Earth observation based monitoring of change in vegetation phenology and productivity is an important and widely used approach to quantify degradation of ecosystems due to climatic or human influences. Most satellite based studies apply linear or polynomial regression methods for trend detections. In this paper it is argued that natural systems hardly react to human or natural influences in a linear or a polynomial manner. At shorter time-scales of few decades natural systems fluctuate to a certain extent in a non-systematic manner without necessarily changing equilibrium.

Most of the current global land cover datasets and global scale land-use models use a classification of land cover based on the dominant land cover type within a distinct region or pixel. Such a classification disregards the diversity and intensity of human influence on land systems. In this paper we propose a novel way of classification and modeling land-use using a classification based on land-use systems (LUSs) that represent specific combinations of human-environment interactions. A cluster analysis was used to identify and map these LUSs.

Numerical studies on impacts of landscape fragmentation due to land use and land cover change (LUCC) on precipitation fields over the Ji-Paraná basin in the Amazon region are carried out using atmospheric Eta model. Experiments consider historical data about LUCC over the basin from 1978 to 2000 and compare simulations under LUCC conditions with simulations under pristine conditions. In agreement with previous observational studies, model results do not show statistically significant impacts on precipitation in the region.

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.

In the anthropogenic fire-disturbed ecosystem of the San Francisco Valley in the Andes of southeastern Ecuador, dense stands of an aggressive invasive weed, the southern bracken fern (Pteridium arachnoideum and Pteridium caudatum), dominate the landscape. To secure sustainable land management in the region, a comprehensive understanding of bracken spatial-distribution patterns and life cycle dynamics is crucial.

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.

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.

There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI).

Among the main effects of human activities on the environment are land use and resulting land cover changes. Such changes impact the capacity of ecosystems to provide goods and services to the human society. This supply of multiple goods and services by nature should match the demands of the society, if self-sustaining human–environmental systems and a sustainable utilization of natural capital are to be achieved. To describe respective states and dynamics, appropriate indicators and data for their quantification, including quantitative and qualitative assessments, are needed.

There are widespread concerns about urban sprawl in China. In response, modeling and assessing urban expansion and subsequent land use and land cover (LULC) changes have become important approaches to support decisions about appropriate development and land resource use. Guangzhou, a major metropolitan city in South China, has experienced rapid urbanization and great economic growth in the past few decades. This study applied a series of Landsat images to assess the urban expansion and subsequent LULC changes over 35 years, from 1979 to 2013.

This study develops an approach to mapping indicators of the potential of ecosystems to supply ecosystem services, and the impact of changes in land cover and use upon them. The study focuses on the EU-25 plus Switzerland and Norway, and develops the methodology proposed by Kienast et al. (2009), which uses expert-and literature-driven modelling methods. The methods are explored in relation to mapping and assessing four of the ecosystem services: “Crop-based production”; “Wildlife products”; “Habitat diversity”; and “Recreation”.

Most impacts on providing ecosystem services (ESs) are related to land use changes that may cause ecosystem fragmentation and loss of ecosystem functions. Spatial planning, focusing on sustainable landscape development, should consider the local potential for providing ESs as well possible impacts due to land use changes. The results of a large number of recent studies on ES assessment are difficult to replicate and integrate into landscape planning or definition of land use policies.