The regular drought episodes in South Africa highlight the need to reduce risk by both policy and local community actions. Environmental socioeconomic factors Africa's agricultural system have been affected past, creating cascading pressures on nation's agro-economic water supply systems. Therefore, understanding key drivers of all components through a comprehensive assessment must be undertaken order inform proactive management. This paper presents, for first time, national irrigated...

Researchers and engineers have increasingly used Deep Learning (DL) for a variety of Remote Sensing (RS) tasks. However, data from local observations or via ground truth is often quite limited training DL models, especially when these models represent key socio-environmental problems, such as the monitoring extreme, destructive climate events, biodiversity, sudden changes in ecosystem states. Such cases, also known small pose significant methodological challenges. This review summarises...

Accurate classification and mapping of crops is essential for supporting sustainable land management. Such maps can be created based on satellite remote sensing; however, the selection input data optimal classifier algorithm still needs to addressed especially areas where field scarce. We exploited intra-annual variation temporal signatures remotely sensed observations used prior knowledge crop calendars development a two-step processing chain classification. First, Landsat-based time-series...

Globally, drought constitutes a serious threat to food and water security. The complexity multivariate nature of challenges its assessment, especially at local scales. study aimed assess spatiotemporal patterns crop condition impact the spatial scale field management units with combined use time-series from optical (Landsat, MODIS, Sentinel-2) Synthetic Aperture Radar (SAR) (Sentinel 1) data. Several indicators were derived such as Normalized Difference Vegetation Index (NDVI), Moisture...

By 2050, two-third of the world’s population will live in cities. In this study, we develop a framework for analyzing urban growth-related imperviousness North Rhine-Westphalia (NRW) from 1980s to date using Landsat data. For baseline 2017-time step, official geodata was extracted generate labelled data ten classes, including three classes representing low, middle, and high level imperviousness. We used output 2017 classification information based on radiometric bi-temporal change detection...

ABSTRACT Effective management of water resources in anthropogenically shaped lowlands requires a comprehensive understanding hydrological processes and balancing various effects complex settings, especially like lowland hydrology. Unlike mountainous headwater catchments with shallow soils, hydrology is typically dominated by groundwater dynamics, often exhibiting pronounced spatial correlation lengths, though other factors may also contribute. This necessitates consideration distant...

Abstract. Drought research addresses one of the major natural hazards that threatens progress toward Sustainable Development Goals. This study aims to map evolution and interdisciplinarity drought over time across regions, offering insights for decision-makers, researchers, funding agencies. By analysing more than 130 000 peer-reviewed articles indexed in SCOPUS from 1901 2022 using latent Dirichlet allocation (LDA) topic modelling, we identified distinct shifts priorities emerging trends....

The resilience of regional hydrology in human-influenced landscapes is a key challenge the context climate change. Lusatia East Germany an example region facing complex challenges water management due to massive open pit mining activities as well being subject increasing climate-induced scarcity. This study presents comprehensive validation and comparative analysis multi-temporal satellite-based evapotranspiration (ET) data at multiple spatial resolutions including 2000m Central Europe...

Eastern Cape Province in South Africa has experienced extreme drought events during the last decade. In Africa, different land management systems exist belonging to two tenure classes: commercial large scale farming and communal small-scale subsistence farming. Communal lands are often reported be affected by degradation among others considered as trigger for this process. Against background, we analyzed vegetation response through assessing productivity trends monitoring intensity,...

Monitoring land degradation (LD) to improve the measurement of sustainable development goal (SDG) 15.3.1 indicator (“proportion that is degraded over a total area”) key ensure more future. Current frameworks rely on default medium-resolution remote sensing datasets available assess LD and cannot identify subtle changes at sub-national scale. This study first adapt local in interplay with high-resolution imagery monitor extent semiarid Kiteto Kongwa (KK) districts Tanzania from 2000–2019. It...

Researchers and engineers have increasingly used Deep Learning (DL) for a variety of Remote Sensing (RS) tasks. However, data from local observations or via ground truth is often quite limited training DL models, especially when these models represent key socio-environmental problems, such as the monitoring extreme, destructive climate events, biodiversity, sudden changes in ecosystem states. Such cases, also known small pose significant methodological challenges. This review summarises...

