Many arid and semi‐arid landscapes around the world are affected by a shift from grassland to shrubland vegetation, presumably induced by climate warming, increasing atmospheric CO₂concentrations, and/or changing land use. This major change in vegetation cover is likely sustained by positive feedbacks with the physical environment. Recent research has focused on a feedback with microclimate, whereby cold intolerant shrubs increase the minimum nocturnal temperatures in their surroundings.

The role of vegetation analysis by remote sensing (RS) and Geographical Information System (GIS) technology to support plans for sustainable development is discussed through a proposal of an index of ecosystem “integrity” or of regeneration capacity. The index is based on the vegetation “mass” of a given land cover type and the capacity that such mass has to contrast soil erosion. The index is therefore taking into account the effects of human activities and not merely the state of ecosystems in terms of their components.

A study on different types of bioindicator was carried out to detect river habitat quality in Central Italy. It was investigated the effectiveness of different bioindication models based on three biotic components: (i) vascular plants – hemeroby index for aquatic (Hw) and terrestrial species (Hₛ), and Ellenberg's soil nutrients indicator (N); (ii) aquatic macroinvertebrates – extended biotic index (EBI); (iii) soil microarthropods – index of soil biological quality (QBS-ar).

Regional faunas are structured by historical, spatial and environmental factors. We studied large‐scale variation in four ecologically different beetle groups (Coleoptera: Dytiscidae, Carabidae, Hydrophiloidea, Cerambycidae) along climate, land cover and geographical gradients, examined faunal breakpoints in relation to environmental variables, and investigated the best fit pattern of assemblage variation (i.e. randomness, checkerboards, nestedness, evenly spaced, Gleasonian, Clementsian).

Fecal pollution enters coastal waters through multiple routes, many of which originate from land-based activities. Runoff from pervious and impervious land surfaces transports pollutants from land to sea and can cause impairment of coastal ocean waters. To understand how land use practices and water characteristics influence concentrations of fecal indicator bacteria (FIB) and pathogens in natural waters, fourteen coastal streams, rivers, and tidal lagoons, surrounded by variable land use and animal densities, were sampled every six weeks over two years (2008 & 2009).

Estimation of land use during the Holocene is crucial to understand impacts of human activity on climate change in preindustrial period. Until now it is still a key issue to reconstruct amount and spatial distribution of prehistoric land use due to lack of data. Most reconstructions are simply extrapolations of population, cleared land amount per person and land suitability for agriculture. In this study, a new quantitative prehistoric land use model (PLUM) is developed based on semi-quantitative predictive models of archeological sites.

Dams strongly impair the fluvial environment by altering downstream flows. We analysed riverscapes downstream of three dams and hypothesized that different dam types in rivers with diverse history of land-use and land cover (LULC) change have significant riparian cover differences at diverse biogeomorphic units (banks, riverbanks, islands). We performed a temporal comparison using pre-dam (1965) and post-dam (2013) high-resolution airborne imagery. A new approach was devised to correct the spatial offset between historical and contemporary imagery.

Steppe, an important belt to protect North China from dust storms, is vulnerable and has been degraded in recent decades because of climatic change and heavy grazing. In order to improve steppe management, this study presents a framework for the monitoring of grazing intensity in Xilingol steppe of middle Inner Mongolia, northern China, by integrating the CENTURY ecosystem model-based simulation and remotely sensed MODIS data-based inversion.

The paper gives an overview on the trends in the usage of landscape metrics as indicators for: land use changes, habitat functions (biodiversity, habitats), landscape regulating functions (fire control, microclimate control, etc.), and information functions (landscape aesthetics). We reviewed papers published in international peer-reviewed journals that are indexed by the Institute of Science Information (ISI) Web of Knowledge from 2000 to 2010. The terms “landscape metrics”, “landscape indexes” and “landscape indices” were searched.

Water resources are influenced by various factors such as weather, topography, geology, and environment. Therefore, there are many difficulties in evaluating and analyzing water resources for the future under climate change. In this paper, we consider climate, land cover and water demand as the most critical factors affecting change in future water resources. We subsequently introduce the procedures and methods employed to quantitatively evaluate the influence of each factor on the change in future water resources.

Mapping and monitoring wetland ecosystems over large geographic areas based on remote sensing is challenging because of the spatial and spectral complexities of the inherent ecosystem dynamics. The main objective of this research was to develop and evaluate a new method for detecting and quantifying wetland changes in the Northern Gulf of Mexico (NGOM) region using multitemporal, multispectral, and multisensor remotely sensed data.

Surface albedo determines radiative forcing and is a key parameter for driving Earth’s climate. Better characterization of surface albedo for individual land cover types can reduce the uncertainty in estimating changes to Earth’s radiation balance due to land cover change. This paper presents new albedo look-up maps (LUM) using a multi-scale hierarchical approach based on MODIS BRDF/albedo products and Landsat imagery. Ten years (2001-2011) of MODIS BRDF/albedo products were used to generate global albedo climatology.