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008 140620s2012 th ad ||| |000 0 eng d
035 _a.b12135057
099 9 _aAIT Thesis no.NR-12-09
100 0 _aLe Van Dung
245 1 0 _aUsing multi-temporal modis data for mapping the paddy rice cultivation area in Ninh Binh Province, Vietnam
260 _aPathum Thani :
_bAsian Institute of Technology,
_c2012
300 _a63 leaves :
_bill., maps, charts
490 1 _aThesis ;
_vno. NR-12-09
500 _aA thesis submitted in partial fulfillment of the requirement for the degree of Master of Science in Natural Resources Management, School of Environment, Resources and Development
502 _aThesis (M. Sc.) - Asian Institute of Technology, 2012
520 _aThe paddy rice cultivation in the Red River Delta, Vietnam has an important role in food security, human health as well as environment. Ninh Binh Province is the one of main paddy cultivation regions of Red River Delta. Mapping paddy rice area in Ninh Binh Province by using remote sensing techniques are useful for the policy makers to manage and plan for food security and socio-economic development in the province as well as in region. There are many kinds of satellites that supply useful information for mapping and monitoring of paddy rice area such as MODIS, LANDSAT. Multi-temporal eight-day composite MODIS products (MOD09A1, MOD09Q1) and Landsat Thematic Mapper (TM) dataset for mapping paddy rice area. Two images of MODIS in 2010 without effects of clouds were chosen as input data of classification. MODIS images are classified by using Maximum Livelihood Classification algorithm in supervised classification, and then method of subpixel classification was implemented to increase accuracy of classification result of paddy rice area. The map of paddy rice cultivation area was created after using supervised classification and subpixel classification. The accuracy of results was over 74% (for 02 June 2010) and 78% (for 14 September 2010) of land use classification in MODIS images. These results are acceptable for the moderate spatial resolution images. Result of subpixel classification was over 86% (02 June 2010) and 90% (14 September 2010) of accuracy. The area estimation from MODIS was compared with area statistics from local government. R2 {u2265} 0.90 showed the strong correlation between estimation data and statistical data from local government. The result of this study will be useful for local people and policy makers in management of paddy land use.
650 0 _aLand use
_zVietnam
_zNinh Binh
650 0 _aRice
_xRemote sensing
_zVietnam
_zNinh Binh
700 1 _aShrestha, Rajendra Prasad,
_eChairperson
700 0 _aTaravudh Tipdecho,
_eExamination committee
700 1 _aRanamukhaarachchi, S.L.,
_eExamination Committee
710 2 _aHUAF,
_eScholarship donor
710 2 _aHAU,
_eScholarship donor
710 2 _aAsian Institute of Technology Fellowship,
_eScholarship donor
710 2 _aFord Foundation,
_eScholarship donor
810 2 _aAsian Institute of Technology.
_tThesis ;
_vno. NR-12-09
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B03532
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_tAbstract--AIT Thesis no.NR-12-09
_vn
945 _lmnait
945 _lmnait
945 _lmnarc
945 _lmnarc
942 _c20
942 _c40
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