Urban sprawl along the Mediterranean coast is characterized by single-family houses and domestic gardens. Many new residences are secondary homes for socio-demographically diverse tourists. We explore the differences between the residence types in terms of their garden structures and plant compositions using socioeconomic and legacy attributes. Outdoor areas of 245 primary and secondary homes were investigated to determine plant compositions, land cover and household characteristics. Then, the outdoor land cover was compared between the two residence types.

Animal dispersal is highly non‐random and has important implications for the dynamics of populations in fragmented habitat. We identified interpatch dispersal events from genetic tagging, parentage analyses and assignment tests and modelled the factors associated with apparent emigration and post‐dispersal settlement choices by individual male agile antechinus (Antechinus agilis, a marsupial carnivore of south‐east Australian forests). Emigration decisions were best modelled with on data patch isolation and inbreeding risk.

Spatially organized distribution patterns of species and communities are shaped by both autogenic processes (neutral mechanism theory) and exogenous processes (niche theory). In the latter, environmental variables that are themselves spatially organized induce spatial structure in the response variables. The relative importance of these processes has not yet been investigated in urban habitats.

Stopover use by migrating shorebirds is affected by patch-level characteristics of habitat, but the relative influence of broad-scale factors is poorly understood. We conducted surveys of ten 10-km-radius landscapes in north-central Oklahoma from 2007 through 2009 to examine the influence of the amount and composition of wetland habitats and surrounding land cover on shorebird use during migration.

In this study, an investigation was performed of the spatial relationships between the occurrences of four types of landslides (slides, flows, falls and creeps) and three categories of land cover (agricultural areas, artificial surfaces and forested and semi-natural areas) that are found in the Arno river basin of central Italy. The main purpose of the study was to test whether the landslides that are mapped within the basin are spatially clustered (i.e., have a spatial attraction) or randomly spatially distributed (i.e., spatially independent) on different types of land cover.

Spatial regression, incorporating spatial error or lag dependency, was performed to interpret determinants of hazardous chemicals at full sub-basin scale and at 500m riparian buffer scale in Qiantang River, eastern coastal China. Monitoring data from 41 monitoring stations were collected between 1996 and 2003 and pretreated for 7 variables—petroleum, hexavalent chromium, total cadmium, total lead, total mercury, total cyanide, and volatile phenol. Results showed that primary predictors and the predictive ability of spatial regression differed with variables and scales.

Improved change vector analysis (ICVA) has recently been promoted as an effective algorithm for multi-class change detection. Unlike the conventional change vector analysis (CVA) that works on two-dimensional data, the ICVA works on multidimensional data. However, ICVA has limitations when the change vector is fraught with similar direction cosine values. In this article, a new algorithm, named median change vector analysis (MCVA) has been proposed for multi-class change detection.

The recent discussion about the relationships between biodiversity and ecosystem services also raises the question as to whether the argumentative basis for nature conservation can be strengthened by emphasizing the role of species and habitats in supporting ecosystem services. A literature survey shows that mainly socio-cultural and some regulating services are dependent on particular species, groups of species, or habitat types, while many other services, especially those related to provisioning, rely more heavily on vegetation structures and land cover.

This article introduces an innovative approach using marker-controlled watershed segmentation (WS) in the Vegetation–Impervious Surface–Soil (V–I–S) feature space for urban land-use and land-cover (LULC) classification. The complement (e.g., the inverse) of the V–I–S feature space image shows depressions, which can be treated as topographic watersheds and they correspond to LULC classes. WS partitions the complement of V–I–S feature space image into LULC regions based on user-specified initial markers.

The RUSLE-3D (Revised Universal Soil Loss Equation-3D) model was implemented in geographic information system (GIS) for predicting the soil loss and the spatial patterns of soil erosion risk required for soil conservation planning. High resolution remote sensing data (IKONOS and IRS LISS-IV) were used to prepare land use/land cover and soil maps to derive the vegetation cover and the soil erodibility factor whereas Digital Elevation Model (DEM) was used to generate spatial topographic factor. Soil erodibility (K) factor in the sub-watershed ranged from 0.30 to 0.48.

To evolve a proper management scenario for groundwater utilization, identification of groundwater potential zones is an important step. In the present study, an attempt has been made to identify possible groundwater potential zones both in terms of quantity and quality. A methodology is proposed for identification of groundwater potential index (GWPI) and a new water quality index (WQI) based on analytic hierarchy process. The proposed methodology has been applied to the shallow alluvial aquifer of central Ganga basin, Kanpur (India).

Land cover identification and monitoring agricultural resources using remote sensing imagery are of great significance for agricultural management and subsidies. Particularly, permanent crops are important in terms of economy (mainly rural development) and environmental protection.