An automated approach to map winter cropped area of smallholder farms across large scales using MODIS imagery

Remote Sensing

Volumn 9, Issue 6, 2017, Pages

  Jain, Meha ^a   Mondal, Pinki ^b   Galford, Gillian L ^c   Fiske, Greg ^d   DeFries, Ruth S ^e  

^a UNIVERSITY OF MICHIGAN   (United States)

^b Earth Institute   (United States)

^c UNIVERSITY OF VERMONT   (United States)

^d WOODS HOLE RESEARCH CENTER   (United States)

^e Howard Hughes Medical Institute   (United States)

Author keywords

Agriculture; Cropped area; India; MODIS; Remote sensing

Indexed keywords

AGRICULTURE; AUTOMATION; BIOLOGY; CALIBRATION; COMPLEX NETWORKS; CROPS; CULTIVATION; INFORMATION SERVICES; NASA; PIXELS; REMOTE SENSING;

AGRICULTURAL PRODUCTIONS; CROPPED AREA; ENHANCED VEGETATION INDEX; HIGH RESOLUTION IMAGERY; INDIA; INFORMATION NETWORKS; MODIS; SPATIAL AND TEMPORAL SCALE;

RADIOMETERS;

EID: 85021103812     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9060566     Document Type: Article

References (37)

