Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms
cg.contact | xiangming.xiao@ou.edu | en_US |
cg.contributor.center | International Center for Agricultural Research in the Dry Areas - ICARDA | en_US |
cg.contributor.center | University of Oklahoma, Center for Spatial Analysis - OU - CSA | en_US |
cg.contributor.center | University of Oklahoma, School of Meteorology - OU - SoM | en_US |
cg.contributor.center | University of Oklahoma, College of Arts and Sciences - OU - CAS | en_US |
cg.contributor.center | University of Oklahoma, College of Atmospheric and Geographic Science - OU - AGS | en_US |
cg.contributor.center | Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research - cas-igsnrr | en_US |
cg.contributor.crp | CGIAR Research Program on Dryland Systems - DS | en_US |
cg.contributor.funder | Indian Council of Agricultural Research - ICAR | en_US |
cg.contributor.project | India Collaborative Program: Restricted funding for breeding for resistance to abiotic stresses in pulses & for 2017/2018 - 2017/2020 - 2020/2021 | en_US |
cg.contributor.project-lead-institute | International Center for Agricultural Research in the Dry Areas - ICARDA | en_US |
cg.coverage.country | CN | en_US |
cg.coverage.region | Eastern Asia | en_US |
cg.creator.id | Biradar, Chandrashekhar: 0000-0002-9532-9452 | en_US |
cg.date.embargo-end-date | 2115-01-28 | en_US |
cg.identifier.doi | https://dx.doi.org/10.1016/j.rse.2015.01.004 | en_US |
cg.isijournal | ISI Journal | en_US |
cg.issn | 0034-4257 | en_US |
cg.journal | Remote Sensing of Environment | en_US |
cg.subject.agrovoc | land use | en_US |
cg.subject.agrovoc | land use change | en_US |
cg.subject.agrovoc | Rice | en_US |
cg.volume | 160 | en_US |
dc.contributor | Xiao, Xiangming | en_US |
dc.contributor | Kou, Weili | en_US |
dc.contributor | Qin, Yuanwei | en_US |
dc.contributor | Zhang, Geli | en_US |
dc.contributor | Li, Li | en_US |
dc.contributor | Jin, Cui | en_US |
dc.contributor | Zhou, Yuting | en_US |
dc.contributor | Wang, Jie | en_US |
dc.contributor | Biradar, Chandrashekhar | en_US |
dc.contributor | Liu, Jiyuan | en_US |
dc.contributor | Moore III, Berrien | en_US |
dc.creator | Dong, Jinwei | en_US |
dc.date.accessioned | 2016-05-15T09:42:30Z | |
dc.date.available | 2016-05-15T09:42:30Z | |
dc.description.abstract | Agricultural land use change substantially affects climate,water, ecosystems, biodiversity, and humanwelfare. In recent decades, due to increasing population and food demand and the backdrop of global warming, croplands have been expanding into higher latitude regions. One such hotspot is paddy rice expansion in northeast China. However, there are no maps available for documenting the spatial and temporal patterns of continuous paddy rice expansion. In this study, we developed an automated, Landsat-based paddy rice mapping (Landsat- RICE) systemthat uses time series Landsat images and a phenology-based algorithmbased on the unique spectral characteristics of paddy rice during the flooding/transplanting phase. As a pilot study, we analyzed all the available Landsat images from 1986 to 2010 (498 scenes) in one tile (path/row 113/27) of northeast China, which tracked paddy rice expansion in epochs with five-year increments (1986–1990, 1991–1995, 1996–2000, 2001–2005, and 2006–2010). Several maps of land cover types (barren land and built-up land; evergreen, deciduous and sparse vegetation types; and water-related land cover types such as permanent water body, mixed pixels of water and vegetation, spring flooded wetlands and summer flooded land) were generated as masks. Air temperature was used to define phenology timing and crop calendar, which were then used to select Landsat images in the phenology-based algorithms for paddy rice and masks. The resultant maps of paddy rice in the five epochs were evaluated using validation samples from multiple sources, and the overall accuracies and Kappa coefficients ranged from84 to 95% and 0.6–0.9, respectively. The paddy rice area in the study area substantially increased from 1986 to 2010, particularly after the 1990s. This study demonstrates the potential of the Landsat-RICE systemand time series Landsat images for tracking agricultural land use changes at 30-mresolution in the temperate zone with single crop cultivation | en_US |
dc.format | en_US | |
dc.identifier | https://mel.cgiar.org/dspace/limited | en_US |
dc.identifier | http://www.sciencedirect.com/science/journal/00344257/160/supp/C | en_US |
dc.identifier.citation | Jinwei Dong, Xiangming Xiao, Weili Kou, Yuanwei Qin, Geli Zhang, Li Li, Cui Jin, Yuting Zhou, Jie Wang, Chandrashekhar Biradar, Jiyuan Liu, Berrien Moore III. (30/4/2015). Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms. Remote Sensing of Environment, 160, pp. 99-113. | en_US |
dc.identifier.status | Limited access | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.11766/4807 | |
dc.language | en | en_US |
dc.publisher | Elsevier | en_US |
dc.source | Remote Sensing of Environment;160,(2015) Pagination 99-113 | en_US |
dc.subject | landsat-rice phenology | en_US |
dc.subject | northeast china | en_US |
dc.subject | paddy rice | en_US |
dc.title | Tracking the dynamics of paddy rice planting area in 1986–2010 through time series Landsat images and phenology-based algorithms | en_US |
dc.type | Journal Article | en_US |
dcterms.available | 2015-01-28 | en_US |
dcterms.extent | 99-113 | en_US |
dcterms.issued | 2015-04-30 | en_US |
mel.impact-factor | 6.265 | en_US |
mel.project.open | http://geoagro.icarda.org/india/ | en_US |