{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T10:59:06Z","timestamp":1781521146308,"version":"3.54.1"},"reference-count":84,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T00:00:00Z","timestamp":1595980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["108-2111-M-008 -036 -MY2"],"award-info":[{"award-number":["108-2111-M-008 -036 -MY2"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["108-2923-M-008 -002 -MY3"],"award-info":[{"award-number":["108-2923-M-008 -002 -MY3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed with R = 0.66 (p value = 0.05). Based on VCI for the same two years (2001 and 2008), 84% and 72% of the country were subject to drought conditions, respectively. Coherently, TRMM data confirm that 2001 and 2008 were the least rainfall years of 108 and 251 mm, respectively. On the other hand, years 2009 and 2010 were registered with the largest vegetation coverage of 16.3% mainly due to lower annual LST than average LST of 14 degrees and partially due to their slightly higher annual rainfalls of 378 and 425 mm, respectively, than the historical average of 327 mm. Based on the derived VCI, 28% and 21% of the study area experienced drought conditions in 2009 and 2010, respectively. It is also found that correlations are relatively high between NDVI and VCI (r = 0.77, p = 0.0002), but slightly lower between NDVI and precipitation (r = 0.51, p = 0.03). In addition, LST played a key role in influencing the value of NDVI. However, both LST and precipitation must be considered together in order to properly capture the correlation between drought and NDVI.<\/jats:p>","DOI":"10.3390\/rs12152433","type":"journal-article","created":{"date-parts":[[2020,7,30]],"date-time":"2020-07-30T03:36:38Z","timestamp":1596080198000},"page":"2433","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":101,"title":["Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3694-6936","authenticated-orcid":false,"given":"Iman","family":"Rousta","sequence":"first","affiliation":[{"name":"Department of Geography, Yazd University, Yazd 8915818411, Iran"},{"name":"Institute for Atmospheric Sciences-Weather and Climate, University of Iceland and Icelandic Meteorological Office (IMO), Bustadavegur 7, IS-108 Reykjavik, Iceland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haraldur","family":"Olafsson","sequence":"additional","affiliation":[{"name":"Institute for Atmospheric Sciences-Weather and Climate, Department of Physics, University of Iceland and Icelandic Meteorological Office (IMO), Bustadavegur 7, IS-108 Reykjavik, Iceland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5139-6434","authenticated-orcid":false,"given":"Md","family":"Moniruzzaman","sequence":"additional","affiliation":[{"name":"Center for Space Science and Technology in Asia and the Pacific (CSSTEAP), Dehradun 248001, India"},{"name":"ASICT Division, Bangladesh Agricultural Research Institute, Gazipur 1701, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Engineering Jiangwan campus, Fudan University, 2005 Songhu Road, Yangpu, Shanghai 200438, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8100-5529","authenticated-orcid":false,"given":"Yuei-An","family":"Liou","sequence":"additional","affiliation":[{"name":"Center for Space and Remote Sensing Research (CSRSR), National Central University (NCU), Taoyuan 32001, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Terence Darlington","family":"Mushore","sequence":"additional","affiliation":[{"name":"Department of Physics, Faculty of Science, University of Zimbabwe, MP167 Mt Pleasant, Harare 00263, Zimbabwe"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amitesh","family":"Gupta","sequence":"additional","affiliation":[{"name":"Indian Institute of Remote Sensing, ISRO, Dehradun 248001, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,29]]},"reference":[{"key":"ref_1","first-page":"289","article-title":"Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data","volume":"8","author":"Bhuiyan","year":"2006","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1007\/s13753-013-0008-8","article-title":"Evaluation of the visible and shortwave infrared drought index in China","volume":"4","author":"Zhang","year":"2013","journal-title":"Int. J. Disaster Risk Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Rousta, I., Nasserzadeh, M., Jalali, M., Haghighi, E., \u00d3lafsson, H., Ashrafi, S., Doostkamian, M., and Ghasemi, A. (2017). Decadal spatial-temporal variations in the spatial pattern of anomalies of extreme precipitation thresholds (case study: Northwest iran). Atmosphere, 8.","DOI":"10.3390\/atmos8080135"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Dorjsuren, M., Liou, Y.-A., and Cheng, C.