A combined deficit index for regional agricultural drought assessment over semi-arid tract of India using geostationary meteorological satellite data

International Journal of Applied Earth Observation and Geoinformation

Volumn 39, Issue , 2015, Pages 28-39

  Vyas, Swapnil S ^a,c   Bhattacharya, Bimal K ^a   Nigam, Rahul ^a   Guhathakurta, Pulak ^b   Ghosh, Kripan ^b   Chattopadhyay, N ^b   Gairola, R M ^a  

^a Indian Space Research Organization Space Application Centre   (India)

^b Ministry of Earth Sciences   (India)

^c NIRMA UNIVERSITY   (India)

Author keywords

Agricultural drought; Geostationary; INSAT products; Satellite meteorology

Indexed keywords

DROUGHT; GEOSTATIONARY SATELLITE; MONSOON; PRECIPITATION (CLIMATOLOGY); RAINFALL; RAINGAUGE; SATELLITE DATA; SEMIARID REGION; WATER SUPPLY;

INDIA;

EID: 84943527909     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2015.02.009     Document Type: Article

References (55)

1. Anon, 2010. Annual Report. 2009-10. Department of Agriculture & Co-cooperation, Ministry of Agriculture, Government of India, 1-3, (www.agricoop.nic.in).
2. Anon, 2012. Southwest Monsoon, End-of-season report, India Meteorological Department, 1-14, (www.imd.gov.in).
3. Anon, 2013. State of Indian Agriculture 2012-13. Department of Agriculture & Co-cooperation, Ministry of Agriculture, Government of India, 1-4, (www.agricoop.nic.in).
4. Agarwal, S., Joshi, P.K., Shukla, Y., Roy, P.S., 2003. SPOT VEGETATION multi temporal data for classifying vegetation in South central Asia. Curr. Sci. 84 (11), 1440-1448.
5. Anyamba, A., Tucker, C., 2005. Analysis of Sahelian vegetation dynamics using NOAA VHRR NDVI data from 1981 to 2003. J. Arid Environ. 63, 596-614.
6. Bajgirana, P., Darvishsefat, A., Khalilic, A., Makhdoumd, M., 2008. Using AVHRR-based vegetation indices for drought monitoring in the Northwest of Iran. J. Arid Environ. 72, 1086-1096.
7. Bhattacharya, B.K., Nigam, R., Dorjee, N., Panigrahy, S., 2008. Normalized Difference Vegetation Index-Towards development of operational products from INSAT 3A CCD data. In: National Symposium on Advances in Remote Sensing Technology and Applications with Special Emphasis on Microwave Remote Sensing, Ahmedabad, 18-20 December. 2008.
8. Bhattacharya, B.K., Mallick, K., Patel, N.K., Parihar, J.S., 2010. Regional clear sky evapotranspiration over agricultural land using remote sensing data from Indian geostationary meteorological satellite. J. Hydrol. 387, 65-80.
9. Brown, J.F., Wardlow, B.D., Tadesse, T., Hayes, M.J., Reed, B.C., 2008. The vegetation drought response index (VegDRI): a new integrated approach for monitoring drought stress in vegetation. GIS Sci. Remote Sens. 45 (1), 16-46.
10. Chandrasekar, K., SeshaSai, M.V.R., Jeyaseelan, A.T., Dwivedi, R.S., Roy, P.S., 2006. Vegetation response to rainfall as monitored by NOAA-AVHRR. Curr. Sci. 91, 1626-1633.
11. Chandrasekar, K., SeshaSai, M.V.R., Roy, P.S., Dwevedi, R.S., 2010. Land surface water index (LSWI) response to rainfall and NDVI using the MODIS vegetation index product. Int. J. Remote Sens. 31 (15), 3987-4005.
12. Damizadeh, M., Saghafian, B., Gieske, A., 2001. Studying vegetation responses and rainfall relationship based-on NOAA/AVHRR images. In: 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November 2001.
13. Drobne, S., Lisec, A., 2009. Multi-attribute decision analysis in GIS: weighted linear combination and ordered weighted averaging. Informatica 33, 459-474.
14. Du, L., Tian, Q., Meng, Q., Jancso, T., Udvardy, P., Huang, Y., 2013. A comprehensive drought monitoring method intigrating MODIS and TRMM data. Int. J. Appl. Earth Obs. Geoinf. 23, 245-253.
15. Farrar, T.J., Nicholson, S.E., Lare, A.R., 1994. The influnce of soil type on the relationship between NDVI, rainfall and soil moisture in semi-arid Bostwana: II. NDVI response to soil. Remote Sens. Environ. 50, 121-133.
