This study examined analyst variation associated with land cover (LC) image classification using 30 × 30 m Landsat ETM+ data for the assessment of coarse spatial resolution regional/global LC products. The study was designed to test the effect of varying training site selections (location and number) among six analysts performing a supervised classification on a Landsat ETM + image. Design constraints maintained other aspects of the classification process constant (i.e., type of classifier, choice of band combinations, etc.).

Remote sensing is considered the most effective tool for estimating evapotranspiration (ET) over large spatial scales. Global terrestrial ET estimates over vegetated land surfaces are now operationally produced at 1-km spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the MOD16 algorithm. To evaluate the accuracy of this product, ground-based measurements of energy fluxes obtained from eddy covariance sites installed in tropical biomes and from a hydrological model (MGB-IPH) were used to validate MOD16 products at local and regional scales.

Background: It is essential that systems for measuring changes in carbon stocks for Reducing Emissions from Deforestation and Forest Degradation (REDD) projects are accurate, reliable and low cost.

Habitat models constitute useful instruments for understanding species-habitat interactions and can constitute helpful conservation tools. The Upper Paraná Atlantic Forest (UPAF) of South America still holds the world’s southernmost jaguar (Panthera onca) population.

With limited resources for habitat conservation, the accurate identification of high-value avian habitat is crucial. Habitat structure affects avian biodiversity but is difficult to quantify over broad extents. Our goal was to identify which measures of vertical and horizontal habitat structure are most strongly related to patterns of avian biodiversity across the conterminous United States and to determine whether new measures of vertical structure are complementary to existing, primarily horizontal, measures.

Feature extraction is highly important for classification of remote-sensing (RS) images. However, extraction of comprehensive spatial features from high-resolution imagery is still challenging, leading to many misclassifications in various applications. To address the problem, a shape-adaptive neighbourhood (SAN) technique is presented based on human visual perception. The SAN technique is an adaptive feature-extraction method that not only considers spectral feature information but also the spatial neighbourhood as well as the shape of features.

Time series of vegetation index (VI) information derived from remote sensing is important for land-cover change detection. Although traditional change vector analysis (TCVA) is an effective method for extracting land-cover change information from a time series of VI data, it has the disadvantage of being too sensitive to temporal fluctuations in VI values. The method tends to overestimate the changes and confuse the actual land-cover conversion with the land covers that have not been converted but experience significant VI changes.

The urban heat island (UHI) effect is the phenomenon of increased surface temperatures in urban environments compared to their surroundings. It is linked to decreased vegetation cover, high proportions of artificial impervious surfaces, and high proportions of anthropogenic heat discharge. We evaluated the surface heat balance to clarify the contribution of anthropogenic heat discharges into the urban thermal environment.

Recent studies using low-resolution satellite time series show that the Sahelian belt of West Africa is witnessing an increase in vegetation cover/biomass, called re-greening. However, detailed information on local processing and changes is rare or lacking. A multi-temporal set of Landsat images was used to produce land-cover maps for the years 2000 and 2007 in a semi-arid region of Niger, where an anomalous vegetation trend was previously detected.

Substitution of the Intergovernmental Panel on Climate Change (IPCC) default methodology by country-specific activity data is recommended for improved estimation of baseline soil organic carbon (SOC) stocks and their changes. In the Republic of Ireland (ROI), previous studies focused either predominantly on grassland or on all land cover types but were depth-limited. To improve the accuracy, Tier 2 approaches are proposed by the IPCC.

Landscape structure not only reflects the natural settings of the landscape but also its history and the impact of human activity. Information about the characteristics of the landscape elements in terms of their structural functionality plays a central role in assessing their ecological quality. Statutory designation of sites plays a key role in conserving and maintaining valuable parts of the landscape. In this study, we investigated whether protection status influences functionality in case studies from the Czech Republic, representing three different landscape types.

The paper deals with the application of Remote Sensing and Geographical Information System (GIS) technique for a watershed development program. For this study, the WRJ-2 watershed falling under Narkhed and Katol Tahsils of Nagpur district, Maharashtra, India is investigated. Various thematic maps (i.e. drainage, geology, soil, geomorphology and land use/ land cover) have been prepared using the remote sensing and GIS techniques. Initially, differential weightage values are assigned to all the thematic maps as per their runoff characteristics.