-H. (2016). Time series MODIS and in situ data analysis for Mongolia drought. Remote Sens., 8.","DOI":"10.3390\/rs8060509"},{"key":"ref_5","first-page":"520","article-title":"The use of soil and water resources at the Mediterranean region in Turkey","volume":"26","author":"Denli","year":"2017","journal-title":"Fresenius Environ. Bull."},{"key":"ref_6","unstructured":"Rousta, I., Doostkamian, M., Olafsson, H., Ghafarian-Malamiri, H., Zhang, H., Taherian, A., Sarif, M., Gupta, R., and Monroy-Vargas, E. (2019). On the relationship between the 500 hPa height fluctuations and the atmosphere thickness over Iran and the Middle East. TETHYS-J. Mediterr. Meteorol. Climatol., 3\u201314."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2018\/6941501","article-title":"Investigation of vorticity during prevalent winter precipitation in Iran","volume":"2018","author":"Rousta","year":"2018","journal-title":"Adv. Meteorol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E. (1976). A Land Use and Land Cover Classification System for Use with Remote Sensor Data.","DOI":"10.3133\/pp964"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2006GL029127","article-title":"A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States","volume":"34","author":"Gu","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"703","DOI":"10.2307\/3235884","article-title":"Measuring phenological variability from satellite imagery","volume":"5","author":"Reed","year":"1994","journal-title":"J. Veg. Sci."},{"key":"ref_11","first-page":"71","article-title":"Drought monitoring with NDVI-based standardized vegetation index","volume":"68","author":"Peters","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_12","unstructured":"Rousta, I., Khosh Akhlagh, F., Soltani, M., and Modir Taheri, S.S. (2014, January 28\u201331). Assessment of blocking effects on rainfall in northwestern Iran. Proceedings of the COMECAP 2014, Heraklion Crete, Greece."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s40333-017-0014-6","article-title":"A remote sensing-based agricultural drought indicator and its implementation over a semi-arid region, Jordan","volume":"9","author":"Hazaymeh","year":"2017","journal-title":"J. Arid Land"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"17149","DOI":"10.3390\/rs71215879","article-title":"A regional land use drought index for Florida","volume":"7","author":"Cheng","year":"2015","journal-title":"Remote Sens."},{"key":"ref_15","first-page":"53","article-title":"Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI)","volume":"18","author":"Dutta","year":"2015","journal-title":"Egypt. J. Remote Sens. Space Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Liou, Y.-A., and Mulualem, G.M. (2019). Spatio\u2013temporal Assessment of Drought in Ethiopia and the Impact of Recent Intense Droughts. Remote Sens., 11.","DOI":"10.3390\/rs11151828"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1002\/2014RG000456","article-title":"Remote sensing of drought: Progress, challenges and opportunities","volume":"53","author":"AghaKouchak","year":"2015","journal-title":"Rev. Geophys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1002\/joc.4847","article-title":"A global classification of vegetation based on NDVI, rainfall and temperature","volume":"37","author":"Zhang","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"28","DOI":"10.2307\/1942049","article-title":"Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types","volume":"5","author":"Gamon","year":"1995","journal-title":"Ecol. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Drori, R., Dan, H., Sprintsin, M., and Sheffer, E. (2020). Precipitation-Sensitive Dynamic Threshold: A New and Simple Method to Detect and Monitor Forest and Woody Vegetation Cover in Sub-Humid to Arid Areas. Remote Sens., 12.","DOI":"10.3390\/rs12081231"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"134585","DOI":"10.1016\/j.scitotenv.2019.134585","article-title":"Monitoring drought using composite drought indices based on remote sensing","volume":"711","author":"Liu","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_22","unstructured":"Rouse, J., Haas, R., Schelle, J., Deering, D., and Harlan, J. (1974). Monitoring the Vernal Advancement or Retrogradation of Natural Vegetation, Texas University Press. NASA\/GSFCType IIIFinal Report Green-BeltMD."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1175\/1520-0469(1998)055<1225:SSDASP>2.0.CO;2","article-title":"Satellite-sensed distribution and spatial patterns of vegetation parameters over a tallgrass prairie","volume":"55","author":"Chen","year":"1998","journal-title":"J. Atmos. