Stonefly samples were collected from disturbed and undisturbed regions of two river basins, tributaries of the Upper Váh River basin (the West Carpathians). Water temperature, oxygen content, coarse benthic matter and some stonefly metrics (abundance, biomass, richness, index of diversity, % predators, % shredders, stonefly total score and stonefly average score) were all negatively influenced by the extent of urban and field land cover.

REVEALS-based quantitative reconstruction of Holocene vegetation cover (expressed in plant functional types, PFTs) is used in the LANDCLIM project to assess the effect of human-induced land-cover change on past climate in NW Europe. Using the Czech Quaternary Pollen Database, this case study evaluates the extent to which selection of data and input parameters for the REVEALS model applications would affect reconstruction outcomes.

Daily tropical rainfall measuring mission (TRMM)-based rainfall and Landsat-derived land-cover maps were used to retrospectively simulate runoff for the Black Volta Basin. This was to ascertain the usefulness of the increasingly available satellite observation data to augment ground-measured hydrometeorological data for unguaged basins or basins with inadequate data. Both visual and statistical comparison of TRMM-based rainfall with the gauged rainfall indicates that the monthly rainfall data are statistically comparable.

Baylisascaris procyonis is a zoonotic nematode commonly found in raccoons (Procyon lotor). Human-altered landscapes can support dense populations of raccoons, increasing the potential for interaction between humans and these animals. We used raccoon feces provided by licensed fur trappers to investigate environmental variables that influence prevalence of B. procyonis at 2 sites in Wisconsin. Trappers submitted raccoon feces to us, along with information on sex, age (juvenile and adult), and approximate trap location for each animal.

To improve the understandings on regional climatic effects of past human-induced land cover changes, the surface albedo changes caused by conversions from natural vegetation to cropland were estimated across northeastern China over the last 300 years, and its climatic effects were simulated by using the Weather Research and Forecasting (WRF) model. Essential natural vegetation records compiled from historical documents and regional optimal surface albedo dataset were used.

A modelling experiment is used to examine different land-use scenarios ranging from extreme deforestation (31% forest cover) to pristine (95% forest cover) conditions and related Payment for Ecosystem Services (PES) schemes to assess whether a change in streamflow dynamics, discharge extremes and mean annual water balance of a 73.4-km² tropical headwater catchment in Costa Rica could be detected.

PURPOSE: Until recently, life cycle assessments (LCAs) have only addressed the direct greenhouse gas emissions along a process chain, but ignored the CO2 emissions of land-use. However, for agricultural products, these emissions can be substantial. Here, we present a new methodology for including the implications of land occupation for CO2 emissions to realistically reflect the consequences of consumers’ decisions.

This study investigates timber demand in Bangladesh. In evaluating timber demand, the significant contributing factors like forest land cover, frequency of furniture manufacturing, price of timber substitute, population growth and railway density have been examined. Panel data over a longer period for a developing country like Bangladesh were not easily available. The data sources were very sporadic for the study — there was no common data pool. A panel dataset over a 17-year period was simulated and analyzed for the study.

Spring phenophases such as the beginning of leaf unfolding, measured in the Irish gardens of the International Phenological Garden (IPG) network, indicate an earlier spring occurrence hence a longer growing season. However, these measurements are limited to selected species of trees at a few point locations in the southern half of the country. The aim of this study was to develop a methodology, based on satellite remote sensing, to measure the vegetation start of season (SOS) across the whole island of Ireland on an annual basis, complementary to existing ground-based methods.

Airborne light detection and ranging (LiDAR) systems are used to measure the range (distance from the sensor to the target) and the intensity data (the backscattered energy from the target). LiDAR has been used extensively to model the topography of the Earth surface. Nowadays, LiDAR systems operating in the near-infrared spectral range are also gaining high interest for land cover classification and object recognition. LiDAR system requires geometric calibration (GC) and radiometric correction (RC) in order to maximize the benefit from the collected LiDAR data.

This research examines the spatio-temporal trends in Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modelling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) time series to ascribe land use change and precipitation to observed changes in land cover from 1982 to 2007 in the Mexican Yucatán Peninsula, using seasonal trend analysis (STA).

The spatio-temporal distribution of land cover provides fundamental data for global climate and environmental change research. In recent decades, five global land cover maps have been produced based on remote sensing data sources and methodologies. Related research have shown that the availability and quality of the first four global land cover datasets are poor at the regional or the continental scale for a variety of reasons. There is still no consensus on the accuracy of the latest global land cover map.