This paper presents an integrated approach to landscape functioning assessment combining energy efficiency and hydrochemical balance studies. Energy balance is expressed by surface temperature while hydrochemical balance is illustrated by electric conductivity and selected hydrochemical parameters. Six model sub-watersheds with different land use situated in southern Bohemia were chosen to show the influence of landscape management on landscape functioning.

Geomorphological mapping plays an essential role in understanding Earth surface processes, geochronology, natural resources, natural hazards and landscape evolution. It involves the partitioning of the terrain into conceptual spatial entities based upon criteria that include morphology (form), genetics (process), composition and structure, chronology, environmental system associations (land cover, soils, ecology), as well as spatial topological relationships of surface features (landforms).

Land use/land cover monitoring and mapping is crucial to efficient management of the land and its resources. Since the late 1980s increased attention has been paid to the use of coarse resolution optical data. The Moderate Resolution Imaging Spectroradiometer (MODIS) has features, which make it particularly suitable to earth characterization purposes. MODIS has 10 products dedicated mainly to land cover characterization and provides three kinds of data: angular, spectral and temporal. MODIS data also includes information about the data quality through the ‘Quality Assessment’ product.

Essential to analyses of forest-cover change is application of geospatial empirical or semi-empirical models of transition potentials based on the likelihood that forest land would change to non-forested land or vice versa depending on prevailing conditions of land-use change. Modeling land-cover as a function of land-use aids in understanding pertinent land-cover dynamics. This can enable forecasting of ramifications of current conversion processes on land designated for agriculture or development.

Corn stover as well as perennial grasses like switchgrass (Panicum virgatum) and miscanthus are being considered as candidates for the second generation biofuel feedstocks. However, the challenges to biofuel development are its effects on the environment, especially water quality. This study evaluates the long-term impacts of biofuel production alternatives (e.g., elevated corn stover removal rates and the potential land cover change) on an ecosystem with a focus on biomass production, soil erosion, water quantity and quality, and soil nitrate nitrogen concentration at the watershed scale.

Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38year Landsat image time-series archive (1972–2010).

Land cover fractions (LCFs) derived through spectral mixture analysis are useful in understanding sub-pixel information. However, few studies have been conducted on the analysis of time-series LCFs. Although multi-scale comparisons of spectral index, hard classification, and land surface temperature images have received attention, rarely have these approaches been applied to LCFs.

Vector-to-raster conversion is a process accompanied with errors. The errors are classified into predicted errors before rasterization and actual errors after that. Accurate prediction of the errors is beneficial to developing reasonable rasterization technical schemes and to making products of high quality. Analyzing and establishing a quantitative relationship between the error and its affecting factors is the key to error prediction.

Global climate models (GCM) investigating the effects of land cover on climate have found that replacing extra-tropical forest with cropland promotes cooling. We compared cropland and forest surface temperatures across the continental United States in 16 cells that were approximately 1°×2° using 1km² MODIS land surface temperature (LST) data and land cover from the 0.0009km² National Land Cover Database (NLCD). We found that forest surface temperatures tended to be cooler than cropland surface temperatures. This relationship held for spring, summer, fall, and annually.

In the present study, Remote Sensing Technique and GIS tools were used to prepare landslide susceptibility map of Shiv-khola watershed, one of the landslide prone part of Darjiling Himalaya, based on 9 landslide inducing parameters like lithology, slope gradient, slope aspect, slope curvature, drainage density, upslope contributing area, land use and land cover, road contributing area and settlement density applying Analytical Hierarchy Approach (AHA). In this approach, quantification of the factors was executed on priority basis by pair-wise comparison of the factors.

Development of accurate classification methods for rapidly changing catchments like that of Lake Basaka is fundamental to better understanding the catchment dynamics, which were not addressed in previous studies. Thus, the aim of this study was to map the decadal land use/cover (LUC) regimes of the Lake Basaka catchment, utilizing time series of LANDSAT images and to analyse the changes that occurred at different time periods. Both unsupervised and supervised image classification systems were utilized in Earth Resources Data Analysis System (ERDAS) Imagine (9.1).

The wild boar is the target species selected for developing a GIS model of potential habitat for big game species, mainly using many GIS layers and kilometric abundance indices (KAI). We identify and weight environmental factors that determine the suitability for wild boar populations in a Mediterranean region, highly influenced by urban and agro-forestry activities. Marina Baja region (Spain) is selected to make a regional analysis. In the GIS modelling process, a suitability value is assigned to each pixel, which represents the habitat preference of the species.