We evaluated Canada Warbler (Cardellina canadensis) responses to changes in habitat characteristics (landscape metrics, landcover, and microhabitat features) at multiple spatial scales resulting from timber harvests (clear-cut, heavy partial, and light partial) between 1996 and 2009. Relative abundance of Canada Warblers decreased over time on our West Virginia study area (Wildlife and Ecosystem Research Forest) and within the Appalachian Bird Conservation Region.

Land-cover updating from remote-sensing data is an effective means of obtaining timely land-cover information. An automatic approach integrating iterative training sample selection (ITSS) and a Markov Random Field (MRF) model is proposed in this study to overcome the land-cover update problem when no previous remote-sensing data corresponding to the land-cover data are available.

The European Commission Directorate-General for the Environment (DG Environment) and the European Environmental Agency (EEA) have identified soil organic matter conservation and mitigation of soil loss by erosion as priorities for the collection of policy-relevant soil data at the European scale. In order to support European Union (EU) soil management policies, soil quality indicators are required that can be applied using harmonized data for the EU Member States.

Understanding species distributions and population responses to environmental parameters is important for addressing landscape-level species conservation. We assessed American black bear (Ursus americanus) resource selection based on spatial distribution of a recolonizing population in Mississippi, USA. Given the philopatric behavior of female bears and the risk-disturbance hypothesis, we predicted that bears recolonizing Mississippi would occupy areas close to their source population but avoid areas near roads and with greater human population density.

In this article, we evaluate and compare results from three integrated assessment models (GCAM, IMAGE, and ReMIND/MAgPIE) regarding the drivers and impacts of bioenergy production on the global land system. The considered model frameworks employ linked energy, economy, climate and land use modules. By the help of these linkages the direct competition of bioenergy with other energy technology options for greenhouse gas (GHG) mitigation, based on economic costs and GHG emissions from bioenergy production, has been taken into account.

In the last decades, due to climate changes, soil deterioration and land use/land cover (LULC) changes, land degradation (LD) has become one of the most important issues at the global, regional and local scale. In concrete terms, LD determines a reduction in the productivity of a territory and in its capacity of providing ecosystem goods and services. “Syndromes” of LD can be assessed in the past, and scenarios, conversely, can be developed for the future, as information baselines for sustainable land management strategies and interventions.

An optimized artificial immune network-based classification model, namely OPTINC, was developed for remote sensing-based land use/land cover (LULC) classification.

The economic value of the Tonle Sap Lake Floodplain to Cambodia is arguably among the highest provided to a nation by a single ecosystem around the world. Nonetheless, the Mekong River Basin is changing rapidly due to accelerating water infrastructure development (hydropower, irrigation, flood control, and water supply) and climate change, bringing considerable modifications to the flood pulse of the Tonle Sap Lake in the foreseeable future.

The frequency and size of wildfires within the Mojave Desert are increasing, possibly due to climate and land cover changes and associated increases in non-native invasive plant biomass, as measured by normalized difference vegetation index (NDVI). These patterns are of particular concern to resource managers in regions where native plant communities are not well adapted to fire.

Boreal forests are a critical component of the global carbon cycle, and timely monitoring allows for assessing forest cover change and its impacts on carbon dynamics. Earth observation data sets are an important source of information that allow for systematic monitoring of the entire biome. Landsat imagery, provided free of charge by the USGS Center for Earth Resources Observation and Science (EROS) enable consistent and timely forest cover updates.

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.

Observational evidence of the impacts of land use/land cover change (LULCC) on changes in surface solar radiation (SSR) in eastern China (EC) during 1979–2008 are identified by using diurnal temperature range as a proxy of SSR and by using observation minus reanalysis approach to disentangle these effects. For the period 1979–2008, the impact of LULCC is shown as a reduction in SSR in most stations in EC, whereas SSR in the reanalysis data has increased at nearly every location.