This study detects patterns of land-use and land-cover changes in the last three decades (1972–2004) and analyses its causative factors in the Upper Dijo River catchment, Midwest escarpment of Ethiopian Rift Valley. Data captured through the synergy of an aerial photo, satellite image and ground-based socio-economic survey were analysed by GIS and SPSS. The results showed a decline in shrub-grassland and riverine trees at 21.5 and 16.3 ha per year, respectively, and increase in plantation trees, annual crops and bare/open grasslands at 2.8, 12.5 and 24.8 ha per year, respectively.

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data.

We exploited publicly available satellite- and aircraft-based imagery to estimate urban vegetation cover fraction and land use by class for a semiarid urban area that includes Phoenix, AZ, USA, using low-cost and technologically modest tools. This technique is also used to evaluate two satellite-derived tree cover datasets as well as to compare estimates from the present study with land cover data generated from another study performed using the same study domain.

Species distribution models are often used to study the biodiversity of ecosystems. The modelling process uses a number of parameters to predict others, such as the occurrence of determinate species, population size, habitat suitability or biodiversity. It is well known that the heterogeneity of landscapes can lead to changes in species’ abundance and biodiversity. However, landscape metrics depend on maps and spatial scales when it comes to undertaking a GIS analysis.

The structure and the spatio-temporal dynamics of the mixed beech–silver fir–Norway spruce old-growth forest of Biogradska Gora (Montenegro) have been analysed at different spatial scales: at the landscape scale, using a high-resolution SPOT5 satellite image and at the stand level with an intensive field survey. This remote-sensing approach has been used to obtain a land cover map in order to define the main vegetation types and to detect the large canopy gaps (>150 m ²).

Counter intuition, an analysis of tree‐line position across the Swiss Alps based on a geographical information system (GIS) with a spatial resolution of 100 m (2.5 million points) revealed no difference in climatic tree‐line altitude with slope exposure. Through step wise discrimination procedures our analysis accounts for anthropogenic tree‐line depression. Any land cover bias affects the frequency of GIS‐points corresponding to tree‐line forests rather than the mean elevation of such points, captured by our analysis.

Measurements of land-cover changes suggest that such shifts may alter atmospheric concentrations of greenhouse gases (GHGs). However, owing to the lack of large-scale GHG data, a quantitative description of the relationships between land-cover changes and GHG concentrations does not exist on a regional scale. The Greenhouse Gases Observing Satellite (GOSAT) launched by Japan on 23 January 2009 can be of use in investigating this issue.

Although spatial scale is important for understanding ecological processes and guiding conservation planning, studies combining a range of scales are rare. Habitat suitability modelling has been used traditionally to study broad-scale patterns of species distribution but can also be applied to address conservation needs at finer scales. We studied the ability of presence-only species distribution modelling to predict patterns of habitat selection at broad and fine spatial scales for one of the rarest mammals in the UK, the grey long-eared bat (Plecotus austriacus).

There is vigorous debate about the potential for reforestation to offset losses in biodiversity associated with tropical deforestation, but a scarcity of good data. We quantified developmental trajectories following active restoration (replanting) of deforested pasture land to tropical Australian rainforest, using 20 different bird community indicators within chronosequences of multiple sites. Bird species composition in restored sites (1–24years old) was intermediate between that of reference sites in pasture and primary rainforest.

Tropical coastal wetlands form complex and dynamic ecosystems based on a mixture of vegetation, soil, and water components. Optical remotely sensed data have often been used to characterize and monitor these ecosystems, which are among the environments most threatened by climate change and anthropogenic activity worldwide.

Increasing the accuracy of thematic maps produced through the process of image classification has been a hot topic in remote sensing. For this aim, various strategies, classifiers, improvements, and their combinations have been suggested in the literature. Ensembles that combine the prediction of individual classifiers with weights based on the estimated prediction accuracies are strategies aiming to improve the classifier performances.

We examined the impacts of the Satsunai River Dam on the hydrology and development of riparian vegetation along the upper and lower reaches of the Satsunai River downstream from the dam. We estimated frequency curves of the flood discharge during the pre-dam (1976-1996) and post-dam (1997-2006) periods and simulated the flood frequency at sampling points within sites under pre-dam, post-dam and dam-removal (using the pre-dam flood discharge and post-dam cross-sections) scenarios. Changes in channel morphology and land cover were investigated by analyzing aerial photographs.