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Displaying 301 - 305 of 661Evaluation of ASTER GDEM using GPS benchmarks and SRTM in China
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) has generated one of the most complete high-resolution digital topographic data sets of the world to date. The ASTER GDEM covers land surfaces between 83° N and 83° S at a spatial resolution of 1 arc-second (approximately 30 m at the equator). As an improvement over Shuttle Radar Topography Mission (SRTM) coverage, the ASTER GDEM will be a very useful product for many applications, such as relief analysis, hydrological studies, and radar interferometry.
Large floods in Europe, 1985–2009
The paper looks at two metrics of flood events: flood severity (related to flood frequency) and flood magnitude (related to flood severity, as above, but also to flood duration and affected area). A time series of flood information, over 25 years, collected by the Dartmouth Flood Observatory, is used to describe the spatio-temporal variability of large floods in Europe. Direct factors responsible for changes in flood severity and magnitude over time may be related to both climate and ground surface changes.
Deforestation and landscape structure changes related to socioeconomic dynamics and climate change in Zagros forests
The Zagros region of western Iran has been affected by the recent changes both in amount and in structure of forest cover. We evaluated the influence of several driving forces on forest cover and structure, including socioeconomic (urban and rural population and rural income) and climatic (mean annual rainfall and mean annual temperature) variables. We acquired all time series Landsat images of a study site from 1972 to 2009. The images were classified to produce a land cover map of each year.
hybrid method combining pixel-based and object-oriented methods and its application in Hungary using Chinese HJ-1 satellite images
Pixel-based and object-oriented processing of Chinese HJ-1-A satellite imagery (resolution 30 m) acquired on 23 July 2009 were utilized for classification of a study area in Budapest, Hungary. The pixel-based method (maximum likelihood classifier for pixel-level method (MLCPL)) and two object-oriented methods (maximum likelihood classifier for object-level method (MLCOL) and a hybrid method combining image segmentation with the use of a maximum likelihood classifier at the pixel level (MLCPL)) were compared. An extension of the watershed segmentation method was used in this article.
VSDI: a visible and shortwave infrared drought index for monitoring soil and vegetation moisture based on optical remote sensing
In this article, a new index, the visible and shortwave infrared drought index (VSDI), is proposed for monitoring both soil and vegetation moisture using optical spectral bands. VSDI is defined as , where ρ represents the reflectance of shortwave infrared (SWIR) red and blue channels, respectively. VSDI is theoretically based on the difference between moisture-sensitive bands (SWIR and red) and moisture reference band (blue), and is expected to be efficient for agricultural drought monitoring over different land-cover types during the plant-growing season.