{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T08:05:31Z","timestamp":1768464331988,"version":"3.49.0"},"reference-count":32,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T00:00:00Z","timestamp":1569196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Sudden short-term severe droughts have major impacts on ecosystem balance. Synoptic and replicable measurements from remotely sensed data are essential for calculating changes to land use\/cover caused by severe drought conditions. In the US, Texas experienced a particularly severe drought in 2011, which adversely affected forest and grassland ecosystems in addition to $7.62 billion of agricultural loss. To assess the extent and severity of the drought we use satellite sensor data and image processing techniques to measure changes in land use\/cover. Our methodology uses change vector analysis (CVA), the normalized difference vegetation index, the normalized difference moisture index, and three variables-brightness, greenness, and wetness-extracted from tasseled cap transforms (TCT). All are established techniques in remote sensing but have as yet been applied in combination to measure land use\/cover changes affected by intense short-term drought conditions. Our objective is to calculate not only vegetation and bare soil indices, but also the intensity of change (magnitude) and the type of change (direction). For CVA direction, we include an improved methodology using the arctangent function based on two arguments, ATAN2 which produces results in all four possible quadrants, and complete characterization of all possible change directions. The three variables of TCT are applied to CVA magnitude and direction using vectors in three dimensions, resulting in eight change categories. Our results are based on Landsat TM sensor data for the years 2009, 2010 and 2011, which represent a short period of severe drought, above average precipitation, and severe drought respectively, for two study sites in Texas. Results indicate that land use\/cover changes were affected by both an increase in precipitation in 2010 as well as a considerable decrease of precipitation in 2011 resulting in the devastating sudden drought.<\/jats:p>","DOI":"10.3390\/rs11192217","type":"journal-article","created":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T11:02:00Z","timestamp":1569236520000},"page":"2217","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Change Vector Analysis, Tasseled Cap, and NDVI-NDMI for Measuring Land Use\/Cover Changes Caused by a Sudden Short-Term Severe Drought: 2011 Texas Event"],"prefix":"10.3390","volume":"11","author":[{"given":"Shoumik","family":"Rahman","sequence":"first","affiliation":[{"name":"Department of Geography, Florida State University, Tallahassee, FL 32306, USA"}]},{"given":"Victor","family":"Mesev","sequence":"additional","affiliation":[{"name":"Department of Geography, Florida State University, Tallahassee, FL 32306, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,23]]},"reference":[{"key":"ref_1","unstructured":"Combs, S. (2012). The Impact of the 2011 Drought and Beyond, Texas Comptroller of Public Accounts."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.jhydrol.2011.03.049","article-title":"Drought modeling\u2014A review","volume":"403","author":"Mishra","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1175\/BAMS-D-11-00213.1","article-title":"A remotely sensed global terrestrial drought severity index","volume":"94","author":"Mu","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_4","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_5","doi-asserted-by":"crossref","unstructured":"Ahmadi, B., Ahmadalipour, A., Tootle, G., and Moradkhani, H. (2019). Remote sensing of water use efficiency and terrestrial drought recovery across the contiguous United States. Remote Sens., 11.","DOI":"10.3390\/rs11060731"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1038\/nature23021","article-title":"Global patterns of drought recovery","volume":"548","author":"Schwalm","year":"2017","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"014016","DOI":"10.1088\/1748-9326\/aa5258","article-title":"Global gross primary productivity and water use efficiency changes under drought stress","volume":"12","author":"Yu","year":"2017","journal-title":"Environ. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1080\/0143116042000298252","article-title":"Hyperspherical direction cosine change vector analysis","volume":"26","author":"Warner","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/s10661-007-0031-6","article-title":"Change vector analysis to categorise land cover change processes using the tasseled cap as biophysical indicator","volume":"145","author":"Siwe","year":"2008","journal-title":"Environ. Monit. Assess."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2473","DOI":"10.3390\/rs3112473","article-title":"A new approach to change vector analysis using distance and similarity measures","volume":"3","author":"Carvalho","year":"2011","journal-title":"Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.rse.2004.10.012","article-title":"Comparison of time series tasseled cap wetness and the normalized difference moisture index in detecting forest disturbances","volume":"94","author":"Jin","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5951","DOI":"10.1007\/s10661-014-3831-5","article-title":"A change vector analysis technique for monitoring land cover changes in Copsa Mica, Romania, in the period 1985\u20132011","volume":"186","author":"Vorovencii","year":"2014","journal-title":"Environ. Monit. Assess."