Mountain ecosystems are, however, fragile and particularly vulnerable to the adverse impacts of climate change, deforestation and forest degradation, land-use change, land degradation and natural disasters.

We assessed the extension of natural habitat conversion into croplands and grazing lands in subtropical NW Argentina and its impact on two key ecosystem functional attributes. We quantified changes in remotely sensed surrogates of aboveground net primary production (ANPP) and seasonality of carbon gains. Both functional attributes are associated with intermediate ecosystem services sensuFisher et al. (2009). Deforestation was estimated based on photointerpretation of Landsat imagery.

During the last decade, the use of the normalized difference vegetation index (NDVI) for drought monitoring applications has drawn many criticisms, mainly because a number of drivers such as land-cover/land-use change, pest infestation, and flooding may depress the NDVI, further causing false drought identification. In this study, the impacts of land-cover change on the NDVI-derived satellite drought indicator, the vegetation condition index (VCI), are presented.

Human‐induced land use and land cover (LUC) changes threaten the ecosystem services of the vulnerable tropical afro‐alpine vegetation. Several LUC change studies are available for the Ethiopian highlands, but relatively little is known about LUC change in the afro‐alpine zones. In this study, LUC changes between 1964 and 2012 were mapped for the afro‐alpine zone of Lib Amba Mountain, part of the Abune Yosef Mountains in North Ethiopia. Historical LUC was derived from georeferenced aerial photographs of 1964 and 1982, and the present LUC (2012) from Bing Map satellite imagery.

The Baekdudaegan Mountain Range is a backbone of the Korean Peninsula which has special spiritual and sentimental significance for Koreans and significant ecological value to diverse organisms. Despite the importance of this region, however, the natural environment of Baekdudaegan has been severely threatened by a variety of human activity and tremendous forest fires. To make management and restoration plans for the deforested areas, it is necessary to investigate quantitatively such natural and human-induced physical changes.

Since the 1950s, with national policy changes and socio-economic development, the habitat of the giant pandas has altered accordingly. This can also be inferred from the population changes of the giant pandas as reported in three national surveys. Thus, monitoring the changes in giant panda habitat and then taking appropriate action would be a valuable contribution to giant panda protection. In this paper, using existing habitats and potential habitats of the giant pandas as the study area, multitemporal remotely sensed data from the three national surveys are used as the data source.

A recent policy response to halting global forest deforestation and degradation, and any resulting greenhouse gas emissions is REDD+, which also includes the role of conservation, sustainable management of forests and enhancement of forest carbon stocks. Although still in its infancy, the success of REDD+ will depend significantly on whether it can be economically viable and if any resulting payments are sufficient to cover the opportunity cost plus any transaction cost.

The distributed hydrology soil vegetation model (DHSVM) is applied in the 107 km² Nam Mae Rim watershed (NMRW) in northern Thailand. Simulations using land cover scenarios for 1989 and 2002, extreme deforestation, and forest, each run with and without roads, show that roads have very small effects on the mean water fluxes, but significantly increase peak flows for all land cover scenarios. The magnitude of the road effect on peak flow depends on the land cover context in which the roads are placed.

Urban land-cover change threatens biodiversity and affects ecosystem productivity through loss of habitat, biomass, and carbon storage. However, despite projections that world urban populations will increase to nearly 5 billion by 2030, little is known about future locations, magnitudes, and rates of urban expansion. Here we develop spatially explicit probabilistic forecasts of global urban land-cover change and explore the direct impacts on biodiversity hotspots and tropical carbon biomass.

Industrial agricultural plantations are a rapidly increasing yet largely unmeasured source of tropical land cover change. Here, we evaluate impacts of oil palm plantation development on land cover, carbon flux, and agrarian community lands in West Kalimantan, Indonesian Borneo. With a spatially explicit land change/carbon bookkeeping model, parameterized using high-resolution satellite time series and informed by socioeconomic surveys, we assess previous and project future plantation expansion under five scenarios.