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/0034-4257(95)00039-4","article-title":"Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data","volume":"52","author":"Gao","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1175\/1520-0477(1995)076<0655:DOTLIT>2.0.CO;2","article-title":"Droughts of the late 1980s in the United States as derived from NOAA polar-orbiting satellite data","volume":"76","author":"Kogan","year":"1995","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0034-4257(98)00012-1","article-title":"An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the US northern and central Great Plains","volume":"65","author":"Yang","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0034-4257(03)00174-3","article-title":"Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices","volume":"87","author":"Ji","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/0143116031000115328","article-title":"Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA","volume":"25","author":"Wan","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ghafarian Malamiri, H., Rousta, I., Olafsson, H., Zare, H., and Zhang, H. (2018). Gap-Filling of MODIS Time Series Land Surface Temperature (LST) Products Using Singular Spectrum Analysis (SSA). Atmosphere, 9.","DOI":"10.3390\/atmos9090334"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1080\/10106040008542161","article-title":"The effects of climatic factors on vegetation dynamics of tallgrass and shortgrass cover","volume":"15","author":"Rundquist","year":"2000","journal-title":"GeoCarto Int."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3827","DOI":"10.1080\/01431160010007033","article-title":"Spatial patterns of NDVI in response to precipitation and temperature in the central Great Plains","volume":"22","author":"Wang","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.14358\/PERS.71.9.1053","article-title":"Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation","volume":"71","author":"Ji","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2761","DOI":"10.1080\/01431169608949106","article-title":"Monitoring regional drought using the vegetation condition index","volume":"17","author":"Liu","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2325","DOI":"10.1080\/01431160500034235","article-title":"Modelling corn production in China using AVHRR-based vegetation health indices","volume":"26","author":"Kogan","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/01431160701271974","article-title":"Using vegetation health indices and partial least squares method for estimation of corn yield","volume":"29","author":"Salazar","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"5201","DOI":"10.1080\/01431160600567787","article-title":"Compared regimes of NDVI and rainfall in semi-arid regions of Africa","volume":"27","author":"Martiny","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.atmosres.2010.11.006","article-title":"Calibration of TRMM rainfall climatology over Saudi Arabia during 1998\u20132009","volume":"99","author":"Almazroui","year":"2011","journal-title":"Atmos. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.rse.2006.11.011","article-title":"Use of TRMM in determining the climatic characteristics of rainfall over Bangladesh","volume":"108","author":"Islam","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_40","first-page":"165","article-title":"Validation of a TRMM-based global Flood Detection System in Bangladesh","volume":"13","author":"Moffitt","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1007\/s40808-020-00751-8","article-title":"The 2000\u20132017 Drought risk Assessment of the Western and Southwestern Basins in Iran","volume":"6","author":"Rousta","year":"2020","journal-title":"Modeling Earth Syst. Environ."},{"key":"ref_42","first-page":"245","article-title":"A comprehensive drought monitoring method integrating MODIS and TRMM data","volume":"23","author":"Du","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1353\/sais.2015.0000","article-title":"Flower of war: An environmental history of opium poppy in Afghanistan","volume":"35","author":"Parenti","year":"2015","journal-title":"SAIS Rev. Int. Aff."},{"key":"ref_44","unstructured":"Price, R. (2019). Climate change as a driver of conflict in Afghanistan and other Fragile and Conflict Affected States, Institute of Development Studies."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Snetkov, A. (2013). The Regional Dimensions to Security: Other Sides of Afghanistan, Springer.","DOI":"10.1057\/9781137330055"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1080\/13504500109470086","article-title":"Afghanistan: Environmental degradation in a fragile ecological setting","volume":"8","author":"Saba","year":"2001","journal-title":"Int. J. Sustain. Dev. World Ecol."},{"key":"ref_47","unstructured":"Savage, M., Dougherty, B., Hamza, M., Butterfield, R., and Bharwani, S. (2009). Socio-Economic Impacts of Climate Change in Afghanistan, Stockholm Environment Institute Press."