1. DeFries, R.; Mondal, P.; Singh, D.; Agrawal, I.; Fanzo, J.; Remans, R.; Wood, S. Synergies and trade-offs for sustainable agriculture: Nutritional yields and climate-resilience for cereal crops in Central India. Glob. Food Secur. 2016, 11, 44-53
2. Fishman, R. More uneven distributions overturn benefits of higher precipitation for crop yields. Environ. Res. Lett. 2016, 11, 024004
3. Lobell, D.B.; Schlenker, W.; Costa-Roberts, J. Climate trends and global crop production since 1980. Science 2011, 333, 616-620
4. Godfray, H.C.J.; Beddington, J.R.; Crute, I.R.; Haddad, L.; Lawrence, D.; Muir, J.F.; Pretty, J.; Robinson, S.; Thomas, S.M.; Toulmin, C. Food security: The challenge of feeding 9 billion people. Science 2010, 327, 812-818
5. Ray, D.K.; Ramankutty, N.; Mueller, N.D.;West, P.C.; Foley, J.A. Recent patterns of crop yield growth and stagnation. Nat. Commun. 2012, 3, 1293
6. Shanahan, J.F.; Schepers, J.S.; Francis, D.D.; Varvel, G.E.; Wilhelm, W.W.; Tringe, J.M.; Schlemmer, M.R.; Major, D.J. Use of remote-sensing imagery to estimate corn grain yield. Agron. J. 2001, 93, 583-589
7. Quarmby, N.A.; Milnes, M.; Hindle, T.L.; Silleos, N. The use of multi-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction. Int. J. Remote Sens. 1993, 14, 199-210
8. Doraiswamy, P.C.; Sinclair, T.R.; Hollinger, S.; Akhmedov, B.; Stern, A.; Prueger, J. Application of MODIS derived parameters for regional crop yield assessment. Remote Sens. Environ. 2005, 97, 192-202
9. Wardlow, B.D.; Egbert, S.L. Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains. Remote Sens. Environ. 2008, 112, 1096-1116
10. Morton, J.F. The impact of climate change on smallholder and subsistence agriculture. Proc. Natl. Acad. Sci. USA 2007, 104, 19680-19685
11. Jain, M.; Mondal, P.; DeFries, R.S.; Small, C.; Galford, G.L. Mapping cropping intensity of smallholder farms: A comparison of methods using multiple sensors. Remote Sens. Environ. 2013, 134, 210-213
12. Jain, M.; Srivastava, A.K.; Balwinder-Singh; Joon, R.K.; McDonald, A.; Royal, K.; Lisaius, M.C.; Lobell, D.B. Mapping smallholder wheat yields and sowing dates using micro-satellite data. Remote Sens. 2016, 8, 860
13. Carletto, C.; Jolliffe, D.; Banerjee, R. The Emperor Has No Data! Agricultural Statistics in Sub-Saharan Africa; World BankWorking Paper;World Bank: Washington, DC, USA, 2013. Available online: http://mortenjerven. com/wp-content/uploads/2013/04/Panel-3-Carletto.pdf (accessed on 7 January 2016)
14. Whitcraft, A.K.; Vermote, E.F.; Becker-Reshef, I.; Justice, C.O. Cloud cover throughout the agricultural growing season: Impacts on passive optical earth observations. Remote Sens. Environ. 2015, 156, 438-447
15. Biradar, C.M.; Xiao, X. Quantifying the area and spatial distribution of double-and triple-cropping croplands in India with multi-temporal MODIS imagery in 2005. Int. J. Remote Sens. 2011, 32, 367-386
16. Spera, S.A.; Cohn, A.S.; VanWey, L.K. Recent cropping frequency, expansion, and abandonment in Mato Grosso, Brazil had selective land characteristics. Environ. Res. Lett. 2014, 9, 064010
17. Lesk, C.; Rowhani, P.; Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 2016, 529, 84-87
18. Gajbhiye, K.S.; Mandal, C. Agro-Ecological Zones, Their Soil Resource and Cropping Systems; National Bureau of Soil Survey and Land Use Planning: Nagpur, India, 2000. Available online: http://www.indiawaterportal. org/sites/indiawaterportal.org/files/01jan00sfm1.pdf (accessed on 11 December 2016)
19. Chand, R.; Lakshmi Prasanna, P.A.; Singh, A. Farm size and productivity: Understanding the strengths of smallholders and improving their livelihoods. Econ. Political Wkly. 2011, 46, 5-11
20. Lobell, D.B.; Burke, M.B.; Tebaldi, C.; Mastrandrea, M.D.; Falcon, W.P.; Naylor, R.L. Prioritizing climate change adaptation needs for food security in 2030. Science 2008, 319, 607-610
21. Mall, R.K.; Singh, R.; Gupta, A.; Srinivasan, G.; Rathore, L.S. Impact of climate change on Indian agriculture: A review. Clim. Chang. 2006, 78, 445-478
22. Erenstein, O.; Thorpe, W. Livelihoods and agro-ecological gradients: A meso-level analysis in the Indo-Gangetic Plains, India. Agric. Syst. 2011, 104, 42-53
23. Jain, M.; Naeem, S.; Orlove, B.; Modi, V.; DeFries, R.S. Understanding the causes and consequences of differential decision-making in adaptation research: Adapting to a delayed monsoon onset in Gujarat, India. Glob. Environ. Chang. 2015, 31, 98-109
24. Wardlow, B.; Egbert, S.; Kastens, J. Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains. Remote Sens. Environ. 2007, 108, 290-310
25. Sakamoto, T.;Wardlow, B.D.; Gitelson, A.A.; Verma, S.B.; Suyker, A.E.; Arkebauer, T.J. A Two-step filtering approach for detecting maize and soybean phenology with time-series MODIS data. Remote Sens. Environ. 2010, 114, 2146-2159
26. National Food Security Mission Crop Calendar of NFSM Crops. Available online: http://nfsm.gov.in/nfmis/RPT/CalenderReport.aspx (accessed on 10 January 2017)
27. Xiao, X.; Boles, S.; Liu, J.; Zhuang, D.; Frolking, S.; Li, C.; Salas, W.; Moore, B., III. Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sens. Environ. 2005, 95, 480-492
28. Ren, J.; Chen, Z.; Zhou, Q.; Tang, H. Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China. Int. J. Appl. Earth Obs. Geoinf. 2008, 10, 403-413
29. Becker-Reshef, I.; Vermote, E.; Lindeman, M.; Justice, C. A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data. Remote Sens. Environ. 2010, 114, 1312-1323
30. O'Brien, K.; Leichenko, R.; Kelkar, U.; Venema, H.; Aandahl, G.; Tompkins, H.; Javed, A.; Bhadwal, S.; Barg, S.; Nygaard, L.; et al. Mapping vulnerability to multiple stressors: Climate change and globalization in India. Glob. Environ. Chang. 2004, 14, 303-313
31. Shah, T. Crop per drop of diesel? Energy squeeze on India's smallholder irrigation. Econ. Political Wkly. 2007, 42, 4002-4009
32. Division, A.I. DistrictWise Land Use Statistics. Available online: http://aps.dac.gov.in/APY/Index.htm (accessed on 10 January 2017)
33. Directorate of Economics and Statistics Area Production Yield Dataset-District 2016. Available online: http://aps.dac.gov.in/APY/Public_Report1.aspx (accessed on 1 September 2016)
34. Duncan, J.M.A.; Dash, J.; Atkinson, P.M. Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing. Glob. Chang. Biol. 2014, 21, 1541-1551
35. Xiao, X.; Boles, S.; Frolking, S.; Li, C.; Babu, J.Y.; Salas, W.; Moore, B., III. Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images. Remote Sens. Environ. 2006, 100, 95-113
36. Lobell, D.B.; Thau, D.; Seifert, C.; Engle, E.; Little, B. A scalable satellite-based crop yield mapper. Remote Sens. Environ. 2015, 164, 324-333
37. Planet Team. Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA, 2017. Available online: https://api.planet.com (accessed on 1 February 2017)