industrial metrology or change detection for deformation studies in geosciences, require results of enhanced accuracy. The tie-point extraction step is the opening in the photogrammetric processing chain and therefore plays a key role in the quality of the subsequent image orientation, camera calibration and 3D reconstruction. Improving its precision will have an impact on the obtained 3D. In this research work we describe a method which aims at enhancing the accuracy of image orientation by adding a second iteration photogrammetric processing. The result from the classical processing is used as a priori information to guide the extraction of refined tie-points of better photogrammetric quality. Evaluated on indoor and UAV acquisitions, the proposed methodology shows a significant improvement on the obtained 3D point accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Posidonia oceanica is an endemic seagrass from the Mediterranean Sea. It is an indicator of water quality and of the ecological state of coastal ecosystems. The aim of this paper is to test acoustic telemetry for monitoring the position of P. oceanica meadow limits with varied types. After evaluating the accuracy of the system, we present results from a spatiotemporal survey of P. oceanica meadows on nine sites located on the French coast. The method has been demonstrated to be highly efficient for high precision underwater mapping regardless of meadow type, with 1cm accuracy for a distance of 40m between the base and the pointer. A temporal survey led at Cerbere–Banyuls shows a weak global progression of 4m2 (progression of 26m2 - regression of 22m2) between 2006 and 2010. Finally, we discuss the cost and efficiency of this method, and wether it should be generalized for further studies. [Copyright &y& Elsevier]