},{"key":"ref_48","first-page":"205","article-title":"Zum Klima und Wasserhaushalt des Hindukuschs und der benachbarten Hochgebirge (The Climate and Water-Budget of the Hindu Kush and Neighbouring Mountain Ranges)","volume":"3","author":"Flohn","year":"1969","journal-title":"Erdkunde"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1127\/badr\/1\/2007\/155","article-title":"Flora and vegetation of Afghanistan","volume":"1","author":"Breckle","year":"2007","journal-title":"Basic Appl. Dryland Res."},{"key":"ref_50","first-page":"295","article-title":"Die W\u00e4lder von Nuristan und Paktia. Standortbedingungen und Nutzung der ostafghanischen Waldgebiete","volume":"2","author":"Rathjens","year":"1974","journal-title":"Geogr. Z."},{"key":"ref_51","unstructured":"McSweeney, C., New, M., and Lizcano, G. (2019, May 20). UNDP climate change country profiles: Afghanistan. Available online: https:\/\/www.geog.ox.ac.uk\/research\/climate\/projects\/undp-cp\/."},{"key":"ref_52","unstructured":"Kamal, G.M. (2004). River Basins and Watersheds of Afghanistan, Afghanistan Information Management Services (AIMS)."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Akhtar, F., Awan, U.K., Tischbein, B., and Liaqat, U.W. (2018). Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment\u2014A Case of Kabul River Basin, Afghanistan. Remote Sens., 10.","DOI":"10.20944\/preprints201804.0133.v1"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.pce.2017.06.002","article-title":"Scenario analysis of land use change in Kabul river basin\u2013a river basin with rapid socio-economic changes in Afghanistan","volume":"101","author":"Najmuddin","year":"2017","journal-title":"Phys. Chem. EarthParts A\/B\/C"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10669-013-9455-4","article-title":"Groundwater-level trends and implications for sustainable water use in the Kabul Basin, Afghanistan","volume":"33","author":"Mack","year":"2013","journal-title":"Environ. Syst. Decis."},{"key":"ref_56","first-page":"205","article-title":"Fragen der horizontalen und vertikalen Landschaftsgliederung in Hochgebirgessytem des Hindykusch","volume":"4","author":"Rathjens","year":"1972","journal-title":"Erdwiss. Forsch."},{"key":"ref_57","first-page":"1","article-title":"Watershed atlas of Afghanistan, working document for planners, parts I and II, 1st edn. Kabul: Government of Afghanistan, Ministry of Irrigation","volume":"60","author":"Favre","year":"2004","journal-title":"Water Resour. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1404","DOI":"10.1111\/j.1749-8198.2008.00154.x","article-title":"Applications of shuttle radar topography mission elevation data","volume":"2","author":"Zandbergen","year":"2008","journal-title":"Geogr. Compass"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2002GL016450","article-title":"Remote estimation of leaf area index and green leaf biomass in maize canopies","volume":"30","author":"Gitelson","year":"2003","journal-title":"Geophys. Res. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.1016\/j.rse.2009.04.016","article-title":"Vegetation dynamics from NDVI time series analysis using the wavelet transform","volume":"113","author":"Gilabert","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1154","DOI":"10.1175\/1520-0442(1997)010<1154:GSAOVP>2.0.CO;2","article-title":"Global-scale assessment of vegetation phenology using NOAA\/AVHRR satellite measurements","volume":"10","author":"Moulin","year":"1997","journal-title":"J. Clim."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.uclim.2018.12.006","article-title":"Remotely sensed retrieval of Local Climate Zones and their linkages to land surface temperature in Harare metropolitan city, Zimbabwe","volume":"27","author":"Mushore","year":"2019","journal-title":"Urban Clim."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/0034-4257(94)00063-S","article-title":"A remote sensing based vegetation classification logic for global land cover analysis","volume":"51","author":"Running","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/S0034-4257(00)00197-8","article-title":"Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density","volume":"76","author":"Broge","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_65","first-page":"309","article-title":"Monitoring vegetation systems in the Great Plains with ERTS","volume":"351","author":"Rouse","year":"1974","journal-title":"NASA Spec. Publ."},{"key":"ref_66","unstructured":"Didan, K. (2019, February 12). MOD13Q1 MODIS\/Terra Vegetation Indices 16-day L3 global 250 m SIN Grid V006. NASA EOSDIS Land Process. DAAC 2015, Available online: https:\/\/lpdaac.usgs.gov\/."