The Scops Owl Otus scops (L., 1758) is a species of European concern, which suffered a noticeable decrease in distribution in the last decades, and changes in agricultural practices have been proposed as a major threat for this owl. We studied the habitat preference of the Scops Owl by assessing the habitat occupancy of 401 territories distributed in a large area in northwest Italy, with a special focus on 98 territories located in a high-density area (Monferrato).

Within the framework of IWRM, a major concern in the humid tropics is the effects of ‘global warming' on the storm rainfall-runoff hydrology of both forests and converted forest lands. Further how such effects need to be incorporated within adaptive, forest-water-land management. But since the mid- 20th century, dramatic changes in land- use (LU) and land cover (LC) have also occurred which have led to rapid rates of deforestation and an expansion of land--forest degradation.

Although land cover and meteorological conditions are known to impact mercury (Hg) deposition processes, few studies have addressed how changes in forest cover and shifting climatic conditions will impact the Hg cycle. The purpose of this study was to examine the effects of forest type (hardwood vs. conifer) and meteorological variation on atmospheric Hg deposition in two forest stands in Huntington Wildlife Forest in upstate New York, USA.

Cloud forest streams are diverse ecosystems that provide valuable services (i.e., drinking water), but are threatened by anthropogenic activities on the watershed. We assessed the relationships between forest cover in the catchment, riparian vegetation, water chemistry, channel geomorphology, and the diversity of aquatic insects (taxonomic and functional diversity) in streams running through cloud forest in the upper part of La Antigua watershed, Mexico.

This study aims to evaluate different methods of integrating optical and multipolarized radar data for land use and land cover (LULC) mapping in an agricultural frontier region in the Central Brazilian Amazon, which requires continuous monitoring due to the increasing human intervention. The evaluation is performed using different sets of fused and combined data.

Providing land cover spatio-temporal information and geo-computing through web service is a new challenge for supporting global change research, earth system simulation and many other societal benefit areas. This requires an integrated knowledge representation and web implementation of static land cover and change information, as well as the related operations for geo-computing. The temporal logic relations among land cover snapshots and increments were examined with a matrix-based three-step analysis.

Due to the particular geographical location and complex geological conditions, the Three Gorges of China suffer from many landslide hazards that often result in tragic loss of life and economic devastation. To reduce the casualty and damages, an effective and accurate method of assessing landslide susceptibility is necessary. Object-based data mining methods were applied to a case study of landslide susceptibility assessment on the Guojiaba Town of the Three Gorges.

Uses of high spatial resolution data obtained from satellite-based sensors include creating land cover maps, deriving large-scale quantitative assessments such as vegetation indices, and visually assessing an area for qualitative information only assessable from large-scale digital data. One of the more popular uses of high spatial resolution data is to use the image as a base map for on-screen digitizing spatially dependent vector products.

Optical Earth Observation data with moderate spatial resolutions, typically MODIS (Moderate Resolution Imaging Spectroradiometer), are of particular value to environmental applications due to their high temporal and spectral resolutions. Time-series of MODIS data capture dynamic phenomena of vegetation and its environment, and are considered as one of the most effective data sources for land cover mapping at a regional and national level.

This paper contributes to the discussion on current issues in methodologies of mapping land cover in the agro-silvo-pastoral landscapes of the Mediterranean. These landscapes, characterized by intermixed land use and indefinite boundaries, require particular attention in applying the patch-corridor-matrix model when classifying patches and their delineation. In a case study area in southeast Portugal, mainly characterized by agro-silvo pastoral systems, the land cover for 1990 has been mapped.

Areal interpolation is used to transfer attribute data between geographically incongruous zonal systems. Remotely sensed land cover data are widely used in intelligent areal interpolation methods to solve this problem. This article examines the usefulness of different publicly available remotely sensed land cover data sets as ancillary data used in conjunction with different areal interpolation methods.

One of the potential applications of polarimetric Synthetic Aperture Radar (SAR) data is the classification of land cover, such as forest canopies, vegetation, sea ice types, and urban areas. In contrast to single or dual polarized SAR systems, full polarimetric SAR systems provide more information about the physical and geometrical properties of the imaged area. This paper proposes a new Bayes risk function which can be minimized to obtain a Likelihood Ratio (LR) for the supervised classification of polarimetric SAR data.