This paper discusses transitions in land use evidenced by the case of the Suoi Muoi catchment area in NW mountain of Vietnam. Land use transitions were detected from LANDSAT and SPOT satellite images taken over the last 40 years. The maps showing changes in land use were linked with biophysical properties of the land such as slope gradient, elevation and soil type, and cultural characteristic of various ethnic groups by means of logistic regression model.

A ca. 2010, 30m resolution map depicting annually tilled areas across the conterminous United States was developed. Input sources included fouryears, spanning 2008–2011, of annual national-level coverage Cropland Data Layer (CDL) land cover classifications as produced by the National Agricultural Statistics Service. Derived total land area under tillage from the aggregate CDL product equaled 112.8million hectares (278.7million acres).

South Atlantic coastal plain streams are unique and understudied freshwater environments that provide crucial habitats for a wide range of aquatic taxa. We investigated patterns in fish assemblages across South Carolina's coastal plain, and developed statistical models to identify the dominant multiscale abiotic environmental factors that influence assemblage structure.

Questions: Which are the factors that influence forest and shrubland loss and regeneration and their underlying drivers? Location: Central Chile, a world biodiversity hotspot. Methods: Using land-cover data from the years 1975, 1985, 1999 and 2008, we fitted classification trees and multiple logistic regression models to account for the relationship between different trajectories of vegetation change and a range of biophysical and socio-economic factors.

Air temperature can be estimated from remote sensing by combining information in thermal infrared and optical wavelengths. The empirical TVX algorithm is based on an estimated linear relationship between observed Land Surface Temperature (LST) and a Spectral Vegetation Index (NDVI). Air temperature is assumed to be equal to the LST corresponding to the effective full vegetation cover, and is found by extrapolating the line to a maximum value of NDVIₘₐₓ. The algorithm has been tested and reported in the literature previously.

Evidence from a multi-date regional-scale analysis of both high-flow and annual-average water quality data from Galloway, south-west Scotland, demonstrates that forest land cover continues to exacerbate freshwater acidification. This is in spite of significant reductions in airborne pollutants. The relationship between freshwater sulphate and forest cover has decreased from 1996 to 2006 indicating a decrease in pollutant scavenging.

Due to the high spectral resolution, hyperspectral images (HSI) have been widely used in land cover classification and material identification. Band selection is one of the necessary preprocessings to reduce the data volume and the redundancy therein for the subsequent analysis. Aiming at speeding up the search-based band selection process, this letter proposes a new technique from the perspective of spectral curve shape similarity.

A new subpixel mapping (SPM) algorithm combining pixel-level and subpixel-level spatial dependences is proposed in this letter. The pixel-level dependence is measured by the spatial attraction model (SAM) with either surrounding or quadrant neighbourhood, while the subpixel-level dependence is characterized by either the mean filter or the exponential weighting function. Both pixel-level and subpixel-level dependences are then fused as the weighted dependence in the constructed objective function.

Aim This paper describes the development of novel indices of bird‐habitat preference to examine bird species’ use of habitats and their distributions relative to habitats. It assesses the implications for bird conservation regionally and the scope for biodiversity assessments generally. Location A 200 km by 400 km area of farmland with seminatural and urban areas, covering south‐eastern England. Methods Cluster analysis was used to link birds to landscapes. Cluster centroid coordinate values were processed to derive indices of bird‐habitat preference.

Ecosystems around the world are already threatened by land‐use and land‐cover change, extraction of natural resources, biological disturbances, and pollution. These environmental stressors have been the primary source of ecosystem degradation to date, and climate change is now exacerbating some of their effects. Ecosystems already under stress are likely to have more rapid and acute reactions to climate change; it is therefore useful to understand how multiple stresses will interact, especially as the magnitude of climate change increases.

Population viability analyses provide a quantitative approach that seeks to predict the possible future status of a species of interest under different scenarios and, therefore, can be important components of large-scale species’ conservation programs. We created a model and simulated range-wide population and breeding habitat dynamics for an endangered woodland warbler, the golden-cheeked warbler (Setophaga chrysoparia). Habitat-transition probabilities were estimated across the warbler's breeding range by combining National Land Cover Database imagery with multistate modeling.

This study utilizes for the first time integrated knowledge-driven and data-driven methods for groundwater potential zoning in the hard-rock terrain of Ahar River catchment, Rajasthan, India by employing remote sensing, geographical information system, multi-criteria decision making (MCDM), and multiple linear regression (MLR) techniques.