Improved change vector analysis (ICVA) has recently been promoted as an effective algorithm for multi-class change detection. Unlike the conventional change vector analysis (CVA) that works on two-dimensional data, the ICVA works on multidimensional data. However, ICVA has limitations when the change vector is fraught with similar direction cosine values. In this article, a new algorithm, named median change vector analysis (MCVA) has been proposed for multi-class change detection.

This article introduces an innovative approach using marker-controlled watershed segmentation (WS) in the Vegetation–Impervious Surface–Soil (V–I–S) feature space for urban land-use and land-cover (LULC) classification. The complement (e.g., the inverse) of the V–I–S feature space image shows depressions, which can be treated as topographic watersheds and they correspond to LULC classes. WS partitions the complement of V–I–S feature space image into LULC regions based on user-specified initial markers.

The impacts of human activities on the natural environment are becoming more and more pronounced. One of the most obvious areas of concern is land use and land cover change. As a result, projects such as Urbanization and Global Environmental Change (UGEC) launched by the International Human Dimension Programme on Global Environmental Change (IHDP) and the Global Land Project (GLP) jointly proposed by IHDP and IGBP were developed to study the interactions between human activities, land systems, and natural environmental change.

In Mediterranean mountains, the abandonment of traditional land-uses is promoting a rapid forest expansion. This trend may be exacerbated by nature reserves, which further limit human disturbance in mountain contexts. We investigated whether ecological parameters, landscape structure, and management policy influenced vegetation cover/dynamics over a 14-year period in the Pollino National Park, a large protected area in southern Italy. Based on remote sensed and field data we obtained land-cover maps referred to 2004, 1997, and 1990.

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed in Ohio, USA, which was one of the largest hyperspectral image acquisitions. A hierarchical approach was employed using two different classification algorithms: ‘image object segmentation’ for level 1 and ‘spectral angle mapper’ (SAM) for level 2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination.

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.

Landslides are a major geologic hazard with estimated tens of deaths and $1–2 billion in economic losses per year in the US alone. The island of Puerto Rico experiences one or two large events per year, often triggered in steeply sloped areas by prolonged and heavy rainfall. Identifying areas susceptible to landslides thus has great potential value for Puerto Rico and would allow better management of its territory. Landslide susceptibility zonation (LSZ) procedures identify areas prone to failure based on the characteristics of past events.

Historical land-cover changes in three delta regions in Southeast Asia are assessed by using selected Landsat images from 1990 to 2005. Potential inundation areas of the delta regions for different return periods are estimated by using digital elevation model data and extreme-value distribution of annual maximum river discharges. The results indicate significant changes of natural land cover within the potential inundation areas due to agricultural exploitation and industrialization. Implications for flood-mitigation policies are discussed.

Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale.

This paper examines the potential effects of urbanization on streamflow in Maine, USA, from 1950 to 2000. The study contrasts nine watersheds in southern Maine, which has seen steady urban growth over the study period, with nine rural watersheds from northern Maine. Historical population data and current land cover data are used to develop an urbanization score for each watershed. Trends in watershed urbanization over the study period are compared to trends in ecologically relevant streamflow characteristics.

Mapping key areas for ecosystem service (ES) supply is essential for the development of strategies that will ensure their future supply. Given the rapid development in this area of research, we performed a review of different approaches used to map ES, with a special focus on those that use social–ecological data. We used an analytical framework based on five criteria for analyzing and comparing the methodological approaches: the types of ES, availability of data sources, types of data sources, spatial scale, and methods used to model ES.

To assess future interactions between the environment and human well-being, spatially explicit ecosystem service models are needed. Currently available models mainly focus on provisioning services and do not distinguish changes in the functioning of the ecosystem (Ecosystem Functions – ESFs) and human use of such functions (Ecosystem Services – ESSs). This limits the insight on the impact of global change on human well-being. We present a set of models for assessing ESFs and ESSs.