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1672\/0277-5212(2007)27[610:CDOWEU]2.0.CO;2","article-title":"Change detection of wetland ecosystems using Landsat imagery and change vector analysis","volume":"27","author":"Baker","year":"2007","journal-title":"Wetlands"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.1080\/01431160110075532","article-title":"Monitoring land-use change in the Pearl River Delta using Landsat TM","volume":"23","author":"Seto","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1080\/2150704X.2012.699201","article-title":"MODIS-based change vector analysis for assessing wetland dynamics in Southern Africa","volume":"4","author":"Landmann","year":"2013","journal-title":"Remote Sens. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"369","DOI":"10.14358\/PERS.69.4.369","article-title":"Land-use\/land-cover change detection using improved change-vector analysis","volume":"69","author":"Chen","year":"2003","journal-title":"Photogram. Engin. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2104","DOI":"10.1016\/j.rse.2007.07.027","article-title":"Spatial and temporal patterns of gap dominance by low-canopy lianas detected using EO-1 Hyperion and Landsat Thematic Mapper","volume":"112","author":"Foster","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.rse.2005.05.009","article-title":"Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection","volume":"97","author":"Healey","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1080\/0143116032000160462","article-title":"Comparative performance of a modified change vector analysis in forest change detection","volume":"26","author":"Nackaerts","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1080\/01431160600868482","article-title":"Sensitivity of change vector analysis to land cover change in an arid ecosystem","volume":"28","author":"Flores","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1080\/014311698216062","article-title":"Change vector analysis: A technique for the multispectral monitoring of land cover and condition","volume":"19","author":"Johnson","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"9316","DOI":"10.3390\/rs6109316","article-title":"Spatio-temporal dynamics of land-use and land-cover in the Mu Us Sandy Land, China, using the change vector analysis technique","volume":"6","author":"Karnieli","year":"2014","journal-title":"Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.rse.2007.03.010","article-title":"Trajectory-based change detection for automated characterization of forest disturbance dynamics","volume":"110","author":"Kennedy","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"729","DOI":"10.5194\/nhess-10-729-2010","article-title":"Using remote sensing to assess tsunami-induced impacts on coastal forest ecosystems at the Andaman Sea coast of Thailand","volume":"10","author":"Roemer","year":"2010","journal-title":"Nat. Hazards Earth Sys. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1007\/s10661-009-0798-8","article-title":"Comparison of remote sensing change detection techniques for assessing hurricane damage to forests","volume":"162","author":"Wang","year":"2010","journal-title":"Environ. Monit. Assess."},{"key":"ref_26","first-page":"8","article-title":"A change vector analysis technique to monitor land use\/land cover in SW Brazilian amazon: Acre State","volume":"34","author":"Lorena","year":"2002","journal-title":"ISPRS Arch."},{"key":"ref_27","unstructured":"Mesev, V. (2007). Remote sensing and GIS for ephemeral wetland monitoring and sustainability in southern Mauritania. Integration of GIS and Remote Sensing, Wiley & Sons."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"236","DOI":"10.14429\/dsj.62.1072","article-title":"Change vector analysis using enhanced PCA and inverse triangular function-based thresholding","volume":"62","author":"Baisantry","year":"2012","journal-title":"Def. Sci. J."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1109\/LGRS.2006.887066","article-title":"An efficient protocol to process Landsat images for change detection with tasseled cap transformation","volume":"4","author":"Han","year":"2007","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1080\/01431161.2011.648281","article-title":"Median change vector analysis algorithm for land-use land-cover change detection from remote-sensing data","volume":"3","author":"Varshney","year":"2012","journal-title":"Remote Sens. Lett."},{"key":"ref_31","unstructured":"Yoon, G.-W., Yun, Y.B., and Park, J.-H. (2003, January 21\u201325). Change vector analysis: Detecting of areas associated with flood using Landsat TM. Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, Tolouse, France."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.isprsjprs.2018.09.006","article-title":"A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies","volume":"146","author":"Yang","year":"2018","journal-title":"ISPRS J. Photogram. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/19\/2217\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:23:09Z","timestamp":1760188989000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/19\/2217"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,23]]},"references-count":32,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["rs11192217"],"URL":"https:\/\/doi.org\/10.3390\/rs11192217","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,23]]}}}