We explored the ecological effects of grassland restoration programs using satellite imagery and field plots sampling data and analyzing the patterns and mechanisms of land cover change and vegetation activities in arid and semiarid China during the period from 1982 to 2008. The grassland cover in the 1980s, 2000 and 2005 was compared before and after the restoration programs. The variability of net primary production (NPP) and rain use efficiency (RUE) were analyzed as indicators of vegetation productivity.

Heterogeneous land cover patterns contribute to unique ecological conditions in cities and little is known about the drivers of these patterns among cities. We studied tree cover patterns in relationship to urban morphology (for example, housing density, parcel size), socioeconomic factors (for example, education, income, lifestyle characteristics), and historical legacies in Baltimore, Maryland, and Raleigh, North Carolina.

Grasslands form the dominant land cover in the upper reaches of the Yellow River and provide a reliable indicator by being strongly correlated with regional terrestrial ecological status. Remote sensing can provide information useful for vegetation quality assessments, but no single sensor can meet the needs for the high temporal–spatial resolution required for such assessments on a watershed scale.

Spatial analysis of remotely-sensed land cover data in conjunction with species distribution atlases can reveal large-scale relationships between animal taxa and their habitats. We investigated the historical distribution patterns of three declining woodland birds, the Marsh Tit (Poecile palustris), Willow Tit (Poecile montana) and Lesser Spotted Woodpecker (Dendrocopos minor), in relation to a parsimonious landscape metric for describing habitat availability in Britain.

Monitoring land-cover changes on sites of conservation importance allows environmental problems to be detected, solutions to be developed and the effectiveness of actions to be assessed. However, the remoteness of many sites or a lack of resources means these data are frequently not available. Remote sensing may provide a solution, but large-scale mapping and change detection may not be appropriate, necessitating site-level assessments. These need to be easy to undertake, rapid and cheap.

Today, 27% of the known mammalian carnivore species are either extinct or threatened, undermining the health of many ecosystems, which provide resources and services that are crucial for human development. Carnivore research and management have been limited by the predominantly cryptic nature of carnivores, sometimes also by their large-scale habitat requirements and their remote distributions. As a consequence, many carnivore species currently remain under-studied.

Africa is home to some of the most vulnerable natural ecosystems and species on the planet. Around 7000 protected areas seek to safeguard the continent's rich biodiversity, but many of them face increasing management challenges. Human disturbances permeating into the parks directly and indirectly affect the ecological functioning and integrity of protected areas. With the envisaged expansion of the protected area network and further expected population and economic growth in the region, the competition between nature conservation and resources demands is likely to increase.

A comprehensive Landslide Susceptibility Zonation (LSZ) map is sought for adopting any landslide preventive and mitigation measures. In the present study, LSZ map of landslide prone Ganeshganga watershed (known for Patalganga Landslide) has been generated using a binary logistic regression (BLR) model.

This study compared concentrations and export of total phosphorus (TP; including dissolved and particulate forms) and nitrogen (N) between quickflow and delayed flow at two adjacent agricultural catchments (Jennings and McLarens Creeks), one of which is undergoing increased urbanization. Annual runoff, frequency of quickflow events in the growing season (GS), and chloride (Cl⁻) concentrations and export were greater at the more urbanized Jennings Creek.

A novel approach to study vegetation dynamics is introduced, using the Empirical Mode Decomposition (EMD) to analyze NDVI time series. The NDVI time series which is nonlinear and nonstationary can be decomposed by EMD into components called intrinsic mode functions (IMFs), based on inherent temporal scales. The highest frequency component which has been found to represent noise is subtracted from the original NDVI series; thus smoothing the noisy signal. The different key features describing vegetation phenology have been extracted by analyzing the noise free signal.

Arctic soils contain three times as much carbon (C) as all aboveground biomass distributed globally, much of which is stored in permafrost soils. Here, we (1) determine the predictability of estimating soil organic carbon (SOC) using different satellite data, classifications, and methods; (2) estimate the quantity and distribution of SOC for the top 10 cm for the Ambolikha River watershed (~121 km ²) in northeast Siberia, a sub-watershed of the Kolyma River; and (3) produce a hybrid SOC map through data fusion, combining the strengths of each data type.

Urbanization is increasingly becoming a widespread phenomenon at all scales of development around the globe. Be it developing or developed nations, all are witnessing urbanization at very high pace. In order to study its impacts, various methodologies and techniques are being implemented to measure growth of urban extents over spatial and temporal domains. But urbanization being a very dynamic phenomenon has been facing ambiguities regarding methods to study its dynamism. This paper aims at quantifying urban expansion in Delhi, the capital city of India.