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Displaying 206 - 210 of 661Object-based land cover change detection for cross-sensor images
Accurate and timely land cover change detection at regional and global scales is necessary for both natural resource management and global environmental change studies. Satellite remote sensing has been widely used in land cover change detection over the past three decades. The variety of satellites which have been launched for Earth Observation (EO) and the large volume of remotely sensed data archives acquired by different sensors provide a unique opportunity for land cover change detection.
Sloping farmland identification using hierarchical classification in the Xi-He region of China
The Loess Plateau suffers the most serious soil erosion in China. Sloping cultivated land is one of the most common land types in the region, and it leads to severe soil erosion. Analyses based on fine resolution satellite imagery can play a key role in the surveying of sloping farmland. In this article, a combination of remote-sensing (RS) and geographical information system (GIS) techniques under the hierarchical classification framework is used to investigate the sloping cultivated land in the Xi–He ecological engineering demonstration region of the Loess Plateau.
Variation in NDVI values with change in spatial resolution for semi-arid savanna vegetation: a case study in northwestern South Africa
Natural vegetation and crop-greening patterns in semi-arid savannas are commonly monitored using normalized difference vegetation index (NDVI) values from low spatial resolution sensors such as the Advanced Very High Resolution Radiometer (AVHRR) (1 km, 4 km) and Moderate Resolution Imaging Spectroradiometer (MODIS) (250 m, 500 m). However, because semi-arid savannas characteristically have scattered tree cover, the NDVI values at low spatial resolution suffer from the effect of aggregation of near-infrared and red energy from adjacent vegetated and non-vegetated cover types.
Characterizing temporal vegetation dynamics of land use in regional scale of Java Island, Indonesia
Improving the understanding of land use and land cover is a major research challenge for the human-environmental sciences and is essential for many aspects of global environmental research. Considering seasonal vegetation dynamics or phenological dynamics in multi-year series leads to a broader view of land use and land cover. This study is based on the hypothesis that a pixel representing a complex but consistent land use has a typical, distinct and repeated temporal pattern of vegetation index inter-annually, which can be used as characteristic signatures for land use classification.
Evaluation of land cover classification based on multispectral versus pansharpened landsat ETM+ imagery
Land cover generated from satellite images is widely used in many real-world applications such as natural resource management, forest type mapping, hydrological modeling, crop monitoring, regional planning, transportation planning, public information services, and so on. Moreover, land cover data are one of the primary inputs to many geospatial models.