16. Ghosh, S.P., 1991. Agro-Climatic Zone Specific Research, Indian Perspective under N.A.R.P. Indian Council of Agricultural Research: New Delhi. 11-15.
17. Guhathakurta, P., Koppar, A.L., Krishnan, U., Menon, P., 2011. New rainfall series for the district, meteorological sub-divisions and country as whole of India. National Climate Center Research Report No. 2/2011 (www.imdpune.gov.in).
18. Guttman, N.B., 1999. Accepting the Standardized Precipitation Index: a calculation algorithm. J. Am. Water Res. Assoc. 35, 311-322.
19. Ji, L., Peters, A.J., 2003. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices. Remote Sens. Environ. 87, 85-98.
20. Karnieli, A., Agam, N., Pinker, R.T., Anderson, M., Imhoff, M.L., Gutman, G.G., Panov, N., Goldberg, A., 2009. Use of NDVI and land surface temperature for drought assessment: merits and limitations. J. Clim. 23, 618-633.
21. Kogan, F.N., 1997. Global drought watch from space. Bull. Am. Meteorol. Soc. 78 (4), 621-636.
22. Kogan, F.N., 2001. Operational space technology for global vegetation assessment. Bull. Am. Meteorol. Soc. 82, 1949-1964.
23. Liu, W., Kogan, F., 1996. Monitoring regional drought using the Vegetation Condition Index. Int. J. Remote Sens. 17 (14), 2761-2782.
24. Loew, A., 2008. Impact of surface heterogeneity on surface soil moisture retrievals from passive microwave data at the regional scale: the Upper Danube case. Remote Sens. Environ. 112, 231-248.
25. Mallick, K., Bhattacharya, B.K., Patel, N.K., 2009a. Estimating volumetric surface moisture content in cropped soils using a soil wetness index based on surface temperature and NDVI. Agric. Forest Meteorol. 137, 1327-1342.
26. Mallick, K., Bhattacharya, B.K., Raji Reddy, D., Banerjee, S., Venkatesh, H., Pandey, V., Mukherjee, J., Vyas, S.P., Gadgil, A.S., Patel, N.K., 2009b. Latent heat flux estimation in clear sky days over Indian agroecosystems using noontime satellite remote sensing data. Agric. Forest Meteorol. 149, 1646-1665.
27. Mckee, T.B., Doesken, J., Kleist, J., 1993. The relationship of drought frequency and duration to time scales. In: Proceedings of Eighth Conference on Applied Climatology, Anaheim, CA, American Meteorological Society, Boston, MA, pp. 179-184.
28. Monteith, J.L., 1965. Evaporation and the environment. In: the state and movement of water in living organisms. In: Nineteenth Symposium of the Society for Experimental Biology. Cambridge University Press, Swansea, UK, pp. 205-234.
29. Monteith, J., 1977. Climate and efficiency of crop production in Britain. Philos. Trans. R. Soc. London, Ser. B, 277-294.
30. Moran, M.S., Kustas, W.P., Vidal, A., Stannard, D.I., Blanford, J.H., Nichols, W.D., 1994. Use of ground-based remotely sensed data for surface energy balance evaluationof a semiarid rangeland. Water Resour. Res. 30 (5), 1339-1350.
31. Mu, Q., Heinsch, F.A., Zhao, M., Running, S.W., 2007a. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sens. Environ. 111, 519-536.
32. Nagarajan, R., 2009. Management and Resource Conservation, Drought: Assessment, Monitoring, Capital Publishing Company, New Delhi, ISBN: 8185589119, p. 312.
33. Nigam, R., Bhattacharya, B.K., Gunjal, R.K., Padmanabhan, N., Patel, N.K., 2011. A continental scale vegetation index from Indian geostationary satellite. Curr. Sci. 10 (100), 1184-1192.
34. Nigam, R., Bhattacharya, B.K., Gunjal, R.K., Padmanabhan, N., Patel, N.K., 2012. Formulation of time series vegetation index from Indian geostationary satellite and comparison with global products. J. Indian Soc. Remote Sens. 40 (1), 1-9.
35. Peters, A.J., Walter-Shea, E.A., Lei, J., Vina, A., Hayes, M., Svoboda, M.R., 2002. Drought monitoring with NDVI-based standardized vegetation index. Photogramm. Eng. Remote Sens. 68, 71-75.
