Land cover classification and change detection analysis using LandSat series and geospatial datasets in Nepal from 1980 to 2010

2015 4th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2015

Volumn , Issue , 2015, Pages 414-418

  Guo, Zhe ^a   Shrestha, Ranjay ^b   Zhang, Wei ^a   Bhandary, Prapti ^a   Yu, Gennong ^b   Di, Liping ^b  

^a INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE   (United States)

^b GEORGE MASON UNIVERSITY   (United States)

Author keywords

Change detection; Land cover and land use; Nepal; Remote sensing; Supervised classification

Indexed keywords

CLASSIFICATION (OF INFORMATION); COST EFFECTIVENESS; DEFORESTATION; LAND USE; REMOTE SENSING; SIGNAL DETECTION; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES; TIME SERIES ANALYSIS;

CHANGE DETECTION; CHANGE DETECTION ANALYSIS; ENVIRONMENTAL RESEARCHES; LAND COVER; LAND COVER CLASSIFICATION; LAND USE AND LAND COVER CHANGE; NEPAL; SUPERVISED CLASSIFICATION;

GEOGRAPHIC INFORMATION SYSTEMS;

EID: 84960434103     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/Agro-Geoinformatics.2015.7248159     Document Type: Conference Paper

References (11)

1. Barnekow Lilies, J-P., T. B. Shrestha, L. P. Dhakal, R. P. Nayaju, and R Shrestha. The map of potential vegetation of Nepal: a forestry/agro-ecologicallbiodiversity classification system. H0rsholm: Center for Skov, Landskab og Planhegning, Kobenhavns Universitet, Development and Environment, 2005.
2. Cortes, C., and V Vapnik. "Support-vector networks." Machine Learning 3, no. 20 (1995): 273
3. Dale, V. H., Offerman, H., Pearson, S., and O'Neill, R. V. (1994). Effects of Forest Fragmentation on Neotropical Fauna, Conservation Biology, 8, 1027-1036.
4. Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter., S. R., Chapin, F. S., Coe, M. T., Daily, G. c., Gibbs, H. K., Helkowski, J. H., Holloway, T., Howard, E. A., Kucharik, C. J., Monfreda, C., Patz, J. A., Prentice, I. C., Ramankutty, N., and Snyder, P. K. (2005). Global Consequences of Land Use, Science, 309, 570-574
5. Pielke, Sr., R. A. (2001). Earth System Modeling-An Integrated Assessment Tool for Environmental Studies, in Present and Future of Modeling Global Environmental Change: Toward Integrated Modeling, eds. T. Matsuno and H. Kida, Tokyo: Terra Scientific, 311-337.
6. Pielke, Sr., R. A. (2005). Land Use and Climate Change, Science, 310, 1625-1626. View related paper by Feddema et al. 2005: The importance of land-cover change in simulating future climates., 310, 1674-1678.
7. Ramankutty N (2004) Croplands in West Africa: A geographically explicit dataset for use in models. Earth Interact 8: 1-22 doi: 10.1175/1087-3562(2004)8.
8. Tou, J. T., and R.C. Gonzalez. Pattern Recognition Principles. Reading, Massachusetts: Addison-Wesley Publishing Company, 1974.
9. Turner, B. L., D. Skole, S. Sanderson, G. Fischer, L. Fresco, and R. Leemans. (1995). Land-use and land-cover change sciencelresearch plan. IGBP report no. 35 and HDP report no. 7.
10. Verchot, L. V., Davidson, E. A., Cattanio, J. H., Ackerman, I. L., Erickson, H. E., and Keller, M. (1999). Land Use Change and Biogeochemical Controls of Nitrogen Oxide Emissions From Soils in Eastern Amazonia. Global Biogeochemical Cycles, 13, 31-46.
11. Vitousek, P. M. 1994. Beyond global warming: ecology and global change. Ecology. 75: 1861-1876.