Understanding vegetation dynamics provides information on changes in land cover that can directly be related to regional changes in the climate system. In data-sparse regions, i.e. northwest Morocco studies are limited by the availability of comprehensive information on precipitation.

Surface and groundwater quantity and quality data are essential in many hydrologic applications and to the development of hydrologic and water quality simulation models. We describe the hydrologic data available in the Little Washita River Experimental Watershed (LWREW) of the Southern Great Plains Research Watershed (SGPRW) and Fort Cobb Reservoir Experimental Watershed (FCREW), both located in southwest Oklahoma.

Estimates of changes and possible causes of regional soil organic carbon (SOC) are critical for evaluation of potential responses of terrestrial biosphere to global changes. A total of 382 soil samples, collected in the 1980s from four counties in the Corn Belt of northeastern China, and of 1,514 samples collected in 2005 from the same area, were examined for SOC concentrations. Spatial and temporal SOC concentrations were evaluated after the 25-year interval using geostatistics and kriging interpolation method.

Social and economic considerations are among the most important drivers of landscape change, yet few studies have addressed economic and environmental influences on landscape structure, and how land ownership may affect landscape dynamics. Watersheds in the Olympic Peninsula, Washington, and the southern Appalachian highlands of western North Carolina were studied to address two questions: (1) Does landscape pattern vary among federal, state, and private lands?

In pace with rapid urbanization, urban areas in many countries are undergoing huge changes. The large spectral variance and spatial heterogeneity within the ‘buildings’ land cover class, as well as the similar spectral properties between buildings and other urban structures, make building change detection a challenging problem. In this work, we propose a set of novel building change indices (BCIs) by combining morphological building index (MBI) and slow feature analysis (SFA) for building change detection from high-resolution imagery.

A Boosted Genetic Fuzzy Classifier (BGFC) is proposed in this paper, for land cover classification from multispectral images. The model comprises a set of fuzzy classification rules, which resemble the reasoning employed by humans. Fuzzy rules are generated in an iterative fashion, incrementally covering subspaces of the feature space, as directed by a boosting algorithm. Each rule is able to select the required features, further improving the interpretability of the obtained model.

Texture provides spatial features complementary to spectral information in land cover classification of high spatial resolution imagery. In texture classification, window size is an important factor influencing classification accuracy, but selecting the optimal window size is difficult. In this paper, we propose an optimized window size texture classification method which can solve the window size selection problem.

There are many factors controlling groundwater pollution and vulnerability. However, the factors’ weights are still not reasonably investigated. In order to assess groundwater quality and the controlling factors in semiarid region, 178 groundwater samples were collected and analyzed for salinity and nitrate content. New statistical techniques of prediction profiler and hierarchical cluster combined with geographic information systems (GIS) were used to assess the groundwater quality based on three categorical controlling factors; landuse/ land cover (LULC), soil texture, and aquifer type.

Over the past few decades, groundwater has become an essential commodity owing to increased demand as a result of growing population, industrialization, urbanization and so on. The water supply situation is expected to become more severe in the future because of continued unsustainable water use and projected change in hydrometeorological parameters due to climate change.

The angular effects of emissivity are ignored in current land surface temperature (LST) products. As a result, the directionality of these LST products limits their further application in many fields. Accurate correction of the angular problem of LST products requires explicit understanding of the angular effects of emissivity at the pixel scale. Currently, nearly ten years of global emissivity products of MODIS are available. However, the pixel-scale directionality of emissivity has never been analyzed.

Deciduous shrub density and landcover are increasing across many areas of the Arctic. Shrub growth may be promoted by a snow–shrub feedback whereby relatively tall shrubs accumulate deeper snow, raising winter soil temperature minima, increasing microbial activity, and enhancing soil solution nitrogen (N). Although there is good evidence for the above components of the hypothesis, it has not yet been determined if shrubs can access the elevated N pool generated by deepened snow.

Extensive groundwater withdrawals in urban areas may cause water shortages, land subsidence, and water quality problems. The Quetta Valley is the largest population center in Balochistan province in western Pakistan. This area is arid and groundwater is the main water source for domestic and agricultural use. This work presents global positioning system (GPS) data and assessment of spatial and temporal variations in water levels. GPS data from two stations from mid-2006 to the beginning of 2009 show subsidence rate of 10� cm\year.