We investigated the relative importance of stand and landscape characteristics in the invasion of a nonnative shrub, Amur honeysuckle, in 40 woodlots in an agricultural matrix in southwest Ohio. We quantified stand characteristics that could influence invasibility, the intrinsic susceptibility of an area to invasion, including woodlot size, perimeter-to-area ratio, tree basal area, and stand age.

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.

Accurate identification of urban land use is essential for many applications. However, as physical surfaces of land-cover types are not necessarily related to their use and economic function, differentiating among thematically detailed urban land uses (single-family residential, multi-family residential, commercial, industrial, etc.) using remotely sensed imagery is a challenging task, particularly over large areas.

The purpose of this study was to investigate the spatial distribution of annual soil loss in the Danjiangkou Reservoir Region, China. Soil erosion was estimated by integrating the universal soil loss equation (USLE) model with GIS. The main factors affecting soil erosion including rainfall erosivity, soil erodibility, slope length and steepness, cover and management factor, and conservation supporting practice factor were determined from precipitation data, soil sample analysis, digital elevation model, land use and land cover, and empirical assessment, respectively.

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.

This study combined uncertainty analysis of carbon emissions with local stakeholders' perspectives to develop an effective Reducing Emission from Deforestation and Degradation (REDD+) scheme at the district level. Uncertainty of carbon emission estimates depends on scale while local stakeholders' views on plausible REDD+ schemes influence and limit transaction costs. The uncertainty analysis formed the basis for determining an appropriate scale for monitoring carbon emission estimates as performance measures for REDD+ incentives.

Water consumed through evapotranspiration (ET) impacts local and regional hydrologic regimes on various spatial and temporal scales. Estimating ET in the Great Plains is a prerequisite for effective regional water resource management of the Ogallala (High Plains) Aquifer, which supplies vital water resources in the form of irrigation for extensive agricultural production.

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.

Area-based information obtained from remote sensing and aerial photography is often used in studies on ecological footprint and sustainability, especially in calculating biocapacity. Given the importance of the modifiable areal unit problem (MAUP; i.e. the scale dependency of area-based information), a comprehensive understanding of how the changes of biocapacity across scales (i.e. the resolution of data) is pivotal for regional sustainable development.

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).

Herbaceous biomass, harvested and handled as hay, has potential for bioenergy production. In the Upper Southeast, fields that cannot be competitively managed to produce another crop can produce an acceptable yield of switchgrass. Using a delayed harvest (crop is allowed to dry standing in the field), switchgrass can be harvested from production fields over a 6-month period. This gives a significant advantage over a crop residue, like corn stover, which is collected over a 5-week harvest season in the Midwest. The Southeast has the potential to be a major bioenergy production region.

In this letter, we present the methodology and accuracy assessment of a new regional 250-m spatial resolution land cover map of insular Southeast Asia. Nearly 500 daily Moderate Resolution Imaging Spectroradiometer images (acquired 2 January–3 July 2010) were used in the production of the map. Additionally, peatland maps, elevation information and Daichi-Advanced Land Observing Satellite mosaic data were utilized in the mapping process.