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Showing items 28000 through 28008 of 73560.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.
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.
Canadaâs National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues.
Capsule Differences in arable land-use intensity and land use changes in lowland and higher-altitude regions of the Czech Republic affected long-term population trends of farmland birds.
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.
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.
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.
This paper examines the implications of adopting catchment scale approaches for the sustainable management of land and water systems.
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.
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