This paper explores the concept of homegardens and their potential functions as strategic elements in land-use planning, and adaptation and mitigation to climate change in Sri Lanka.

Unprecedented land use and land cover (LULC) changes in the Gilgel Tekeze catchment of the upper Nile River basin in Ethiopia may have far-reaching consequences for the long-term sustainability of the natural resources base. This study analyzed the dynamics and hydrologic effects of LULC changes between 1976 and 2003 as shown in satellite imagery. The effects of these LULC changes on the hydrologic response were investigated using the WetSpa model to estimate spatially distributed average annual evapotranspiration, surface runoff, and groundwater recharge.

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.

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).

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.

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.

Understanding soil processes is fundamental to the success of forest restoration programs. We compared different types of soils in Mediterranean mountain forests with respect to their edaphic environments and influence of vegetation cover and lithology. We then used this information to determine the suitability of current forest restoration programs in these ecosystems.

Land management in tropical woodlands is being used to sequester carbon (C), alleviate poverty and protect biodiversity, among other benefits. Our objective was to determine how slash-and-burn agriculture affected vegetation and soil C stocks and biodiversity on an area of miombo woodland in Mozambique, and how C stocks and biodiversity responded once agriculture was abandoned.

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 vicious poverty–environmental spiral commonly exists due to the interconnectedness of the socioeconomic aspects of farmers and land degradation. The socioeconomic situation of farmers affects their capabilities to implement environmentally viable soil and water conservation measures. These situations include farm practices and attitudes toward rational use of resources. An observational study was conducted to have an insight of the perception of farmers about the danger of gully erosion and their willingness to adopt new improved soil and water conservation measures.