Regional Applications of Crop Phenology Proportion Index on Fractional Crop Area Estimation Using MO DIS Data

被引:0
|
作者
Li, Le [1 ]
Pan, Yaozhong [2 ]
Zhang, Jinshui [2 ]
Zhu, Xiufang [2 ]
Li, Fangting [3 ]
机构
[1] Beijing Normal Univ, Coll Life Sci, Beijing, Peoples R China
[2] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing, Peoples R China
[3] State Key Lab Informat Engn Surveying Mapping & S, Wuhan, Peoples R China
关键词
MODIS; sub-pixel; agriculture mapping; regional estimation; LAND-COVER; MODIS; AGRICULTURE;
D O I
暂无
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
MODIS data have proven useful for various vegetation applications at large scales. Considering the mismatched spatial resolution between MODIS and agricultural field size, it is important to map crop areas at the sub-pixel level of MODIS. The Crop Phenology Proportion Index (CPPI) model has shown promises in deriving fractional crop areas in typical cultivated areas. In this study, we applied the CPPI model to map fractional winter wheat areas for the entire Jiangsu Province in China. We employed the National Agricultural Census Data to stratify counties of different cultivation intensities and selected samples for stratified counties. We evaluated the model performance and found that an overall accuracy of 82.3% for the estimated winter wheat areas. The results demonstrated the potential of the CPPI model for estimating fractional crop areas across large geographical regions.
引用
收藏
页码:162 / 166
页数:5
相关论文
共 50 条
  • [31] Objective sampling estimation of regional crop area supported by remotely sensed images
    Barreto Luiz, Alfredo Jose
    Formaggio, Antonio Roberto
    Neves Epiphanio, Jose Carlos
    Arenas-Toledo, John Mauricio
    Goltz, Elizabeth
    Brandao, Daniela
    [J]. PESQUISA AGROPECUARIA BRASILEIRA, 2012, 47 (09) : 1279 - 1287
  • [32] Wheat crop production estimation using satellite data
    Bairagi G.D.
    Hassan Z.-U.
    [J]. Journal of the Indian Society of Remote Sensing, 2002, 30 (4) : 213 - 219
  • [33] Forest and Crop Leaf Area Index Estimation Using Remote Sensing: Research Trends and Future Directions
    Xu, Jin
    Quackenbush, Lindi J.
    Volk, Timothy A.
    Im, Jungho
    [J]. REMOTE SENSING, 2020, 12 (18)
  • [34] LINEAR MIXTURE MODELING APPLIED TO AVHRR DATA FOR CROP AREA ESTIMATION
    QUARMBY, NA
    TOWNSHEND, JRG
    SETTLE, JJ
    WHITE, KH
    MILNES, M
    HINDLE, TL
    SILLEOS, N
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 1992, 13 (03) : 415 - 425
  • [35] A crop phenology detection method using time-series MODIS data
    Sakamoto, T
    Yokozawa, M
    Toritani, H
    Shibayama, M
    Ishitsuka, N
    Ohno, H
    [J]. REMOTE SENSING OF ENVIRONMENT, 2005, 96 (3-4) : 366 - 374
  • [36] Spatialisation of a crop model using phenology derived from remote sensing data
    Duchemin, B
    Hadria, R
    Rodriguez, JC
    Lahrouni, A
    Khabba, S
    Boulet, G
    Mougenot, B
    Maisongrande, P
    Watts, C
    [J]. IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 2200 - 2202
  • [37] Extending Crop Type Reference Data Using a Phenology-Based Approach
    Yadav, Kamini
    Congalton, Russell G.
    [J]. FRONTIERS IN SUSTAINABLE FOOD SYSTEMS, 2020, 4
  • [38] Remote Sensing Derived Leaf Area Index and Potential Applications for Crop Modeling
    Smith, A. M.
    Bourgeois, G.
    DeJong, R.
    Nadeau, C.
    Freemantle, J.
    Teillet, P. M.
    Chichagov, A.
    Fedosejevs, G.
    Welm, H.
    Shankaie, A.
    [J]. 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 2088 - +
  • [39] Exploring the possibilities of remote yield estimation using crop water requirements for area yield index insurance in a data-scarce dryland
    Eze, Emmanuel
    Girma, Atkilt
    Zenebe, Amanuel
    Kourouma, Jean Moussa
    Zenebe, Gebreyohannes
    [J]. JOURNAL OF ARID ENVIRONMENTS, 2020, 183
  • [40] CROP MAPPING APPLICATIONS AT SCALE: USING GOOGLE EARTH ENGINE TO ENABLE GLOBAL CROP AREA AND STATUS MONITORING USING FREE AND OPEN DATA SOURCES
    Lemoine, Guido
    Leo, Olivier
    [J]. 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 1496 - 1499