Classification using ASTER data and SVM algorithms;: The case study of Beer Sheva, Israel
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Summary
A new dataset from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spaceborne sensor was used with support vector machine (SVM)-based algorithms for classification processing, showing that the approach based on SVM has high performance in convergence, speed, and accuracy of training and classifying.
- Type
- article
- Published
- 2002-05-01
- Cited by
- 277
- References
- 9
- OpenAlex
- https://openalex.org/W52871114
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:128059054
Keywords
Advanced Spaceborne Thermal Emission and Reflection Radiometer, Support vector machine, Multispectral image, Remote sensing, Computer science
References
- The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA's Terra platform
- Evaluation of Two Applications of Spectral Mixing Models to Image Fusion
- Input space versus feature space in kernel-based methods
- On domain knowledge and feature selection using a support vector machine
- Support vector machines for histogram-based image classification
- An overview of statistical learning theory
- Comparison of the spectral information content of Landsat Thematic Mapper and SPOT for three different sites in the Phoenix, Arizona region
- SPATIAL QUALITY EVALUATION OF FUSION OF DIFFERENT RESOLUTION IMAGES
- The Nature of Statistical Learning Theory
- The Nature of Statistical Learning Theory
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- Advanced Techniques for the Classification of Very High Resolution and Hyperspectral Remote Sensing Images
- MERIS BASED LAND COVER CHARACTERIZATION: A COMPARATIVE STUDY
- Remote Sensing of Urbanization and Environmental Impacts
- Urban land use detection and change using an enhanced monitoring system with remote sensing tools and GIS in the EUREGIO Meuse-Rhine area
- Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping.
- Mise à jour d’une base de données d’occupation du sol à grande échelle en milieux naturels à partir d’une image satellite THR
- Integration of multi-seasonal Landsat 8 and TerraSAR-X data for urban mapping: An assessment
- Evaluating the Aster Sensor for Mapping and Characterizing Forest Fire Fuels in Northern Idaho
- Hydrological modelling in the meso scale semiarid region of Wadi Kafrein / Jordan -The use of innovative techniques under data scarcity
- River-flow boundary delineation from digital aerial photography and ancillary images using Support Vector Machines
- Multi-source remote sensing image fusion based on support vector machine
- The Improvement of Land Cover Classification by Thermal Remote Sensing
- Factors influencing the accuracy of remote sensing classifications : a comparative study
- Spatial pattern recognition for crop-livestock systems using multispectral data
- Multiclass Approaches for Support Vector Machine Based Land Cover Classification
- Use of multispectral data to identify farm intensification levels by applying emergent computing techniques
- Expansion of a glacial lake, Tsho Chubda, Chamkhar Chu Basin, Hindukush Himalaya, Bhutan
- Predicted ultimate capacity of laterally loaded piles in clay using support vector machine
- Quality-Oriented Classification of Aircraft Material Based on SVM
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