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Displaying 501 - 505 of 1195Spatial Assessment of Soil Organic Carbon Density Through Random Forests Based Imputation
Regional estimates of soil carbon pool have been made using various approaches that combine soil maps with sample databases. The point soil organic carbon (SOC) densities are spatialized employing approaches like regression, spatial interpolation, polygon based summation, etc. The present work investigates a data mining based spatial imputation for spatial assessment of soil organic carbon density. The study area covers Andhra Pradesh and Karnataka states of India.
Mapping Wetland Areas Using Landsat-Derived NDVI and LSWI: A Case Study of West Songnen Plain, Northeast China
Increasing interest in wetlands for environmental management requires an understanding of the location, spatial extent, and configuration of the resource. The National Wetlands Inventory is the most commonly used data source for this information. However, its accuracy is limited in some contexts, such as agricultural and forested wetlands. An large number of studies have mapped wetlands worldwide from the perspective of land use and land cover change. However, information on the actual wetland planting areas annually is limited, which greatly impacts ongoing research.
Health, safety, and environmental risk assessment of steel production complex in central Iran using TOPSIS
This research was carried out with the aim of presenting an environmental management plan for steel production complex (SPC) in central Iran. Following precise identification of the plant activities as well as the study area, possible sources of environmental pollution and adverse impacts on the air quality, water, soil, biological environment, socioeconomic and cultural environment, and health and safety of the employees were determined considering the work processes of the steel complex. Afterwards, noise, wastewater, and air pollution sources were measured.
new data aggregation technique to improve landscape metric downscaling
Scale is a fundamental concept in landscape ecology and considerable attention has been given to the scale-dependent relationships of landscape metrics. Many metrics have been found to exhibit very consistent scaling relationships as map resolution (i.e., pixel or grain size) is increased. However, these scaling relationships tend to break down when attempting to ‘downscale’ them, and the scaling function is often unable to accurately predict metric values for finer resolutions than the original data. The reasons for this breakdown are not well understood.
Dublin SURGE Project: geochemical baseline for heavy metals in topsoils and spatial correlation with historical industry in Dublin, Ireland
The Dublin SURGE (Soil Urban Geochemistry) Project is Dublin’s first baseline survey of heavy metals and persistent organic pollutants in topsoils and is part of a Europe-wide initiative to map urban geochemical baselines in ten cities. 1,058 samples were collected as part of a stratified random sampling programme in the greater Dublin area to give an overview of baseline conditions in the city. Samples were analysed for 31 inorganic elements including heavy metals.