Bhuiyan, C., 2004. various droughts for monitoring drought condition in Aravalli terrain of India. In Proceedings of the XXth ISPRS Conference.Int. Soc. Photogramm. Remote Sensing, Istanbul.
Cammalleria, C., Verger, A.R., Lacazec, R. & Vogta, J.V., 2019. Harmonization of GEOV2 fAPAR time series through MODIS data for global drought monitoring. International Journal of Applied Earth Observation and Geoinformation, 80, 1-12.
Caccamo, A., Majumder, S., Richardson, A., Strong, R. & Oddo, S., 2011. Molecular interplay between mammalian target of rapamycin (mTOR), amyloid-b, and Tau: effects on cognitive impairments. Journal of Biological Chemistry, 285, 13107-1320.
Funk, C. & Budd, M.E., 2009. Phenologically-Tuned MODIS NDVI-based production nomaly estimates for Zimbabwe. Remote Sensing of Environment, 113 p.
Garcia-Leon, D., Contrerasc, S. & Huninkc, J., 2019. Comparison of meteorological and satellite-based drought indices as yield predictors of Spanish cereals. Agricultural Water Managemen, 213, 388-396.
Gouveia, C., Trigo, R.M. & DaCamra, C.C., 2009. Drought and vegetation stress monitoring in Portugal using satellite data. Natural Hazards and Earth System Sciences, 9(1), 185-195.
Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X. & Ferreira, L.G., 2002. Remote Sensing for Natural Resources Management and Enviromental Monitoring: Manual of remote sensing3 ed. V. 4, Univercity of Arizona.
Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X. & Ferreira, L.G., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices.
Remote Sensing of Environment,
83(1–2), 195-213.
IPCC, 2007. Climate change- synthesis report. Fourth Assessment Report of the Intergovernmental Panel of Climate Change. Rome.
JIE, Z., Mu, Q. & Hu, J., 2016. Assessing the remotely sensed Drought Severity Index for agricultural drought monitoring and impact analysis in North China. Ecological Indicators, 63, 296-309.
Kogan, F.N., 1990. Remote sensing of weather impacts on vegetation in non-homogeneous areas. International Journal of Remote Sensing, 11(8), 1405-1419.
Kogan, F.N., 2001. Operational space technology for global vegetation assessment. Bulletin of the American Meterological Society. 82(9), 64-1949.
Kogan, F.N., 2002. World droughts in the new millenium from AVHRR-based Vegetation Health Indices. Eos Transaction of American Geophysical Union, 83(48), 562-563.
Liu, C.L. & Wu, J.J., 2008. Crop drought monitoring using MODIS NDVI over Mid- Territory of China.
International Geosciense and Remote Sensing Symposium. DOI:
10.1109/IGARSS.2008.4779491.
Martha, C.A., Cornelio, A.Z., pol, C.S.,
Christopher, R.H., Kathryn, S.
M., Tugrul, Y.
F.,
Jason, A.O. &
Robert, T., 2016. The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts,
Remote Sensing of Environment, 174, 82-99.
Rojas, O., Vrieling, A. & Rembold, F., 2011. Assessing drought probability for agricultural areas in Africa with coarse resolution remote sensing imagery.
Remote Sensing of Environment, 115, 343-52.
Rizqi, I., Bambang, H.T., Diar, S., La Ode, S.I., Selamet, K.M. & Dyah, R.P., 2016. Identification of agricultural drought extent based on vegetation health indices of Landsat data: case of Subang and Karawang. Indonesia. Procedia Environmental Sciences,33, 14-20.
Rizky Auliaa, M., Liyantonoa Setiawanb, Y. & Fatikhunnadaa, A., 2016. Drought detection of West Java’s paddy field using MODIS EVI satellite images (case study: Rancaekek and Rancaekek Wetan). Procedia Environmental Sciences, 33, 646-653.
Sharma, A., 2006. Spatial data mining for drought monitoring: An approach using temporal NDVI and rainfall relationship. Thesis Geo- Information Science and Earth Observation, India.
Sruthi, S. & Mohammed Aslam, M.A., 2015. Agricultural Drought Analysis Using the NDVI and Land Surface Temperature Data; a Case Study of Raichur District. Aquatic Procedia, 4, 1258-1264.
Tallaksen, L.M. & Van Lanen, H.A., 2004. Hydrological drought: processes and estimation methods for streamflow and groundwater. Elsevier, 48, 22.
Thenkabail, P.S., Enclona, E.A., Ashton, M.S., Legg, C., Jean, D. & Dieu, M., 2004. The Use of Remote Sensing Data for Drought Assessment and Monitoring in Southwest Asia. International Water Management Institute, PO Box 2075, Colombo, Sri Lanka.
Vicente-Serrano, S.M., Cuadrat-Prats, J.M. & Romo, A., 2006. Early prediction of crop production using drought indices at different time-scales and remote sensing data: application in the Ebro valley (North-East Spain). International Journal of Remote Sensing, 27(3).
Vyas, S.S., Bhattacharya, B.K., Nigam, R., Guhathakurta, P., Ghosh, K., Chattopadhyay, N. & Gairola, R.M., 2015. 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, 39, 28-39.
Zhang, A. & Jia, G., 2013. Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data.
Remote Sensing of Environment, 134, 1223.