Elephant-induced thicket degradation in the Addo Elephant National Park (AENP), Eastern Cape, South Africa, was assessed during 1973 and 2010 using multitemporal satellite imagery. Changes in the thicket condition, in relation to the AENP expansion, were analyzed using the Normalized Difference Vegetation Index, postclassification, and landscape metrics. The change detection of land-cover classes was analyzed by postclassification. Landscape-spatial metrics were used in order to gain an understanding of vegetation-fragmentation trends.

On the basis of interactions between landscape characteristics and precipitation inputs, watersheds respond differently to different climatic inputs. The objective of this study was to quantitatively characterize controls on runoff generation from two first order micro‐catchments in the Amazonia region. The study investigated the variation of hydrological signatures at micro‐catchment scale and related these to landscape and land cover differences and weather descriptors that control the observed responses.

Regional climate is influenced by land surface processes through energy exchange between land and atmosphere at various scales. The performance of climate model simulation is largely influenced by land cover parameterization, especially over areas that experience rapid change of land surface characterization. Accurate land cover datasets suited for climate modeling are urgently needed to improve model parameterization for better simulation.

Climate change is causing range shifts in many species, and impacts are predicted to be highest in mountain regions. The effectiveness of protected areas in preserving suitable habitats for target species in the face of climate change is particularly concerning, as many protected sites may lose suitable conditions for those species. We investigate the potential effect of temperature increase on the regional distribution of pygmy and boreal owl, mountain forest specialists in the Italian Alps, and the relative effectiveness of the Natura 2000 network at the regional level.

We measured bidirectional arthropod fluxes at 12 river reaches distributed across an urban‐rural gradient of riparian land use and land cover in the Scioto River system of Ohio (U.S.A.). For the terrestrial‐to‐aquatic arthropod flux (i.e. inputs of terrestrial arthropods to the river from the land), urban development was positively related to density of inputs but negatively related to biomass, partially explained by shifts in community composition and body size. Riparian grassland, typical of rural (i.e.

Increasing land utilization through diverse forms of human activities, such as agriculture, forestry, urban growth, and industrial development, has led to negative impacts on the water quality of rivers. To find out how catchment attributes, such as land use, hydrologic soil groups, and lithology, can affect water quality variables (Ca²⁺, Mg²⁺, Na⁺, Cl⁻, HCO₃⁻, pH, TDS, EC, SAR), a spatio-statistical approach was applied to 23 catchments in southern basins of the Caspian Sea.

Context Coyotes (Canis latrans) have adapted successfully to human landscape alteration in the past 150 years and in recent decades have successfully moved into urban areas. While this causes concern about human–wildlife conflicts, research also suggests that coyotes tend to avoid humans and human activity in urban areas. For improving management, a better understanding of space use by coyotes is needed. Aims To study how coyote social behaviour influences fine-scale space use in urban areas we present results from an extensive, multi-year GPS telemetry study (2005–13).

Super resolution mapping is a continuously growing area of remote sensing. Satellite images coupled with a very high spectral resolution, and are suitable for detection and classification of surfaces and different elements in the observed image. The main problem with high resolution data for these applications is the (relatively) low spatial resolution, which can vary from a few to tens of meters.

Irregular shape of terrain causes variable illumination angles and diverse reflectance values within same land cover type in optical remote sensing image. It causes problems in image segmentation and misclassification (snow with other land cover). This perception leads to develop an empirical-statistical based topographic correction (ESbTC) algorithm for reflectance modeling after compared with existed topographic correction methods like Cosine correction, C-correction, Minnaert correction, sun–canopy–senor with c-correction (SCS + C) and slope matching, in the context of snow reflectance.

While it is clear that many migratory behaviors are shared across taxa, generalizable models that predict the distribution and abundance of migrating taxa at the landscape scale are rare. In migratory landbirds, ephemeral concentrations of refueling birds indicate that individual behaviors sometimes produce large epiphenomena in particular geographic locations. Identifying landscape factors that predict the distribution and abundance of birds during migratory stopover will both improve our understanding of the migratory process and assist in broad, regionally relevant conservation.

Quantification of landscape pattern is of primary interest in landscape ecological studies. For quantification purposes, a large number of landscape metrics have been developed, with definitions based on measurable patch attributes. Calculation of these metrics is commonly conducted on wall-to-wall maps, whereas a new interest is to use sample data. It is argued that a sample survey takes less time and results are more reliable. The overall objective in this paper was to present the potential of the line interest sampling method for estimating a special contagion metric.

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture.