In this work, we used the Regional Hydro‐Ecological Simulation System (RHESSys) model to examine runoff sensitivity to land cover changes in a mountain environment. Two independent experiments were evaluated where we conducted simulations with multiple vegetation cover changes that include conversion to grass, no vegetation cover and deciduous/coniferous cover scenarios. The model experiments were performed at two hillslopes within the Weber River near Oakley, Utah watershed (USGS gauge # 10128500).

Dust emission and deposition are associated with several factors such as surface roughness, land cover, soil properties, soil moisture (SM), and wind speed (WS). A combination of land surface and remote-sensing models has recently been investigated for dust detection and monitoring. The thermal bands of the Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI) satellite are widely used for qualitative detection of dust over desert because of their high spectral and temporal resolutions.

This work evaluates the changes of nitrate-nitrogen (NO₃-N), ammonium-nitrogen (NH₄-N), total phosphorus (P) and chemical oxygen demand (COD) concentrations in stream waters as related to the land use/land cover (LULC) alterations within eight small (5–39� km²) tile-drained catchments in the southern part of The Czech Republic in the period 1993–2010, when massive grassing of arable land took place. The robust tools of seasonal Mann–Kendall trend test and LOcally WEighted Scatterplot Smoothing methods were employed to reveal trends of the monitored parameters with adjustment to hydrology.

The Land Transformation Model (LTM) is hierarchically coupled with meso-scale drivers to project urban growth across the conterminous USA. Quantity of urban growth at county and place (i.e., city) scales is simulated using population, urban density and nearest neighbor dependent attributes. We compared three meso-scale LTMs to three null models that lack meso-scale drivers. Models were developed using circa 1990–2000 data and validated using change in the 2001 and 2006 National Land Cover Databases (NLCD).

Habitat loss and fragmentation are the greatest threats to the endangered Florida panther (Puma concolor coryi). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic (D ²) to develop a model based on broad-scale landscape characteristics associated with panther home ranges.

Recognized as one of the richest and most extensive savannas in the world, the Cerrado region, the second largest biome in South America, presents an intense and continuous human-induced land-cover change, which has already affected around 40% of its original area. In the pursuit of orientation and planning for current and long-term occupation, in this work we present plausible deforestation scenarios for the entire Cerrado biome, to 2050.

A framework is described that has been used to assess the effect of the European Commission's Agenda 2000 proposal on the Dumfries and Galloway region, Scotland. The model assesses the impact of agriculture on land-use patterns, the environment and socio-economics of the region. It incorporates a farm-type linear programming sub-model with environmental and socio-economic sub-models.

Accurate built-up information is imperative for loss estimation and disaster management after the occurrence of catastrophic events such as earthquake, tornado, tsunami and flood. These catastrophic events leave behind a trail of mass destruction with property and human losses amounting to millions. Once a natural disaster hits a region, built-up information is required within a short span of time for disaster management. Nowadays, earth observation satellite imagery serves as a promising source to extract the land use / land cover classes.

In this study, the impact of the rapid rate of urbanization over the Pearl River Delta (PRD) region of China since the 1980s on its seasonal climate is investigated using the Weather Research and Forecasting Model. Two land-cover data are employed to simulate the urbanization effects on the regional climate in both summer (June and August) and winter (December and February) for 26 years from 1984 to 2009. Spatial and temporal features of the urbanization effect on temperature and precipitation are found to be different between summer and winter.

In this article we investigate if qualitative soil fertility datasets derived during participatory processes can be combined with a corresponding land use change model (i) to improve the understanding of the social-ecological complexity of land use change and (ii) to allow testing of alternative scenarios even in data-poor environments. To test this hypothesis, a participatory assessment approach was combined with the spatially explicit, soil fertility driven FALLOW (Forest, Agroforest, Low-value Landscape Or Wasteland?) model.

Geographical information systems (GIS)-based approaches support the traditional empirical assessment and monitoring measures to indicate large-scale environmental alterations caused by global change. We examined the relationship between cover patterns of emergent aquatic plants derived from the CORINE land cover database, and environmental gradients (i.e. lake, climate and land cover and soil variables) at four different buffer scales (50m, 100m, 300m and 500m) in 408 boreal lakes in Finland.

The identification of land cover changes on a continental scale is a laborious and time-consuming process. A new methodology is proposed based exclusively on SPOT VGT data, illustrated for the African Continent using GLC2000 as reference to select 26 distinct land cover types (classes).