Very high resolution (VHR) images are a valuable information source to estimate land cover area and land cover change. When full coverage of a region with VHR images is not affordable, a sample of images can be considered. Square grids provide a practical sampling frame for VHR images. When using a land cover map as pseudo-truth, the sampling variance is easily assessed but may be overestimated if the land cover map has a coarse resolution.

Water is central to life and earth processes, connecting physical, biological, chemical, ecological, and economic forces across the landscape. The vast scope of hydrologic sciences requires research efforts worldwide and across a wide range of disciplines.

This study uses a combination of Landsat series data (Multispectral Scanner or MSS, Thematic Mapper or TM and Enhanced Thematic Mapper or ETM+) to map land-use and land-cover change (LULCC) from 1975 to 2001. It extends the land change record to 2008 using Chinese–Brazil Earth Resources Satellite (CBERS)-2 and CBERS-2B data on a multi-scene level. It also establishes a methodology to correct for systematic distortion inherent in CBERS imagery without the loss of information present in Landsat 7 ETM+ imagery post-2003.

Little is known about the structure of riparian communities within the central Gulf coast of Texas. We present a phytosociological description of the riparian corridor within two contiguous sites along the Mission River in Refugio County, Texas, that differ in respect to tidal influence along the river, and compare this woody riparian community to others in Texas. In summer 2009 and 2010, we established 33 transects perpendicular to the river after reviewing digital data from ArcMap 9.3.1 on elevation, edaphic characteristics, uses of land, and cover of land and wetland.

The United Nations Environment Programme (UNEP) has begun a process of developing a legally binding instrument to manage emissions of mercury from anthropogenic sources. The UNEP Governing Council has concluded that there is sufficient evidence of significant global adverse impacts from mercury to warrant further international action; and that national, regional and global actions should be initiated as soon as possible to identify populations at risk and to reduce human generated releases.

Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions.

This study examines the causes and consequences of gully erosion, as perceived by the local people of Dangara area, Nigeria. The study particularly seeks to explore the local people’s perceptions of gully erosion and how it affects crop, settlement development, crop yields, land ownership and values, rural economics and private conservation investments in Dangara area of Nigeria’s Federal Capital Territory. It is based on analysis of data collected using questionnaires administered to 346 respondents in the area.

Object-based image analysis (OBIA) is a widely used method for knowledge-based interpretation of very high resolution imagery. It relies on expert knowledge to classify the desired classes from the imagery at hand. The definition of classes is subjective, usually project-specific and not shared with the community. Ontologies as a form of knowledge representation technique are acknowledged as solution to establish and document class definitions independently of an OBIA framework. However, ontologies have not yet been strongly integrated in this image analysis framework.

We review the current status of experimental studies in India to understand the linkages between afforestation and hydrology. This discipline deals with the use and management of water, social awareness of environmental problems, and ecosystem limitations on provision of watershed services by river basins in the mountain regions of India.

Soil erosion in southeast Spain is a complex process due to strong interactions between biophysical and human components. Significant progress has been achieved in the understanding of soil hydrological behavior, despite the fact that most investigations were focused on the experimental plot scale. Although experimental plots allow exploring the effect of multiple biophysical and anthropogenic factors, they provide limited insights in the combined effect of all factors acting together at the landscape scale.

Vegetation type is one of many factors that affect watershed hydrology and is an especially important influence on surface hydrological processes. Canopy and ground cover vegetation provide a natural cushion against the impact energy of rainfall in headwater portions of a stream basin, increasing water filtration into the soil and reducing surface runoff, but effects of different vegetation types are not fully understood. We sought to evaluate the capacity of different vegetation communities to regulate surface runoff in an alpine landscape.

Artificial neural networks (ANN) are nonlinear models widely investigated in hydrology due to their properties of universal approximation and parsimony. Their performance during the training phase is very good, and their ability to generalize can be improved by using regularization methods such as early stopping and cross-validation. In our research, two kinds of generic models are implemented: the feed-forward model and the recurrent model.