This study established the possibility of rapid evaluation of land cover structure and situation using as an example the Temelin Nuclear Power Plant (Czech Republic) emergency zone. The composition, surface representation and spatial distribution of crop species in the area of interest were assessed on the basis of satellite data analysis (Landsat 5 TM). The supervised classification method of Landsat data yielded 92% accuracy of classification into the land cover classes.

This paper addresses two important issues for large Mediterranean city regions: the differential impact of compact urban ‘growth’ and low-density ‘sprawl’ on land cover changes (LCCs), and their final effect on changing land cover relationships (LCRs). The urban expansion of Rome (Italy) during the last 50 years and the related LCCs were investigated as a paradigmatic example of compact versus dispersed urban development.

Urban and community forests play an important role in the overall carbon budget of the USA. Accurately quantifying carbon sequestration by these forests can provide insight for strategic planning to mitigate greenhouse gas effects on climate change. This study provides a new methodology to estimate net forest carbon sequestration (FCS) in urban and community lands of northern New England using ground based forest growth rates, housing density data, satellite derived land cover and tree canopy cover maps at the county level.

In pace with rapid urbanization, urban areas in many countries are undergoing huge changes. The large spectral variance and spatial heterogeneity within the ‘buildings’ land cover class, as well as the similar spectral properties between buildings and other urban structures, make building change detection a challenging problem. In this work, we propose a set of novel building change indices (BCIs) by combining morphological building index (MBI) and slow feature analysis (SFA) for building change detection from high-resolution imagery.

A Boosted Genetic Fuzzy Classifier (BGFC) is proposed in this paper, for land cover classification from multispectral images. The model comprises a set of fuzzy classification rules, which resemble the reasoning employed by humans. Fuzzy rules are generated in an iterative fashion, incrementally covering subspaces of the feature space, as directed by a boosting algorithm. Each rule is able to select the required features, further improving the interpretability of the obtained model.

In this article, a new index, the visible and shortwave infrared drought index (VSDI), is proposed for monitoring both soil and vegetation moisture using optical spectral bands. VSDI is defined as , where ρ represents the reflectance of shortwave infrared (SWIR) red and blue channels, respectively. VSDI is theoretically based on the difference between moisture-sensitive bands (SWIR and red) and moisture reference band (blue), and is expected to be efficient for agricultural drought monitoring over different land-cover types during the plant-growing season.

The impact on temperature of the urban growth in central Mexico from 1993 to 2009 and the sensitivity of forecast to change in land cover are studied using high resolution numerical simulations. The mesoscale atmospheric Weather Research and Forecasting model (WRF) uses Global Land Cover Characteristics (GLCC) data created from NOAA-AVHRR satellite images from 1992 and 1993.

Anthropogenic changes in land use and cover (LULC) in stream catchments can alter the composition of riparian plant communities, which can affect ecosystem functions of riparian areas and streams from local to landscape scales. We conducted a study to determine if woody plant species composition and abundance along headwater streams were correlated with categorical and continuous LULC and environmental variables along an urban-to-rural gradient.

During the last few decades, land use changes have largely affected the global warming process through emissions of CO₂. However, C sequestration in terrestrial ecosystems could contribute to the decrease of atmospheric CO₂rates. Although Mediterranean areas show a high potential for C sequestration, only a few studies have been carried out in these systems. In this study, we propose a methodology to assess the impact of land use and land cover change dynamics on soil organic C stocks at different depths.

Paired watersheds are used to develop a deciduous nutrient uptake stoichiometry. The watersheds are those of the House Rock Run and the Brubaker Run located in the Pennsylvania Appalachian Piedmont, USA. These two watersheds are nearly identical with respect to bedrock, regolith, climate, geomorphology, morphometry, baseflow hydrology, and type and successional stage of forest vegetation. They only differ by the percentage of deciduous forest cover, with House Rock Run having 59% and Brubaker Run having 76%.

We tested the possibility of using digital, color aerial ortho-photographs and monoscopic, panchromatic satellite images of comparable spatial and radiometric resolution, to map recent landslides in Italy and to update existing measures of landslide mobilization. In a 90-km² area in Umbria, central Apennines, rainfall resulted in abundant landslides in the period from September 2004 to June 2005. Analysis of the rainfall record determined the approximate dates of landslide occurrence and revealed that the slope failures occurred in response to moderately wet rainfall periods.

Satellite remote sensing has become a popular tool to analyze agricultural drought through terrestrial vegetation health conditions using the normalized difference vegetation index (NDVI). Drought monitoring techniques using remote sensing-based drought indices assume that vegetation conditions vary year-to-year due to prevailing weather conditions (e.g., precipitation and temperature), and current conditions are evaluated based on the deviation from the long-term statistics such as mean, minimum, or maximum.