Super-resolution mapping (SRM) is a process that provides land-cover spatial distribution with a spatial resolution finer than the size of a remotely sensed image pixel. Usually, the fraction images generated from soft classifiers are used as constraints in SRM, making the accurate estimation of fraction images an important task in SRM. Supervised fuzzy c-means (sFCM), which belongs to the fuzzy-set technology commonly applied for unmixing mixed pixels, is capable of providing accurate estimates of fraction images used for SRM.

Intensification of human activities has caused drastic losses in semi-natural habitats, resulting as well in declining connectivity between remaining fragments. Successful future restoration should therefore increase both habitat area and connectivity. The first steps in a framework for doing so are addressed here, which involve the mapping of past habitat change.

This research investigated the effects of climate and land cover change on variation in sagebrush ecosystems. We combined information of multi-year sagebrush distribution derived from multitemporal remote sensing imagery and climate data to study the variation patterns of sagebrush ecosystems under different potential disturbances. We found that less than 40% of sagebrush ecosystem changes involved abrupt changes directly caused by landscape transformations and over 60% of the variations involved gradual changes directly related to climatic perturbations.

Controls on chemical weathering, such as bedrock geology, runoff, and temperature, are considered to be the primary drivers of Si transport from the continents to the oceans. However, recent work has highlighted terrestrial vegetation as an important control over Si cycling. Here we show that at the regional scale (Southern New England, USA), land use/land cover (LULC) is an important variable controlling the net transport of Si from the land to the sea, accounting for at least 40% of dissolved Si (DSi) fluxes.

Variations of forest area and vegetation activity in China from 2001 to 2009 were investigated using the IGBP land-cover data and the EVI (Enhanced Vegetation Index) dataset derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) products in the 3 years of 2001, 2005, and 2009. The area of forests in China had increased by about 10%, and the changes in EVI-indicated vegetation activity showed large regional differences. The EVI decreased between 2001 and 2005 while it increased between 2005 and 2009 in most areas of southern China.

Forest area determined from remote sensing-derived land cover maps alone at moderate resolution may not appropriately reflect dynamics of housing development in the forested wildland-urban interface (WUI). We conducted a study to quantify how housing development could affect estimates of forest carbon sequestration (FCS) in northern New England, where the percentage of WUI in relation to total land area is nearly double the national average.

Ecosystem goods and services have been brought to the forefront of policy making all over the world. It is acknowledged that these goods and services underpin human well-being. The provision of water resources is amongst those services that have raised more attention, given its unquestionable value and global threats like climatic change. Nevertheless, the biophysical basis that determines the land-use/water interactions has been often ignored. For the formulation of sound decisions, it is necessary to extend the empirical basis that determines these complex relations.

The territorial approach to rural development highlights the role of local actors, networks, culture, nature and landscape amenities. The Organization for Economic Co-operation and Development (OECD) definition of rurality is, however, not capable of dealing with local and community definitions of rurality, which vary from study to study. In everyday life, physical planners, rural policymakers and local rural actors need a consistent definition of rurality.

Rapidly increasing demand for food, fiber, and fuel together with new technologies and the mobility of global capital are driving revolutionary changes in land use throughout the world. Efforts to increase land productivity include conversion of millions of hectares of rangelands to crop production, including many marginal lands with low resistance and resilience to degradation. Sustaining the productivity of these lands requires careful land use planning and innovative management systems.

A critical challenge for range scientists is to provide input to management decisions for land units where little or no data exist. The disciplines of range science, basic ecology, and global ecology use different perspectives and approaches with different levels of detail to extrapolate information and understanding from well-studied locations to other land units.

Due to the progressive increase in population, sustainable development of desert land in Egypt has become a strategic priority in order to meet the increasing demands of a growing population for food and housing. Such obligations require efficient compilation of accurate land-cover information in addition to detailed analysis of archival land-use changes over an extended time span. In this study, we applied a methodology for mapping land cover and monitoring change in patterns related to agricultural development and urban expansion in the desert of the Kom Ombo area.

Classification of the Earth's surface types is one of the important remote-sensing applications of radar polarimetry. An unsupervised classification scheme based on the use of entropy and alpha angle is widely used for land-cover classification using multi-polarization radar images. The polarimetric entropy and the alpha angle are used to characterize a target's randomness and scattering mechanism, respectively. Here, we replace the entropy by the Gini index. Evaluation of the Gini index is computationally efficient.