The Mississippi River Delta Plain has experienced substantial wetland loss from subsidence, erosion, and sea level rise, threatening coastal communities and the ecosystems that support them. The Atchafalaya River, the largest distributary of the Mississippi River, has one of the few prograding delta features along the ~200-km deltaic coastline. Understanding changes in the Atchafalaya River Delta complex (ARDC) development has critical implications for future prediction and management strategy for the Mississippi River Delta Plain.

Urbanization effects on ecosystem functions are both important and complex, characterized by scale multiplicity, spatial heterogeneity, and intensive human disturbances. Integrating the hierarchical structure of urban landscape pattern with ecosystem processes through simulation modeling can facilitate our understanding of human–environment interactions in urban environment.

The diurnal land surface temperature (LST) variation is a primary characteristic of the effects of urbanization. However, no study to date has focused on changes in diurnal LST variation in urban environments. This paper investigates the effects of urbanization on landscape pattern and diurnal LST variation of Taipei City, using MODIS thermal images and SPOT multispectral remote sensing images over the 1994–2010 period. Supervised land-cover classifications were conducted to investigate decadal land-cover changes within the study area.

The aim of our study was to explore the spectral properties of fire-scorched (burned) and non fire-scorched (vegetation) areas, as well as areas with different burn/vegetation ratios, using a multisource multiresolution satellite data set. A case study was undertaken following a very destructive wildfire that occurred in Parnitha, Greece, July 2007, for which we acquired satellite images from LANDSAT, ASTER, and IKONOS. Additionally, we created spatially degraded satellite data over a range of coarser resolutions using resampling techniques.

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete.

Knowing the influence of land use/land cover changes on the hydrological behavior of a subwatershed is essential to land use planning. The Alto Paraguaçu Watershed is a major producer of fruits and vegetables, and currently the largest producer of English potato in the north/northeast of Brazil. The water availability in the region can be considered the limiting factor to the expansion of agricultural frontiers.

Geographic information systems (GIS) allow researchers to make cost-effective, spatially explicit predictions of species' distributions across broad geographic areas. However, there has been little research on whether using fine-scale habitat data collected in the field could produce more robust models of species' distributions. Here we used radio-telemetry data collected on a declining species, the North American wood turtle (Glyptemys insculpta), to test whether fine-scale habitat variables were better predictors of occurrence than land-cover and topography variables measured in a GIS.

Forest fires in mountainous areas can cause severe deforestation which can potentially trigger secondary natural hazards like debris falls and avalanches. We documented an extreme case study for the range of possible post-fire land cover (LC) dynamics. We investigated a 15-ha, steep (10°–65°) burnt slope in Styria (Austria) at elevation of 760°-113 m, which burned in 1946 and has not fully recovered to date. Seven 8-class legend LC maps were produced (1954, 1966, 1973, 1982, 1998, 2004, 2009) and integrated in a vector-based GIS, mainly by on-screen interpretation of aerial photos.

Soil loss poses a significant threat to the long-term sustainability of hydrological systems, the environment, and agriculture. In this regard, efficient soil management relies on accurate quantification of soil loss. To this end, the Organization for Economic Cooperation and Development (OECD) standard of soil erosion, developed for agricultural areas, has been applied in many countries, including South Korea.

KEY MESSAGE : We compiled 2,458 biomass equations from 168 destructive sampling studies in Indonesia. Unpublished academic theses contributed the largest share of the biomass equations. The availability of the biomass equations was skewed to certain regions, forest types, and species. Further research is necessary to fill the data gaps in emission factors and to enhance the implementation of climate change mitigation projects and programs.

Land use is a dynamic phenomenon that changes with time and space due to anthropogenic pressure and development. Evaluating the existing land use and its periodic change is useful for urban planners, policy makers and natural resource managers. Land use and land cover changes in Mekelle City, Ethiopia (north east Africa) over a period of 25 years was studied using remotely sensed data. Multi temporal satellite data of Landsat was used to map and monitor urban land use changes occurred during two point of time of 1985 and 2010.

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates.