Spatial Distribution of Cropping Systems in South Asia Using Time-Series Satellite Data Enriched with Ground Data

被引:2
作者
Gumma, Murali Krishna [1 ]
Panjala, Pranay [1 ]
Dubey, Sunil K. [2 ]
Ray, Deepak K. [3 ]
Murthy, C. S. [2 ]
Kadiyala, Dakshina Murthy [4 ]
Mohammed, Ismail [1 ]
Takashi, Yamano [5 ]
机构
[1] Int Crops Res Inst Semi Arid Trop, Patancheru 502324, India
[2] Mahalanobis Natl Crop Forecast Ctr MNCFC, New Delhi 110012, India
[3] Univ Minnesota, Inst Environm, St Paul, MN 55108 USA
[4] Acharya NG Ranga Agr Univ, Dept Agron, Guntur 522034, India
[5] Asian Dev Bank, Dhaka 1207, Bangladesh
关键词
cropping systems; South Asia; crop type mapping; time-series analysis; crop phenology detection; MAPPING PADDY RICE; SPECTRAL MATCHING TECHNIQUES; USE/LAND-COVER LULC; FOOD SECURITY; GLOBAL CROPLANDS; IRRIGATED AREAS; LAND-COVER; MODIS; WATER; BASIN;
D O I
10.3390/rs16152733
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A cropping system practice is the sequential cultivation of crops in different crop seasons of a year. Cropping system practices determine the land productivity and sustainability of agriculture in regions and, therefore, information on cropping systems of different regions in the form of maps and statistics form critical inputs in crop planning for optimal use of resources. Although satellite-based crop mapping is widely practiced, deriving cropping systems maps using satellites is less reported. Here, we developed moderate-resolution maps of the major cropping systems of South Asia for the year 2014-2015 using multi-temporal satellite data together with a spectral matching technique (SMT) developed with an extensive set of field observation data supplemented with expert-identified crops in high-resolution satellite images. We identified and mapped 27 major cropping systems of South Asia at 250 m spatial resolution. The rice-wheat cropping system is the dominant system, followed by millet-wheat and soybean-wheat. The map showing the cropping system practices of regions opens up many use cases related to the agriculture performance of the regions. Comparison of such maps of different time periods offers insights on sensitive regions and analysis of such maps in conjunction with resources maps such as climate, soil, etc., enables optimization of resources vis-& agrave;-vis enhancing land productivity. Thus, the current study offers new opportunities to revisit the cropping system practices and redesign the same to meet the challenges of food security and climate resilient agriculture.
引用
收藏
页数:18
相关论文
共 55 条
  • [1] GLOBAL DISTRIBUTION OF NATURAL FRESH-WATER WETLANDS AND RICE PADDIES, THEIR NET PRIMARY PRODUCTIVITY, SEASONALITY AND POSSIBLE METHANE EMISSIONS
    ASELMANN, I
    CRUTZEN, PJ
    [J]. JOURNAL OF ATMOSPHERIC CHEMISTRY, 1989, 8 (04) : 307 - 358
  • [2] AUTOMATIC CORN SOYBEAN CLASSIFICATION USING LANDSAT MSS DATA .1. NEAR-HARVEST CROP PROPORTION ESTIMATION
    BADHWAR, GD
    [J]. REMOTE SENSING OF ENVIRONMENT, 1984, 14 (1-3) : 15 - 29
  • [3] Becerra J., 2006, P 8 INT C SO HEM MET, P861
  • [4] Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India
    Biggs, T. W.
    Thenkabail, P. S.
    Gumma, M. K.
    Scott, C. A.
    Parthasaradhi, G. R.
    Turral, H. N.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2006, 27 (19) : 4245 - 4266
  • [5] Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program
    Boryan, Claire
    Yang, Zhengwei
    Mueller, Rick
    Craig, Mike
    [J]. GEOCARTO INTERNATIONAL, 2011, 26 (05) : 341 - 358
  • [6] Land Surface Water Index (LSWI) response to rainfall and NDVI using the MODIS Vegetation Index product
    Chandrasekar, K.
    Sai, M. V. R. Sesha
    Roy, P. S.
    Dwevedi, R. S.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (15) : 3987 - 4005
  • [7] Choice H., 2009, Agroecological Zones
  • [8] Connor D.J., 2011, Crop ecology: productivity and management in agricultural systems
  • [9] Irrigated areas of India derived using MODIS 500 m time series for the years 2001-2003
    Dheeravath, V.
    Thenkabail, P. S.
    Chandrakantha, G.
    Noojipady, P.
    Reddy, G. P. O.
    Biradar, C. M.
    Gumma, M. K.
    Velpuri, M.
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2010, 65 (01) : 42 - 59
  • [10] Evolution of regional to global paddy rice mapping methods: A review
    Dong, Jinwei
    Xiao, Xiangming
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2016, 119 : 214 - 227