The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud and land Elevation Satellite (ICESat) provides elevation data with very high accuracy which can be used as ground data to evaluate the vertical accuracy of an existing Digital Elevation Model (DEM). In this article, we examine the differences between ICESat elevation data (from the 1064 nm channel) and Shuttle Radar Topography Mission (SRTM) DEM of 3 arcsec resolution (90 m) and map-based DEMs in the Qinghai-Tibet (or Tibetan) Plateau, China.

Land use change is one of the main stress factors on ecosystems near urban areas. We analysed land use dynamics within Xochimilco, a World Heritage Site area in Mexico City. We used satellite images and GIS to quantify changes in land use/land cover (LULC) from 1989 to 2006 in this area, and a Markov projection model to simulate the impact of different management scenarios through to 2057. The results show an alarming rate of urbanisation in 17 years. LULC change runs in one direction from all other land use categories towards urban land use.

Notions of land cover relating to physical landscape characters are readily captured by satellite imagery. Land use on the other hand relates more to the societal aspects of a landscape. We argue that much of the spatial configuration of landscape characters is related to land use and that satellite data can be used to represent and investigate interpretations of land use. We propose and demonstrate the joint use of a novel SRPC procedure for satellite imagery together with an explicit representation of category semantics.

In Burkina Faso, livestock sedentarization programmes are still at the top of policy makers’ agendas and at the heart of their discourse, despite huge changes in land cover, land use and territorialities in rural areas. This paper contributes to the literature on the impact of livestock policies targeting the sedentarization of pastoralism in sub-Saharan Africa by specifically highlighting the territorial consequences of such policies.

A disaggregated approach to land cover survey is developed utilising data primitives. A field methodology is developed to characterise five attributes: species composition, cover, height, structure and density. The utility of these data primitives, as land cover ‘building blocks’ is demonstrated via classification of the field data to multiple land cover schema. Per-pixel classification algorithms, trained on the basis of the classified field data, are utilised to classify a SPOT 5 satellite image. The resultant land cover maps have overall accuracies approaching 80%.

Carbon-based forest conservation requires the establishment of ‘reference emission levels’ against which to measure a country or region's progress in reducing their carbon emissions. In East Africa, landscape-scale estimates of carbon fluxes are uncertain and factors such as deforestation poorly resolved due to a lack of data. In this study, trends in vegetation cover and carbon for East Africa were quantified using moderate-resolution imaging spectroradiometer (MODIS) land cover grids from 2002 to 2008 (500-m spatial resolution), in combination with a regional carbon look-up table.

This study presents spatial and temporal changes of carbon storages of forest timber biomass in a typical forest management unit of the northeastern part of Turkey. The effects of land-use and land-cover changes on the amount of carbon storage are analyzed. Temporal changes of carbon storage of the area were estimated using forest inventory data. The spatial distribution of carbon densities was mapped using Geographic Information Systems (GISs). As an overall change between 1984 and 2005, there was a net increase of 12,379 ha in forested areas.

In the Mexican coasts, as in many tropical and subtropical coastal areas, shrimp culture grew exponentially over the last three decades. This process has produced an intense debate on the economic benefits but also about the extent and intensity of the impact of this activity on the coastal ecosystems, particularly the effects of pond construction on mangrove areas and other coastal wetlands.

The SWAT model (Soil and Water Assessment Tool) was applied for simulating the hydrologic pattern of Paraopeba river basin, in Minas Gerais state, under different land use and occupation scenarios, looking to support basin management actions. The model parameters were calibrated and validated, with respect to the data observed from 1983 to 2005. The basin was assessed at the ‘Porto do Mesquita’ gauging station and change in land use and occupation was based on the annual growth scenarios proposed in the partial report of Paraopeba basin’s master plan.

In the past few decades there has been an increasing pressure of population all over the world, especially in India, resulting in the utilization of every available patch of available land from woodlands to badlands. The study area represents a basin which is economically growing fast by converting the fallow lands, badlands and woodlands to agricultural land for the past few decades.

Hydrological classification systems seek to provide information about the dominant processes in the catchment to enable information to be transferred between catchments. Currently, there is no widely agreed‐upon system for classifying river catchments. This paper develops a novel approach to classifying catchments based on the temporal dependence structure of daily mean river flow time series, applied to 116 near‐natural ‘benchmark’ catchments in the UK. The classification system is validated using 49 independent catchments.

Effects of incorporating multi-seasonal information into image classifications for large-scale land cover mapping are investigated. Data from four Landsat7 ETM+ scenes (March, May, June 2002, September 1999) were included step-wise into classifications by discriminant analysis to document their relevance for classification accuracy. The classification using all four images reached a maximum accuracy of 69.2%, significantly higher compared with single-date classifications and showing less fluctuations in classification accuracy.