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.

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.

The mean shift (MS) algorithm is based on a statistical approach to the clustering problem. Specifically, the method is a variant of density estimation. We revisit in this article the MS paradigm and its use for clustering of remotely sensed images. Specifically, we investigate further the classification accuracy of remotely sensed images as a function of various MS parameters, such as the variant used, kernel type, dimensionality, kernel bandwidth, etc.

The Soil and Water Assessment Tool (SWAT) has been used for assessing the impact of land cover and land management changes on water resources for a wide range of scales and environmental conditions across the globe. However, originally designed for temperate regions, SWAT must be critically examined for its appropriate use in tropical watersheds. One major concern is the simulation of perennial tropical vegetation due to the absence of dormancy.

Most of China's 24–28 primate species are threatened with extinction. Habitat reduction and fragmentation are perhaps the greatest threats. We used published data from a conservation genetics study of 5 endangered primates in China (Rhinopithecus roxellana, R. bieti, R. brelichi, Trachypithecus francoisi, and T. leucocephalus); distribution data on these species; and the distribution, area, and location of protected areas to inform conservation strategies for these primates. All 5 species were separated into subpopulations with unique genetic components.

Deriving a priori gridded parameters is an important step in the development and deployment of an operational distributed hydrologic model. Accurate a priori parameters can reduce the manual calibration effort and/or speed up the automatic calibration process, reduce calibration uncertainty, and provide valuable information at ungauged locations. Underpinned by reasonable parameter data sets, distributed hydrologic modeling can help improve water resource and flood and flash flood forecasting capabilities.