Ecosystem services, i.e., services provided to humans from ecological systems have become a key issue of this century in resource management, conservation planning, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national interests for integrating ecology with economics to help understand the effects of human policies and actions and their subsequent impacts on both ecosystem function and human well-being.

China’s economic development over the past three decades has been remarkable due to the establishment of the “Reform and Opening-up” program. Meanwhile, urbanization, one of the most intensive human activities, has significantly changed the land cover across China. Here we used remote sensing data and landscape metrics to explore the spatiotemporal patterns of urbanization in two large Chinese cities, Chengdu (1978–2010) and Chongqing (1976–2010).

Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past.

Species distribution modelling (SDM) can help conservation by providing information on the ecological requirements of species at risk. We developed habitat suitability models at multiple spatial scales for a threatened freshwater turtle, Emydoidea blandingii, in Ontario as a case study. We also explored the effect of background data selection and modelling algorithm selection on habitat suitability predictions. We used sighting records, high-resolution land cover data (25m), and two SDM techniques: boosted regression trees; and maximum entropy modelling.

The composition and configuration of landscape elements as well as their size and shape co-determine the character of the flows and processes in the landscape. Using remote sensing data and landscape metrics, this article sets out to analyse changes in the landscape structure at two different spatial scales, focusing on two study areas in the Czech Republic in the latter half of the twentieth century.

Improving the understanding of land use and land cover is a major research challenge for the human-environmental sciences and is essential for many aspects of global environmental research. Considering seasonal vegetation dynamics or phenological dynamics in multi-year series leads to a broader view of land use and land cover. This study is based on the hypothesis that a pixel representing a complex but consistent land use has a typical, distinct and repeated temporal pattern of vegetation index inter-annually, which can be used as characteristic signatures for land use classification.

A dam's construction always imposes some risks to the environment. In this article, the environmental risks of the Polrood dam, located in a northern province of Iran, during its construction phase, were identified, ranked, and evaluated. The risk factors were initially identified by Delphi questionnaire and then rated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Subsequently, the Analytical Hierarchy Process (AHP) was applied to classify the risk factors into four major categories, and Expert Choice software was used to weight them.

Mount Kilimanjaro is considered the highest free-standing mountain in the world and a symbol of the African continent. Steep slopes and high altitudes are on the backdrop of unique biophysical characteristics, in which changes between savannas, tropical cloud forests, and subalpine vegetation can be observed in relatively small distances. In the context of this complex and heterogeneous landscape, describing the interactions between climatic variables and ecosystem functions is crucial for understanding the drivers of biodiversity.

Human activities in many parts of the world have greatly changed the natural land cover. This study has been conducted on Pichavaram forest, south east coast of India, famous for its unique mangrove bio-diversity. The main objectives of this study were focused on monitoring land cover changes particularly for the mangrove forest in the Pichavaram area using multi-temporal Landsat images captured in the 1991, 2000, and 2009.

The wintering Great Grey Shrike Lanius excubitor was censused in Poland more than two decades ago (during the winters of 1988/89 and 1989/90). Single censuses were made during each winter on sample plots varying from 4.1 to 35.1 km² (mean: 16.4 km²). Altogether, data from 404 plots, covering in total more than 6.6 thousands km² were used for the analysis. Based on this data and environmental information gathered in GIS databases (Corine land cover ““CLC1990”” database, digital elevation model ““GTOPO30”” dataset) we modelled habitat- and spatial-related variation in shrike distribution.

The land surface models used in numerical weather forecasts and hydrological applications rely on the accuracy of land cover maps available from satellite remote sensing to simulate the energy and water balance at the surface of the Earth. While the impact of classification accuracy on land surface simulations has already been reported, little attention has been paid on the consequences of land cover map uncertainty driven by geolocation accuracy.

Freshwater lakes are known to release carbon dioxide (CO₂) and methane (CH₄) to the atmosphere; however, the importance of lakes in global nitrous oxide (N₂O) budgets is not yet known. Further, despite the abundance of small lakes on the landscape, neither emissions of these gases nor their drivers are well described.