Mangroves in Kenya provide a wide range of valuable services to coastal communities despite their relatively small total area. Studies at single sites show reductions in extent and quality caused by extraction for fuel wood and timber and clearance for alternative land use including saltpans, aquaculture, and tourism. Such studies suggest that Kenyan mangroves are likely to conform to the general global trend of declining area but there are no reliable recent estimates of either total mangrove extent or trends in coverage for the country.

As in many other developing countries, cities in Bangladesh have witnessed rapid urbanization, resulting in increasing amounts of land being taken over and therefore land cover changing at a faster rate. Until now, however, few efforts have been made to document the impact of land use and land cover changes on the climate, environment, and ecosystem of the country because of a lack of geospatial data and time-series information.

Green corridors are inevitable part of land cover and land use planning activities as they affect climate, hydrology and ecology of the urbanized regions. Detection and monitoring of green corridors and their relative functions are very important in terms of landscape management. They also carry information on changing speed from “green to grey” and fragmentation level of the urbanized regions. Analyzing the fragmentation level of the landscape formation reflects the management strategy and overall success of decision makers.

To conserve and manage wetland resources, it is important to inventory and monitor wetlands and their adjacent uplands. Satellite remote sensing has several advantages for monitoring wetland resources, especially for large geographic areas. This review summarizes the literature on satellite remote sensing of wetlands, including what classification techniques were most successful in identifying wetlands and separating them from other land cover types. All types of wetlands have been studied with satellite remote sensing.

We suggest a classificatory approach for land cover analysis that integrates fuzzy set theory with permutation techniques. It represents a non parametric alternative and/or a complement of traditional multivariate statistics when data are scarce, missing, burdened with high degree of uncertainty and originated from different sources and/or times. According to this approach, the Operational Geographic Units (OGUs) in which landscape is subdivided and sampled are classified with hierarchical clustering methods.

The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity.

Since China's economic reform in the late 1970s, Shanghai, the country's largest and most modern city, has experienced rapid expansion and urbanization. Here, we explore its land‐use and land‐cover changes, focusing on the impacts of the urbanization process on air and water quality, local climate, and biodiversity. Over the past 30 years, Shanghai's urban area and green land (eg urban parks, street trees, lawns) have increased dramatically, at the expense of cropland.

Widespread and increasing urbanization has resulted in the need to assess, monitor, and understand its effects on stream water quality. Identifying relations between stream ecological condition and urban intensity indicators such as impervious surface provides important, but insufficient information to effectively address planning and management needs in such areas.

Water resource conservation is of utmost importance, especially for agriculture in developing countries. Frequent occurrences of water shortage have driven more social efforts in researching on water resources spatial distribution, as the land cover changes recently have shown positive influences. For the purpose of efficient water resources management, hydrological processes under different types of land covers and soil textures are supposed to be accurately analyzed and evaluated.

The confusion matrix is the standard way for reporting the accuracy of land cover and other information classified from remote-sensing imagery. This letter describes a geographically weighted method for generating spatially distributed measures of accuracy (overall, user and producer accuracies) from a logistic geographically weighted regression. A kernel-based approach defines the data and weights that are used to calculate the accuracies at each location in the study area.

This paper provides a geographical assessment of potential bioenergy production in the European Union from residues of eight agricultural crops (wheat, barley, rye, oat, maize, rice, rapeseed and sunflower). The evaluation is geographically explicit at the scale of 1km² and is based on two main computational steps. In the first step the amount of crop residues resulting from statistical assessment based on the methodology developed by Scarlat et al.

This study investigated the landscape characteristics that influence C and N in unsaturated surface soils of riparian zones along 1st to 3rd order streams in the Atlantic Coastal Plain of the Delaware River Basin. Unsaturated surface soils (0–30cm) were sampled in forested and non-forested sites at 29 locations throughout S New Jersey and SE Pennsylvania. Overall, the soil %C and %N in forested and non-forested riparian sites studied in this investigation were comparable to similar riparian zone soils in eastern North America.