The bracken (Pteridium aquilinum) fern is environmentally significant due to its great abundance and swift colonisation, and its perception as a problem plant in degrading agricultural or ecologically sensitive land. Various attempts have been made to map bracken using remote sensing, but these have proved relatively unsuccessful, often apparently constrained by the lack of spatial detail associated with medium spatial resolution satellite sensors such as the Landsat series. In this study, bracken was characterised using a combination of 30m Landsat sensor imagery and 4m IKONOS imagery.

Numerous studies underline the importance of immaterial benefits provided by ecosystems and especially by cultural landscapes, which are shaped by intimate human–nature interactions. However, due to methodological challenges, cultural ecosystem services are rarely fully considered in ecosystem services assessments. This study performs a spatially explicit participatory mapping of the complete range of cultural ecosystem services and several disservices perceived by people living in a cultural landscape in Eastern Germany.

Central India hosts one of the largest repositories of archaeological sites in the world having a semi-arid climate and distinct eco-geography which is prone to rapid change due to human activities. This paper discusses the changes in land use and land cover for the past twenty-three years in the region altering the rich cultural heritage, revealing by the presence of numerous painted rock-shelter sites in the region. The land cover and land use changes in terms of deforestation, urban growth and development and sandstone mining have been evaluated in the present study.

In this study, the Surface Energy Balance Algorithms for Land (SEBAL) model and Moderate Resolution Imaging Spectroradiometer (MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration (ET) over the Sanjiang Plain, Northeast China. Land cover/land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index (NDVI) time series data, which were reconstructed based on the Savitzky-Golay filtering approach.

The aim of the research is to analyse the landscape structure changes from the end of the Soviet times in 1974–1986 until 2005 when market economy existed in Lithuania. The changes of landscape structure were observed in 100 sample areas (squares) each of them having 2.5 km2 area and distributed in different landscape types. The changes in sample areas (squares) with determination of land cover structure transformations were observed using topographic photos and ortophoto images at a scale 1:10 000.

Large carnivores, with their expansive home range and resource requirements, are a good model for understanding how animal populations alter habitat selection and use as human densities and development increase. We examined the habitat selection of red wolves (Canis rufus) in North Carolina, USA, where the population of red wolves resides in a mosaic of naturally occurring and human-associated land cover. We used locations from 20 GPS-collared red wolves, monitored over 3years, to develop resource selection functions at the landscape level.

In this study we analyzed the large scale spatial patterns of river pH, alkalinity, and CO₂ partial pressure (PCO₂) in North America and their relation to river catchment properties. The goal was to set up empirical equations which can predict these hydrochemical properties for non-monitored river stretches from geodata of e.g. terrain attributes, lithology, soils, land cover and climate. For an extensive dataset of 1120 river water sampling locations average values of river water pH, alkalinity and PCO₂ were calculated.

The rapid population growth and ongoing development activities has resulted in natural resources demolition. However, the dynamics of the natural resources in relation to different biophysical and socio-economic factors are still remains poorly understood. The present study investigates the basic natural resources i.e. forest, rangeland and surface water bodies’ status using satellite data for the years 1990, 1998, and 2006, and their change detection in relation to biophysical and socio-economic factors.

Encroachment of nitrogen-fixing trees and shrubs into grasslands and savannas is a well-documented land cover change that occurs worldwide. In the Rio Grande Plains region of southern Texas, previous studies have shown woody encroachment by leguminous Prosopis glandulosa (mesquite) trees increases soil C and N, decreases microbial biomass N relative to soil N, and accelerates N mineralization and nitrification.

High N₂O emissions have been observed in semi-arid grasslands, especially during freeze/thaw periods, when denitrification might be the main process of N₂O production. However, there have been few denitrification studies in semi-arid grassland. This study was designed to determine the denitrification potential of four representative land cover types (typical steppe, meadow steppe, marshland, arid steppe) in two grasslands in Inner Mongolia, China.

Support vector machines (SVM) are nowadays receiving increasing attention in remote sensing applications although this technique is very sensitive to the parameters setting and training set definition. Self-training is an effective semisupervised method, which can reduce the effort needed to prepare the training set by training the model with a small number of labeled examples and an additional set of unlabeled examples. In this study, a novel semisupervised SVM model that uses self-training approach is proposed to address the problem of remote sensing land cover classification.

Labeling of connected components in an image or a raster of non-imagery data is a fundamental operation in fields of pattern recognition and machine intelligence. The bulk of effort devoted to designing efficient connected components labeling (CCL) algorithms concentrated on the domain of binary images where labeling is required for a computer to recognize objects.