The main objective of the present work is to delineate the groundwater potential zones in Bilari watershed of district Shivpuri, Madhya Pradesh. Remote Sensing data and GIS were used to delineate the groundwater potential zones of the area. IRS-1D (LISS III) data have been utilized to extract information on various themes such as geomorphology, structure, drainage and land use/land cover. Available lithology and soil maps have also been used.

Countryside Survey is a unique large scale long-term monitoring programme investigating stock and change of habitats, landscape features, vegetation, soil and freshwaters of Great Britain. Repeat field surveys combine policy and scientific objectives to provide evidence on how multiple aspects of the environment are changing over time, a key goal of international science in the face of profound human impacts on ecosystems.

Global knowledge about the spatial distribution of species is orders of magnitude coarser in resolution than other geographically-structured environmental datasets such as topography or land cover. Yet such knowledge is crucial in deciphering ecological and evolutionary processes and in managing global change. In this review, we propose a conceptual and cyber-infrastructure framework for refining species distributional knowledge that is novel in its ability to mobilize and integrate diverse types of data such that their collective strengths overcome individual weaknesses.

Spatial indices measure the geometric arrangement of land use and land cover classes at various scales and are computationally adaptive with wavelet transform coefficients. Decision rules built on permutations of three spatial indices – energy, log energy and Shannon's diversity – are used to improve the accuracy of multi-resolution hierarchical wavelet-based classifications. Comparisons are made with classification results derived from other texture measures, as well as with classification results calculated from more conventional per-pixel techniques.

The ground reference data obtained to assess map accuracy can be simultaneously used to estimate area (extent). This dual-purpose use of ground reference data is examined for the special case of a two-class map of ‘change’ and ‘no change’. To assess the accuracy of a change map, stratified sampling is often implemented with a disproportionately larger sample size allocated to the map change stratum. But this allocation targeting user's accuracy of change is not necessarily effective for the competing objective of estimating the area of change.

Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m Normalized Difference Vegetation Index data and Landsat imagery to identify areas that changed from 2001 to 2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby waterbodies.

OTALEX II is the Territorial and Environmental Observatory of Alentejo (Portugal) and Extremadura (Spain), co-financed by POCTEP, developed with the cross-border collaboration of several Portuguese and Spanish bodies. It is composed of a Spatial Data Infrastructure (SDI) created in 2007, SDI-OTALEX (www.ideotalex.eu), which is an exchange platform for geographic information and Webmapping services among project partners.

Urban regions are important places of ecosystem service demands and, at the same time, are the primary source of global environmental impacts. Although there is broad agreement on the importance of incorporating the concept of ecosystem services into policy strategies and decision-making, the lack of a standardized approach to quantifying ecosystem services at the landscape scale has hindered progress in this direction. Moreover, tradeoffs between ecosystem services and the supply/demand ratio of ecosystem services in urban landscapes have rarely been investigated.

Monitoring land cover over large areas on a yearly basis is challenging. The spatial and temporal consistency of an object-based change detection algorithm was tested through a multi-year application on the forest of Borneo, using SPOT-VEGETATION time series from 2000 to 2008. Continuous change thresholds allowed the tuning of the algorithm according to specific requirements in terms of omission and commission errors.

Central Asia has experienced drastic socio-economic, geopolitical, and ecological transitions within the last few decades. The USSR collapse in 1991 has led to widespread changes in land cover and land use due to economic and political transformations within the region. Management practices during and after the Soviet era have intensified ecological problems and demands on resources.

BACKGROUND: The toxic effects of ultrafine particles (UFP) are a public health concern. However, epidemiological studies on the long term effects of UFP are limited due to lacking exposure models. Given the high spatial variation of UFP, the assignment of exposure levels in epidemiological studies requires a fine spatial scale. The aim of this study was to assess the performance of a short-term measurement protocol used at a large number of locations to derive a land use regression (LUR) model of the spatial variation of UFP in Girona, Spain.

Remote-sensing technology provides a powerful means for land use/land cover (LU/LC) monitoring at global and regional scales. However, it is more efficient and effective to combine remote-sensing measurements with a geographic information system (GIS) database and expert knowledge for change updating than to use remote-sensing technology alone. In this article, these different sources of information are integrated in the proposed framework, which is able to provide rapid updating of LU/LC information.