Global, long-term monitoring of changes in Earth's land surface requires quantitative comparisons of satellite images acquired under widely varying atmospheric conditions. Although physically based estimates of surface reflectance (SR) ultimately provide the most accurate representation of Earth's surface properties, there has never been a globally consistent SR dataset at the spatial resolution (b1 ha) or temporal extent (~40 years) of the Landsat mission.

Declining urban tree canopy cover in the United States underscores the importance of elucidating factors that influence the distribution of urban trees. This is particularly relevant as most urban trees are located on private property while their canopies maintain ecosystem services that constitute public goods. Thus, municipalities establish institutions in the form of canopy cover goals and various policies to incentivize private actions to meet those goals.

An illumination correction algorithm has been developed to improve the accuracy of forest change detection from Landsat-derived reflectance data. This algorithm is based on an empirical rotation model and was tested on Landsat image pairs over the Cherokee National Forest, Tennessee; Uinta–Wasatch–Cache National Forest, Utah; San Juan National Forest, Colorado; and Sinkyone Wilderness State Park, California. The illumination correction process successfully eliminated correlation between Landsat reflectance and illumination condition.

Aim We test the prediction that beta diversity (species turnover) and the decay of community similarity with distance depend on spatial resolution (grain). We also study whether patterns of beta diversity are related to variability in climate, land cover or geographic distance and how the independent effects of these variables depend on the spatial grain of the data. Location Europe, Great Britain, Finland and Catalonia. Methods We used data on European birds, plants, butterflies, amphibians and reptiles, and data on British plants, Catalonian birds and Finnish butterflies.

Boulengerula uluguruensis is a terrestrial caeciliid caecilian described from the Uluguru Mountains of Tanzania. We investigated the relative abundance of B. uluguruensis in agricultural and forested habitats at the beginning of the rainy season. This caecilian was found over a wide altitudinal range (450–1175 m a.s.l.), and in many land cover types (including natural forest, plantation forest and small scale agriculture), and different soil textures (including very compact soil). Based on quantitative and semi‐quantitative surveys, B.

Rapid development of shrimp farming may lead to unrecognized and undesirable changes of land cover/land use patterns in coastal areas. Of special concern is the loss of mangrove forest in coastal areas such as Quang Ninh, Vietnam, which is adjacent to the World Heritage-listed Ha Long Bay. Understanding the status and changes of land cover/land use for coastal shrimp farms and mangrove forests can support environmental protection and decision-making for sustainable development in coastal areas.

Soil erosion is one of the major threats to the conservation of soil and water resources in the Danjiangkou Reservoir region (DRR), China. In order to describe the areas with high soil erosion risk (SER) and to develop adequate erosion prevention measures, SER in the DRR was assessed by integrating the CORINE model with GIS and RS.

The Persian Long-tailed Desert Lizard, Mesalina watsonana , is one of the most common and most widely distributed lizards on the Iranian Plateau extending from Iran to Pakistan and Afghanistan. The species is frequently encountered in various types of habitats. We collected over 600 distributional records from available literature, museum collections, and our own field work and used bioclimatic and land cover characteristics to develop a model of potential distribution for M. watsonana . According to the model, the most important factors limiting the distribution of M.

The initial step in most object-based classification methodologies is the application of a segmentation algorithm to define objects. In the context of synthetic aperture radar (SAR) image analysis, the presence of speckle noise might hamper the segmentation quality. The aim of this study is to assess the segmentation performance of SAR images when no filter or different filters are applied before segmentation.

CONTEXT: The loss of landscape heterogeneity is causing declines of farmland biodiversity around the world. Traditional farmland regions are often highly heterogeneous and harbor high biodiversity, but are under threat of land cover homogenization due to changing agricultural practices. One species potentially affected by landscape homogenization is the Corncrake (Crex crex), which is threatened in Western Europe but remains widespread in the traditional farmland regions of Eastern Europe.

CONTEXT: Insect species of different trophic level will respond differently to landscape configuration. OBJECTIVE: In this context we explore the way landscape structure affects the distribution and abundance of the whitefly Siphoninus phillyreae and its predator Clitostethus arcuatus in olive orchards. METHODS: Adult individuals of these two species were collected using sticky traps placed in 12 olive host patches in Argentina. Host patches were detected and quantified using Landsat 5 TM images. Different landscape metrics were estimated for the study area land covers.

Land cover and land use changes in Kenya’s Rift Valley have altered the hydrologic response of the River Njoro watershed by changing the partitioning of excess rainfall into surface discharge and groundwater recharge. The watershed contributes a significant amount of water to Lake Nakuru National Park, an internationally recognized Ramsar site, as well as groundwater supplies for local communities and the city of Nakuru.