Spatially extensive high-resolution soil moisture mapping is valuable in practical forestry and land management, but challenging. Here we present a novel technique involving use of LIDAR-derived terrain indices machine learning (ML) algorithms capable accurately modeling at 2 m spatial resolution across the entire Swedish forest landscape. We used field data from about 20,000 sites Sweden to tr...

OBJECTIVE Pressure ulcers often occur at sites subjected to pressure and wetness. Although skin wetness is a risk factor for pressure ulcers,the mechanisms and effects of wetness versus urine constituents on skin breakdown is unclear. The hypothesis that wetness reduces skin hardness and, thereby, increases vulnerability of underlying blood vessels to pressure-induced flow reductions was tested...

Wetlands are a valuable ecosystem that provides various services to flora and fauna. This study developed compared deep shallow learning models for wetland classification across the climatically dynamic landscape of Alberta’s Parkland Grassland Natural Region. approach mapping entailed exploring multi-temporal (combination spring/summer fall months over 4 years—2017 202) multisensory (Sentinel ...

Forest fires are becoming a serious concern in Central European countries such as Austria (AT) and the Czech Republic (CZ). Mapping fire ignition probabilities across can be useful tool for risk mitigation. This study was conducted to: (i) evaluate contribution of variables obtained from open-source datasets (i.e., MODIS, OpenStreetMap, WorldClim) modeling probability at country level; (ii) inv...

Abstract. Hillslope similarity is an active topic in hydrology because of its importance improving our understanding hydrologic processes and enabling comparisons paired studies. In this study, we propose a holistic bottom-up hillslope clustering based on region's integrative hydrodynamic response quantified by the seasonal changes groundwater levels ΔP. The main advantage ΔP ability to capture...

Soil moisture is a crucial factor limiting the growth and survival of plants on Loess Plateau. Its level has severe impact plants’ development type distribution characteristics communities. This study area Jihe Basin in Plateau, China. Multiple linear regression models with different environmental variables (land use, topographic meteorological factors, etc.) were developed to simulate soil moi...

Abstract. In the domain of landslide risk science, susceptibility mapping (LSM) is very important, as it helps spatially identify potential landslide-prone regions. This study used a statistical ensemble model (frequency ratio and evidence belief function) two machine learning (ML) models (random forest XGBoost; eXtreme Gradient Boosting) for LSM in province Belluno (region Veneto, northeastern...

Landslides are a common geologic hazard that disrupts the social and economic balance of affected society. Therefore, identifying zones prone to landslides is necessary for safe living minimal disruption activities in event hazard. The factors causing often function local geo-environmental set-up need region-specific study. This study evaluates site characteristics primarily altered by anthropo...

In coarse resolution hydrological modeling, we face the problem of subgrid variability, effects which are difficult to express and often hidden in parameterization calibration. We present a numerical experiment with physically based model ParFlow-CLM quantify effect heterogeneities headwater catchments within cell size typically used for regional applications. simulate homogeneous domains topog...

Prediction of drought and flood events can be difficult, but the standardized precipitation index (SPI) calculated from monthly data may be a useful tool for predicting future dryness/wetness events in China. The rainy season SPI was calculated from monthly precipitation data from 3804 meteorological stations in China. The spatiotemporal variation, periodic change, and trend in rainy season SPI...