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2012.12.002","article-title":"First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling\u2013calibration procedure","volume":"131","author":"Duan","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Deng, G., Zhang, H., Guo, X., and Ying, H. (2018, January 18\u201320). Assessment of Drought in Democratic People\u2019s Republic of Korea in 2017 Using TRMM Data. Proceedings of the 2018 Fifth International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Xi\u2019an, China.","DOI":"10.1109\/EORSA.2018.8598557"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2","article-title":"The tropical rainfall measuring mission (TRMM) sensor package","volume":"15","author":"Kummerow","year":"1998","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1007\/s12517-018-3487-5","article-title":"Determination and prediction of standardized precipitation index (SPI) using TRMM data in arid ecosystems","volume":"11","author":"Mossad","year":"2018","journal-title":"Arab. J. Geosci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.atmosres.2015.08.008","article-title":"Evaluation of the TRMM 3B43 gridded precipitation estimates over Greece","volume":"169","author":"Nastos","year":"2016","journal-title":"Atmos. Res."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1175\/1520-0477(1997)078<0005:TGPCPG>2.0.CO;2","article-title":"The global precipitation climatology project (GPCP) combined precipitation dataset","volume":"78","author":"Huffman","year":"1997","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_73","unstructured":"Huffman, G., Stocker, E., Bolvin, D., Nelkin, E., and Jackson, T. (2019, February 12). GPM IMERG Final Precipitation L3 Half Hourly 0.1 Degree \u00d7 0.1 Degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), Available online: https:\/\/disc.gsfc.nasa.gov\/datasets."},{"key":"ref_74","unstructured":"McKee, T.B., Doesken, N.J., and Kleist, J. (1993, January 17\u201322). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology, Anaheim, CA, USA."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1175\/1520-0493(1958)086<0117:ANOTGD>2.0.CO;2","article-title":"A note on the gamma distribution","volume":"86","author":"Thom","year":"1958","journal-title":"Mon. Weather Rev."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1007\/s11269-006-9062-y","article-title":"Drought forecasting using the standardized precipitation index","volume":"21","author":"Cancelliere","year":"2007","journal-title":"Water Resour. Manag."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1016\/j.aqpro.2015.02.162","article-title":"Drought index computation using standardized precipitation index (SPI) method for Surat District, Gujarat","volume":"4","author":"Shah","year":"2015","journal-title":"Aquat. Procedia"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/S0034-4257(97)00132-6","article-title":"Drought monitoring and corn yield estimation in Southern Africa from AVHRR data","volume":"63","author":"Unganai","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_79","unstructured":"Thenkabail, P.S., and Gamage, M. (2004). The Use of Remote Sensing Data for Drought Assessment and Monitoring in Southwest Asia, Iwmi."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"2653","DOI":"10.1080\/01431160802555788","article-title":"Identification of drought-vulnerable areas using NOAA AVHRR data","volume":"30","author":"Jain","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky\u2013Golay filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1109\/TPWRS.2004.835632","article-title":"Short-term load forecasting for the holidays using fuzzy linear regression method","volume":"20","author":"Song","year":"2005","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.rse.2014.04.008","article-title":"Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI","volume":"149","author":"Pervez","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_84","first-page":"2689","article-title":"Intra-seasonal Variation of Rainfall and Climate Characteristics in Kabul River Basin","volume":"3","author":"Shokory","year":"2017","journal-title":"Cent. Asian J. Water Res. (CAJWR) \u0426\u0435\u043d\u0442\u0440\u0430\u043b\u044c\u043d\u043e\u0430\u0437\u0438\u0430\u0442\u0441\u043a\u0438\u0439 \u0416\u0443\u0440\u043d\u0430\u043b \u0418\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0439 \u0412\u043e\u0434\u043d\u044b\u0445 \u0420\u0435\u0441\u0443\u0440\u0441\u043e\u0432"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/15\/2433\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:52:37Z","timestamp":1760176357000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/15\/2433"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,29]]},"references-count":84,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["rs12152433"],"URL":"https:\/\/doi.org\/10.3390\/rs12152433","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,29]]}}}