Pixel-based and object-oriented processing of Chinese HJ-1-A satellite imagery (resolution 30 m) acquired on 23 July 2009 were utilized for classification of a study area in Budapest, Hungary. The pixel-based method (maximum likelihood classifier for pixel-level method (MLCPL)) and two object-oriented methods (maximum likelihood classifier for object-level method (MLCOL) and a hybrid method combining image segmentation with the use of a maximum likelihood classifier at the pixel level (MLCPL)) were compared. An extension of the watershed segmentation method was used in this article.

In this article, a new index, the visible and shortwave infrared drought index (VSDI), is proposed for monitoring both soil and vegetation moisture using optical spectral bands. VSDI is defined as , where ρ represents the reflectance of shortwave infrared (SWIR) red and blue channels, respectively. VSDI is theoretically based on the difference between moisture-sensitive bands (SWIR and red) and moisture reference band (blue), and is expected to be efficient for agricultural drought monitoring over different land-cover types during the plant-growing season.

Land use change and landscape patterns have a large effect on land productivity and ecosystem biodiversity. Based on geographical information system technology and remote sensing data related to land use and land cover of Jiangsu and Zhejiang provinces and Shanghai (Jiang-Zhe-Hu area), we analyzed patterns of landscape change and predicted land use dynamics using the CA-MARKOV model. We also analyzed the conversion rate and area among landscape classes using the CA-Markov model.

In Central Asia, water is a particularly scarce and valuable good. In many ecosystems of this region, the vegetation development during the growing season is dependent on water provided by rainfall. With climate change, alterations of the seasonal distribution of precipitation patterns and a higher frequency of extreme events are expected. Vegetation dynamics are likely to respond to these changes and thus ecosystem services will be affected.

Preserving large tracts of natural habitats is essential to maintain biodiversity. Nevertheless, even large areas may still suffer from less “visible” impacts such as loss of ecological processes. Because mapping ecological processes over large scales is not practical, an alternative is to map surrogate species that are key for those processes.

Understanding the effects of land-cover alterations on ecosystem functioning has become a major challenge in ecological research during the last decade. This has stimulated a rapid growth in research investigating the links between land-cover change and biotic interactions, but to date no study has evaluated the progress towards achieving this scientific goal.

The breakdown of socialism caused massive socio-economic and institutional changes that led to substantial agricultural land abandonment. The goal of our study was to identify the determinants of agricultural land abandonment in post-Soviet Russia during the first decade of transition from a state-controlled economy to a market-driven economy (1990–2000). We analyzed the determinants of agricultural land abandonment for approximately 150,550km² of land area in the provinces (oblasts) of Kaluga, Rjazan, Smolensk, Tula and Vladimir in European Russia.

The provision of ecosystem services at the landscape level can be significantly influenced by land management practices. Within an agriculturally dominated case study area in Saxony, Germany, a more detailed land use classification, which includes differentiated information on agricultural management practices, was utilized within the raster-based planning support tool GISCAME. “Management” refers to typical, regional crop rotations and soil tillage practices.

The paper looks at two metrics of flood events: flood severity (related to flood frequency) and flood magnitude (related to flood severity, as above, but also to flood duration and affected area). A time series of flood information, over 25 years, collected by the Dartmouth Flood Observatory, is used to describe the spatio-temporal variability of large floods in Europe. Direct factors responsible for changes in flood severity and magnitude over time may be related to both climate and ground surface changes.

Identifying the primary causes and examining the processes and trends of land use change are crucial for land use planning, utilization of regional resources and environment management. Combining the ecological quantity analysis with GIS technology, based on the land use data and remote sense images, the changes of land use and land cover and the driving force were analyzed in the mainstream of the Tarim River from 1973 to 2005.

The Zagros region of western Iran has been affected by the recent changes both in amount and in structure of forest cover. We evaluated the influence of several driving forces on forest cover and structure, including socioeconomic (urban and rural population and rural income) and climatic (mean annual rainfall and mean annual temperature) variables. We acquired all time series Landsat images of a study site from 1972 to 2009. The images were classified to produce a land cover map of each year.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) has generated one of the most complete high-resolution digital topographic data sets of the world to date. The ASTER GDEM covers land surfaces between 83° N and 83° S at a spatial resolution of 1 arc-second (approximately 30 m at the equator). As an improvement over Shuttle Radar Topography Mission (SRTM) coverage, the ASTER GDEM will be a very useful product for many applications, such as relief analysis, hydrological studies, and radar interferometry.