The aim of this study was to determine the amplitude and the driving factors of the spatial variability in soil CO₂ efflux in a young European beech forest. Soil CO₂ efflux was measured in 2003 and 2004 in seven beech plots differing in terms of soil type and leaf area index. After eliminating temporal fluctuations due to soil temperature and soil water content, standardized soil CO₂ efflux varied significantly among plots over a large range given the homogeneity of the land cover type.

Changes in land use and climate are expected to alter the risk of malaria transmission in areas where rainfall limits vector abundance. We use a coupled hydrology–entomology model to investigate the effects of land use change on hydrological processes impacting mosquito abundance in a highland village of Ethiopia. Land use affects partitioning of rainfall into infiltration and runoff that reaches small-scale topographic depressions, which constitute the primary breeding habitat of Anopheles arabiensis mosquitoes.

Stonefly samples were collected from disturbed and undisturbed regions of two river basins, tributaries of the Upper Váh River basin (the West Carpathians). Water temperature, oxygen content, coarse benthic matter and some stonefly metrics (abundance, biomass, richness, index of diversity, % predators, % shredders, stonefly total score and stonefly average score) were all negatively influenced by the extent of urban and field land cover.

Recent European research projects have developed approaches that downscale land use related results of economic models. These results are primarily downscaled from the national or regional scale to a spatial resolution appropriate for environmental impact analysis. Different studies represent the interactions between the economic and geographic components of the land system in different ways. This paper explores how interactions between economic and geographic aspects of the land system can be strengthened in modelling studies.

This paper represents the first national effort of its kind to systematically investigate the impact of changes in climate and land use and land cover (LULC) on the carbon cycle with high-resolution dynamic LULC data at the decadal scale (1990s and 2000s).

Sustainable water resources management plans depend on reliable monitoring of land use –land cover (LULC) changes. The use of the remote sensing techniques in LULC changes detection brings consistency and reliability to the decision maker at regional scale. Three temporal data sets of images were used to obtain the land cover changes in this study: Landsat-5 Thematic Mapper (TM) acquired in 1984, and Landsat-7 enhanced Thematic Mapper acquired in 2000 and 2005 consequently. Each temporal data set consists of four Landsat scenes, which were mosaicked to cover the whole Nile Delta.

Net primary productivity (NPP) is an important component of the terrestrial carbon cycle. Accurately mapping the spatial-temporal variations of NPP in China is crucial for global carbon cycling study. In this study the process-based Boreal Ecosystem Productivity Simulator (BEPS) was employed to study the changes of NPP in China’s ecosystems for the period from 2000 to 2010. The BEPS model was first validated using gross primary productivity (GPP) measured at typical flux sites and forest NPP measured at different regions.

In Indonesia, vegetation fires occur every year in the dry season. To determine where and why fires occur, the natural and cultural landscape features that influence the location of fires were analysed. We investigated the probability of fire occurrence as a function of predisposing conditions and ignition sources, such as land use, land use zoning, accessibility or land cover, to understand the spatial determinants of fires. The study area is the entire province of Jambi, central Sumatra, Indonesia.

Most existing multi-temporal classification studies use spectral information alone and ignore the temporal correlation between two-date images. This article proposes a new method to characterize the local temporal correlation using multi-temporal texture measured with a geostatistical function called the pseudo cross variogram (PCV). The derived multi-temporal texture, as an additional band, was combined with the spectral information in multi-temporal classification.

The reference classifications that serve as the fundamental basis of accuracy assessment of land-cover maps are subject to uncertainty. A fuzzy interval approach is proposed in which linguistic-scale labels assigned to each land-cover class at each sample observation are converted to fuzzy intervals. These fuzzy intervals are then used to produce a fuzzy confusion matrix from which fuzzy thematic accuracy measures analogous to overall, user's, and producer's accuracy are produced.

This paper discusses a statistical and band transformation based approach to select bands for hyperspectral image analysis. Hyperspectral images contain large number of spectral bands with redundant information about the spectral classes in the image scene. It is necessary to reduce the high dimensionality of the data for the processing of hyperspectral data. We report a feature selection technique that removes correlated spectral bands using band decorrelation technique and obtains maximum variance image bands based on factor analysis.

The effects of land management and disturbance on ecosystem performance (i.e. biomass production) are often confounded by those of weather and site potential. The current study overcomes this issue by calculating the difference between actual and expected ecosystem performance (EEP) to generate ecosystem performance anomalies (EPA). This study aims to delineate and quantify average EPA from 2000–2009 within the Greater Platte and Upper Colorado River Basins, USA.