Land-use and land-cover change profoundly affect human well-being and, therefore, have become a major topic for society. A thorough understanding of past and present processes transforming landscapes is essential for guiding future developments toward the sustained provision of the ecosystem services humans critically depend upon. Drawing on the driving forces and resilience frameworks, we identify possible variables and patterns of land change, connecting them to empirical findings in three case study areas in the Swabian Alb region, southwestern Germany.

A framework for preparation of an early warning system was developed for Maryland, using a GIS database and a collective overlay of maps that highlight highway slopes susceptible to soil slides or slope failures in advance through spatial and statistical analysis. Data for existing soil slope failures was collected from geotechnical reports and field visits. A total of 48 slope failures were recorded and analyzed. Six factors, including event precipitation, geological formation, land cover, slope history, slope angle, and elevation were considered to affect highway soil slope stability.

The paper provides a coherent pattern identification analysis of the impacts of coastal land use and land cover (LULC) on evapotranspiration (ET) under the impact of seawater intrusion. The study applied the Landsat satellite data to characterize the LULC at Laizhou Bay, Shandong Province, China. Then, the ET and heat fluxes were estimated using the surface energy balance algorithm for land model with two-time phase thermal infrared band images and regional surface parameters.

With the increasing availability of European and global forest maps, users are facing the difficult choice to select the most appropriate map for their purposes. Many of these maps are potential input datasets for forest-related applications for the European Union (EU), due to their spatial extent and harmonised approach at the European level. However, they possess different characteristics in terms of spatial detail or thematic accuracy. Little attention has been paid to the effect of these characteristics on simulation models and the resultant policy implications.

Over the past decades, the Gujarat state of India experienced intensive agricultural and industrial activities, fertilizer consumption and abstraction of groundwater, which in turn has degraded the ground water quality. Protection of aquifers from nitrate pollution is a matter of prime concern for the planners and decision-makers. The present study assessed the spatial and temporal variation of groundwater nitrate levels in areas with different land use/land cover activities for both pre- and post-monsoon period.

An improved Carnegie Ames Stanford Approach (CASA) model based on two kinds of remote sensing (RS) data, Landsat Enhanced Thematic Mapper Plus (ETM +) and Moderate Resolution Imaging Spectro-radiometer (MODIS), and climate variables were applied to estimate the Net Primary Productivity (NPP) of Xuzhou in June of each year from 2001 to 2010. The NPP of the study area decreased as the spatial scale increased. The average NPP of terrestrial vegetation in Xuzhou showed a decreasing trend in recent years, likely due to changes in climate and environment.

The confusion matrix is the standard way for reporting the accuracy of land cover and other information classified from remote-sensing imagery. This letter describes a geographically weighted method for generating spatially distributed measures of accuracy (overall, user and producer accuracies) from a logistic geographically weighted regression. A kernel-based approach defines the data and weights that are used to calculate the accuracies at each location in the study area.

In this study, a terrain classification algorithm is presented that was derived from various properties of the returned full waveform signals collected from the Ice, Cloud and land elevation Satellite (ICESat) mission. Such an algorithm would be beneficial for current and future studies of the cryosphere, particularly Greenland and Antarctica, by helping to identify changes in the large scale surface properties over time. The algorithm developed was validated over a test region in the Dry Valleys of Antarctica, where the terrain is well known and regularly monitored.

Lidar and orthophotograph-derived land cover are combined with in situ vegetation measurements to assess habitat characteristics typifying four species of butterflies with differing habitat preferences across a large spatial extent (∼30,000 ha) in northern Idaho, USA. Lidar data are employed to characterize both vegetation structure and topography, whereas digital orthophotographs and in situ vegetation measurements are employed to quantify surrounding land use and larval host plant cover, respectively.

Mangroves in Kenya provide a wide range of valuable services to coastal communities despite their relatively small total area. Studies at single sites show reductions in extent and quality caused by extraction for fuel wood and timber and clearance for alternative land use including saltpans, aquaculture, and tourism. Such studies suggest that Kenyan mangroves are likely to conform to the general global trend of declining area but there are no reliable recent estimates of either total mangrove extent or trends in coverage for the country.

As in many other developing countries, cities in Bangladesh have witnessed rapid urbanization, resulting in increasing amounts of land being taken over and therefore land cover changing at a faster rate. Until now, however, few efforts have been made to document the impact of land use and land cover changes on the climate, environment, and ecosystem of the country because of a lack of geospatial data and time-series information.

Green corridors are inevitable part of land cover and land use planning activities as they affect climate, hydrology and ecology of the urbanized regions. Detection and monitoring of green corridors and their relative functions are very important in terms of landscape management. They also carry information on changing speed from “green to grey” and fragmentation level of the urbanized regions. Analyzing the fragmentation level of the landscape formation reflects the management strategy and overall success of decision makers.