36. Persendt, F.C., 2009. Drought risk assessment using remote sensing and GIS to alleviate poverty. A case study of the Oshikoto region in Namibia. In: Conference on Applied Geoinformatics for Society and Environment (AGSE), Stuttgart University of Applied Sciences, Germany, pp. 20-21, August.
37. Prakash, S., Mahesh, C., Gairola, R.M., Pal, P.K., 2010. Estimation of Indian summer monsoon rainfall using Kalpana-1 VHRR data and its validation using rain gauge and GPCP data. Meteorol. Atmos. Phys. 110, 45-57.
38. Rahimzadeh, P.B., Shimizu y. Hosoi, F., Omasa, K., 2009. MODIS vegetation and water indices for drought assessment in semi-arid ecosystem of Iran. J. Agric. Meteorol. 65 (4), 349-355.
39. Rajeevan, M., Pai, D.S., Rohilla, A.K., 2005. New statistical models for long-range forecasting of southwest monsoon rainfall over India, National Climate Center Research Report No. 2/2006.
40. Rhee, J., Im, J., Carbone, G.J., 2010. Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sens. Environ. 114, 2875-2887.
41. Rossi, S., Niemeyer, S., 2012. Dought monitoring with estimates of the fraction absorbed photosynthetically-active radiation (fAPAR) derived from MERIS. In: Wardlow, B., Anderson, M., Verdin, J. (Eds.), Remote Sensing for Drought Innovative Monitoring Approaches. CRC Press-Taylor & Francis, Boca Raton, FL, USA, pp. 95-116.
42. Roerink, G.J., Su, Z., Menenti, M., 2000. S-SEBI: a simple remote sensing algorithm to estimate the surface energy balance. Phys. Chem. Earth 25, 147-157.
43. Running, S.W., Thornton, P.E., Nemani, R., Glassy, J.M., 2000. Global terrestrial gross and net primary productivity from the Earth Observing System. In: Sala, O.E., Jackson, R.B., Mooney, H.A., Howarth, R.W. (Eds.), Methods in Ecosystem Science. Springer, New York, pp. 44-57.
44. Sepulcre-Canto, G., Horion, S., Singleton, A., Carrao Vogt, J., 2012. Development of Combined Drought Indicator to detect agricultural drought in Europe. Nat. Hazards Earth Syst. Sci. 12, 3519-3531.
45. Singh, S.K., Bhattacharya, B.K., Kulkarni, A., 2013. A Cross calibration of INSAT 3A CCD channel radiance with IRS P6 AWiFS sensor. J. Earth Syst. Sci. 122 (4), 957-966.
46. Thenkabail, P., Gamage, M., Smakhtin, V., 2004. Use of remote sensing data for drought assessment and monitoring in Southwest Asia. In: Technical Report 85. International Water Management Institute (IWMI).
47. Tucker, C.J., 1979. Red and photographic infrared linear combination for monitoring vegetation. Remote Sens. Environ. 8, 127-150.
48. Tucker, C., Choudhury, B., 1987. Satellite remote sensing of drought conditions. Remote Sens. Environ. 23, 243-251.
49. Udelhoven, T., Stellmes, M., del Barrio, G., Hill, J., 2009. Assessment of rainfall and NDVI anomalies in Spain (1989-1999) using distributed lag models. Int. J. Remote Sens. 30 (8), 1961-1976.
50. Vittal, K.P.R., Rao, K.V., Sharma, K.L., Victor, U.S., Chary, G.R., Sarkar, G.R.M., 2005. Guidelines for Rainfed Production System and Management. In: Drought Management, Sharma, K.D., Ramasashtri, K.S. (Eds.). India: Allied Publisher Private Limited, pp. 76-106.
51. Wan, Z., Wang, P., Li, X., 2004. Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in southern Great Plains, USA. Int. J. Remote Sens. 26, 61-72.
52. Wang, J., Price, K.P., Rich, P.M., 2001. Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains. Int. J. Remote Sens. 22, 3827-3844.
53. Wang, P., Wen, X., Gong, J., Song, C., 2004. Vegetation temperature condition index and its application for drought monitoring. Proc. IGRASS 2001 (1), 141-143.
54. Wilhite, D., 2005. Drrought and water crisis: science, technology and management issues. In: Drought as Hazard: Understanding the Natural and Social Context. CRC Press, Taylor and Francis Group, New York, pp. 3-29.
55. Zhang, A., Jia, G., 2013. Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data. Remote Sens. Environ. 134, 12-23.