Predicting crop yield using deep learning (DL) and remote sensing is a promising technique in agriculture. In smallholder agriculture (< 2 ha), where 84% of the farms operate globally, it crucial to build model that can be useful across several fields (high spatial transferability). However, enhancing transferability small-scale setting faces significant challenges, including autocorrelation, heterogeneity scale dependence dynamics, as well need address limited data points. This study aimed...

Abstract Achieving land degradation neutrality (LDN) has been proposed as a way to stem the loss of resources globally. To date, LDN operationalization at country level remained challenge both from policy and science perspective. Using an approach incorporating cloud‐based geospatial computing with machine learning, national datasets cover, productivity dynamics, soil organic carbon stocks were developed. example Botswana, proportion degraded assessed. Between 2000 2015, grassland lost...

Abstract Increasing population and a severe water crisis are imposing growing pressure on Iranian cropping systems to increase crop production meet the rising demand for food. Little is known about separate contribution of trends variability harvested area yield in severely drought-prone areas such as Iran. In this study we (a) quantify importance 12 most important annual crops under rainfed irrigated conditions (b) test how well can be explained by drought dynamics. We use remote sensing...

The intensification of food production systems has resulted in landscape simplification, with trees and hedges disappearing from agricultural land, principally industrialized countries. However, more recently, the potential agroforestry small woody features (SWFs), e.g., hedgerows, woodlots, scattered groups trees, to sequester carbon was highlighted as one strategies combat global climate change. Our study aimed assess extent SWFs embedded within landscapes Germany, estimate their stocks,...

Abstract Maize production in low-yielding regions is influenced by climate variability, poor soil fertility, suboptimal agronomic practices, and biotic influences, among other limitations. Therefore, the assessment of yields to various management practices is, others, critical for advancing site-specific measures enhancement. In this study, we conducted a multiseason calibration evaluation DSSAT–CERES-Maize model assess maize yield response two common cultivars grown Trans Nzoia County Kenya...

Peatlands play a pivotal role in global carbon cycling and the conservation of biodiversity even though they cover small fraction Earth's terrestrial surface. These ecosystems are, however, increasingly vulnerable due to climate change impacts anthropogenic activities, leading significant degradation many areas. This review compiles analyses various studies that employ remote sensing for comprehensive peatland mapping monitoring. Remote offers detailed insights into critical features,...

Timely monitoring of agricultural production and early yield predictions are essential for food security. Crop growth conditions related to climate variability impacted by extreme events. Remotely sensed time-series could be used study the in crop production. However, choice remotely data methods is still an issue, as different datasets have spatiotemporal characteristics. Our primary goal was test algorithms several estimation U.S. at county field scale. For a county-level analysis,...

Abstract Population growth and increasing demand for agricultural production continue to drive global cropland expansions. These expansions lead the overexploitation of fragile ecosystems, propagating land degradation, loss natural diversity. This study aimed identify factors driving use/land cover changes (LULCCs) subsequent expansion in Trans Nzoia County Kenya. Landsat images were used characterize temporal LULCCs 30 years derive using change detection. Logistic regression (LR), boosted...

The effects of land cover configuration on surface temperature (LST) have been extensively documented. However, few studies examined the woody features and their LST in agricultural landscapes. A study was conducted Brandenburg, Germany to examine potential impacts small (SWF) adjacent areas. High-resolution maps at regional scale, together with remotely sensed proxies vegetation conditions (such as topography crop types), were used quantify impact SWFs gradient different distances during...

Abstract Agricultural production assessments are crucial for formulating strategies closing yield gaps and enhancing efficiencies. While in situ crop measurements can provide valuable accurate information, such approaches costly lack scalability large-scale assessments. Therefore, modeling remote sensing (RS) technologies essential assessing conditions predicting yields at larger scales. In this study, we combined RS a growth model to assess phenology, evapotranspiration (ET), dynamics grid...

Drought is one of the extreme climatic events that has a severe impact on crop production and food supply. Our main goal to test suitability remote sensing-based indices detect drought impacts from global regional scale. Moderate resolution imaging spectroradiometer (MODIS) based imagery, spanning 2001 2017 was used for this task. This includes normalized difference vegetation index (NDVI), land surface temperature (LST), evaporative stress (ESI), which ratio actual potential...