This study is carried out to determine land use changes by Geographic Information Systems and Remote sensing methods in Yenimahalle district of Ankara province. Changes in land use were identified between 2000-2005 and 2000-2010. For the study Landsat-5 image of year 2000, Ikonos image of year 2005, and SPOT image of year 2010 were used. 1:25000 scale topo maps and soil maps, and CORINE land use data were also used. GPS data collected from field were used for ground truth studies.

China’s economy is growing explosively with double-digit rates of growth. However, behind the scenes of this economic miracle, a dark underbelly exists. The potential impact of the unsustainable use of land resources is increasing. Each parcel of land has a stationary geographic location, while its utilization is optional. The re-adjustment and optimization of land use patterns ought to be encouraged.

We measured bidirectional arthropod fluxes at 12 river reaches distributed across an urban‐rural gradient of riparian land use and land cover in the Scioto River system of Ohio (U.S.A.). For the terrestrial‐to‐aquatic arthropod flux (i.e. inputs of terrestrial arthropods to the river from the land), urban development was positively related to density of inputs but negatively related to biomass, partially explained by shifts in community composition and body size. Riparian grassland, typical of rural (i.e.

In order to investigate spatial and temporal characteristics of the purely grazing-based livestock husbandry system in southwestern Madagascar, individual animals from 12 cattle and 12 goat herds that were equally distributed across four villages were fitted with GPS tracking collars and their behaviour during pasturing was directly observed to identify seasonal variations in land use and movement patterns along the regional altitude and vegetation gradient.

Remote sensing is a useful technology for monitoring the spatial distribution and expansion of built-up and bare land areas. One effective approach, known as the normalized difference built-up index (NDBI), has been promoted for identifying built-up areas based on Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+) data.

Rapid land ownership changes in the Northern Forest of the eastern United States have spurred development as well as conservation. Local people have experienced differing degrees of participation in land use decisions. We examine two conservation projects from the Northern Forest state of Maine. This paper presents the policy processes from these projects and an assessment of their impact on conflict and support for the project. One project was a top-down approach, and the second was a grassroots, private effort by local citizens to conserve forestland.

Endocrine-disrupting contaminant (EDC) loads in rivers, and the associated risk to wildlife, may be linked to different anthropogenic stressors occupying river catchments. The aims of this study were to evaluate seasonal and spatial variation in steroid estrogen loads, and (anti)estrogenic and (anti)androgenic activity in a river catchment (upper Olifants River, South Africa), subject to a diversity of anthropogenic impacts. In addition, Mozambique tilapia, Oreochromis mossambicus, was applied as African-endemic sentinel and source of in vivo biomarkers.

The shortage of forest products and unsustainability of current land use practices experienced by many hillside farmers in the Caribbean is associated with increasing rates of conversion and degradation of remaining natural forests. This pressure could be alleviated by the establishment of trees in community/farm forests or more integrated agroforestry systems.

Bashagard district is one of the important malaria endemic areas in southern Iran. From this region a total of 16,199 indigenous cases have been reported in recent years. The aim of this study was to determine the situation of the disease and provide the risk map for the area. ArcGIS9.2 was used for mapping spatial distribution of malaria incidence. Hot spots were obtained using evidence-based weighting method for transmission risk.

Remote sensing images obtained by remote sensing are a key source of data for studying large-scale geographic areas. From 2013 onwards, a new generation of land remote sensing satellites from USA, China, Brazil, India and Europe will produce in 1year as much data as 5 years of the Landsat-7 satellite. Thus, the research community needs new ways to analyze large data sets of remote sensing imagery. To address this need, this paper describes a toolbox for combing land remote sensing image analysis with data mining techniques.