Humans have fundamentally altered global patterns of biodiversity and ecosystem processes. Surprisingly, existing systems for representing these global patterns, including biome classifications, either ignore humans altogether or simplify human influence into, at most, four categories. Here, we present the first characterization of terrestrial biomes based on global patterns of sustained, direct human interaction with ecosystems. Eighteen “anthropogenic biomes” were identified through empirical analysis of global population, land use, and land cover.

Precise soil quality assessment is critical for designing sustainable agriculture policies, restoring degraded soils, carbon (C) modeling, and improving environmental quality. Although the consequences of soil quality reduction are generally recognized, the spatial extent of soil degradation is difficult to determine, because no universal equation or soil quality prediction model exists that fits all ecoregions. Furthermore, existing soil organic C (SOC) models generate estimates with uncertainties that may exceed 50%.

The paper presents the development of a groundwater potential index (GWPI) map of the Araniar River basin, India, through an overlay analysis of climatic, geologic, geomorphic, soil and land use/land cover features of the basin using Landsat5 Thematic Mapper (TM) data and ArcGIS9.2. A correlation analysis of the developed GWPI map was carried out with a yield map of the basin to standardize the weights assigned to each theme.

Oil exploitation and road development have strongly fragmented the coastal landscapes, leading to profound ecological consequences. The dynamic relationships between oil wells, roads, and landscape fragmentation indices in the Yellow River Delta, China were explored. Oil wells, roads and land cover were mapped from TM images in 1992, 2000, 2006, and 2009, respectively. Changes and relationships were compared among three selected typical sections using linear regression models.

Over the last few decades, many researchers have produced landslide susceptibility maps using different techniques including the probability method (frequency ratio), the analytical hierarchy process (AHP), bivariate, multivariate, logistics regression, fuzzy logic and artificial neural network In addition, a number of parameters such as lithology, slope, aspect, land cover, elevation, distance to stream, drainage density, distance to lineament, seismicity, and distance to road are recommended to analyze the mechanism of landslides.

Lithology is an important characteristic of the terrestrial surface, whose properties influence chemical weathering rates. Specifically non-silicate minerals may contribute significantly to the weathering derived fluxes from silicate-dominated lithological classes. The Japanese Archipelago consists of predominantly silicate-dominated lithologies with a high proportion of volcanics.

Dissolved organic matter (DOM) influences the physical, chemical, and biological properties of aquatic ecosystems. We hypothesized that controls over spatial variation in DOM quantity and composition (measured with DOM optical properties) differ based on the source of DOM to aquatic ecosystems. DOM quantity and composition should be better predicted by land cover in aquatic habitats with allochthonous DOM and related more strongly to nutrients in aquatic habitats with autochthonous DOM.

A set of landscape metrics is used to study the long-term environmental transformation of a typical coastal Mediterranean area from 1850 to 2005. Our figures show a dramatic environmental deterioration between 1950 and 2005. The main proximate drivers of this landscape degradation are the effects of urban sprawl on former agricultural areas located in the coastal plains, together with the abandonment and reforestation of hilly slopes intercepted by low-density residential areas, highways, and other linear infrastructures.

We investigated the role of land use/land cover and agriculture practices on stream dissolved organic carbon (DOC) dynamics in the Willow Slough watershed (WSW) from 2006 to 2008. The 415km² watershed in the northern Central Valley, California is covered by 31% of native vegetation and the remaining 69% of agricultural fields (primarily alfalfa, tomatoes, and rice). Stream discharge and weekly DOC concentrations were measured at eight nested subwatersheds to estimate the DOC loads and yields (loads/area) using the USGS developed stream load estimation model, LOADEST.

Various spectral data preprocessing approaches have been used to improve endmember extraction for urban landscape decomposition, yet little is known of their comparative adequacy for impervious surface mapping. This study tested four commonly used spectral data treatment strategies for endmember derivation, including original spectra, image fusion via principal component analysis, spectral normalization, and the minimum noise fraction (MNF) transformation.

Based on the fact that streamwater quality reflects landscape conditions, the objectives of this study were: to investigate nitrogen (N), carbon (C), and major ion concentrations in six streams crossing minimally disturbed Atlantic Forest areas, with similar geomorphological characteristics; to determine N and C fluxes in one of these pristine streams (Indaiá); and assess the impact of human activity on the biogeochemistry of two other streams in the same region, crossing urbanized areas.

Optimization techniques are often used in remote sensing retrieval of surface or atmospheric parameters. Nevertheless, different algorithms may exhibit different performances for the same optimization problem. Comparison of some classic optimization approaches in this article aims to select the best method for retrieving aerosol opacity, or even for other parameters, from remotely sensed data. Eight frequently used optimization algorithms were evaluated using both simulated data and actual AATSR (advanced along track scanning radiometer) data.