{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T20:49:07Z","timestamp":1778878147503,"version":"3.51.4"},"reference-count":30,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2020,4,12]],"date-time":"2020-04-12T00:00:00Z","timestamp":1586649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006245","name":"Ministry of Science and Technology, Israel","doi-asserted-by":"publisher","award":["62596"],"award-info":[{"award-number":["62596"]}],"id":[{"id":"10.13039\/501100006245","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote-sensing tools and satellite data are often used to map and monitor changes in vegetation cover in forests and other perennial woody vegetation. Large-scale vegetation mapping from remote sensing is usually based on the classification of its spectral properties by means of spectral Vegetation Indices (VIs) and a set of rules that define the connection between them and vegetation cover. However, observations show that, across a gradient of precipitation, similar values of VI can be found for different levels of vegetation cover as a result of concurrent changes in the leaf density (Leaf Area Index\u2014LAI) of plant canopies. Here we examine the three-way link between precipitation, vegetation cover, and LAI, with a focus on the dry range of precipitation in semi-arid to dry sub-humid zones, and propose a new and simple approach to delineate woody vegetation in these regions. By showing that the range of values of Normalized Difference Vegetation Index (NDVI) that represent woody vegetation changes along a gradient of precipitation, we propose a data-based dynamic lower threshold of NDVI that can be used to delineate woody vegetation from non-vegetated areas. This lower threshold changes with mean annual precipitation, ranging from less than 0.1 in semi-arid areas, to over 0.25 in mesic Mediterranean area. Validation results show that this precipitation-sensitive dynamic threshold provides a more accurate delineation of forests and other woody vegetation across the precipitation gradient, compared to the traditional constant threshold approach.<\/jats:p>","DOI":"10.3390\/rs12081231","type":"journal-article","created":{"date-parts":[[2020,4,13]],"date-time":"2020-04-13T10:41:52Z","timestamp":1586774512000},"page":"1231","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Precipitation-Sensitive Dynamic Threshold: A New and Simple Method to Detect and Monitor Forest and Woody Vegetation Cover in Sub-Humid to Arid Areas"],"prefix":"10.3390","volume":"12","author":[{"given":"Ron","family":"Drori","sequence":"first","affiliation":[{"name":"Institute of Plant Science and Genetic in Agriculture, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harel","family":"Dan","sequence":"additional","affiliation":[{"name":"The Steinhardt Museum of Natural History, Tel-Aviv University, Tel Aviv-Yafo 6997801, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Sprintsin","sequence":"additional","affiliation":[{"name":"Land Development Authority, Jewish National Fund-Keren Kayemet LeIsrael, Eshtaol, M.P. Shimshon 99775, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Efrat","family":"Sheffer","sequence":"additional","affiliation":[{"name":"Institute of Plant Science and Genetic in Agriculture, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1093\/jpe\/rtm005","article-title":"Remote sensing imagery in vegetation mapping: A review","volume":"1","author":"Xie","year":"2008","journal-title":"J. Plant Ecol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.tplants.2014.10.008","article-title":"Global satellite monitoring of climate-induced vegetation disturbances","volume":"20","author":"McDowell","year":"2015","journal-title":"Trends Plant Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-resolution global maps of 21st-century forest cover change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_4","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_5","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/S0034-4257(02)00078-0","article-title":"Global land cover mapping from MODIS: Algorithms and early results","volume":"83","author":"Friedl","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.rse.2007.01.010","article-title":"Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing","volume":"109","author":"Sonnentag","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.isprsjprs.2018.02.010","article-title":"Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data","volume":"139","author":"Higginbottom","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2004.02.003","article-title":"Land surface temperature retrieval from LANDSAT TM 5","volume":"90","author":"Sobrino","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the relation between NDVI, fractional vegetation cover, and leaf area index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/s40562-019-0132-4","article-title":"High-resolution calculation of the urban vegetation fraction in the Pearl River Delta from the Sentinel-2 NDVI for urban climate model parameterization","volume":"6","author":"Wong","year":"2019","journal-title":"Geosci. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.3390\/rs70302283","article-title":"Remote Sensing of Shrubland Drying in the South-East Mediterranean, 1995\u20132010: Water-Use-Efficiency-Based Mapping of Biomass Change","volume":"7","author":"Shoshany","year":"2015","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"893","DOI":"10.2307\/1936225","article-title":"Leaf Area of Mature Northwestern Coniferous Forests: Relation to Site Water Balance","volume":"58","author":"Grier","year":"1977","journal-title":"Ecology"},{"key":"ref_13","unstructured":"Woodward, F.I. (1987). Climate and Plant Distribution, Cambridge University Press."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1093\/oxfordjournals.aob.a083148","article-title":"Comparative Physiological Studies on the Growth of Field Crops: I. Variation in Net Assimilation Rate and Leaf Area between Species and Varieties, and within and between Years","volume":"11","author":"Watson","year":"1947","journal-title":"Ann. Bot."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/2017JG004105","article-title":"Estimation of Woody and Herbaceous Leaf Area Index in Sub-Saharan Africa Using MODIS Data","volume":"123","author":"Kahiu","year":"2018","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_16","unstructured":"Perelman, Y. (2012). Leaf Area Organization in Aleppo Pine Forests Depending on Abiotic Environment Factors. [Ph.D. Thesis, Hebrew University of Jerusalem (in Hebrew)]."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1038\/nature04070","article-title":"Determinants of woody cover in African savannas","volume":"438","author":"Sankaran","year":"2005","journal-title":"Nature"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gascon, F., Bouzinac, C., Th\u00e9paut, O., Jung, M., Francesconi, B., Louis, J., Lonjou, V., Lafrance, B., Massera, S., and Gaudel-Vacaresse, A. (2017). Copernicus Sentinel-2A Calibration and Products Validation Status. Remote Sens., 9.","DOI":"10.3390\/rs9060584"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1046\/j.1365-2699.1999.00153.x","article-title":"Estimating woody and herbaceous vegetation cover from time series satellite observations","volume":"8","author":"Roderick","year":"1999","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.foreco.2013.08.026","article-title":"Homogenization in forest performance across an environmental gradient\u2013The interplay between rainfall and topographic aspect","volume":"310","author":"Dorman","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_22","unstructured":"Drori, R., and Dan, H. (2015). Woody Vegetation Density Product User Guide (in Hebrew), Natural History Museum\/National Center for Biodiversity Research at Tel Aviv University. Available online: http:\/\/www.hamaarag.org.il\/file\/427\/download."},{"key":"ref_23","unstructured":"Drori, R. (2017). Technical Supplement for the 2016 State of Nature Report (in Hebrew), Natural History Museum\/National Center for Biodiversity Research at Tel Aviv University. Available online: http:\/\/www.hamaarag.org.il\/file\/1859\/download."},{"key":"ref_24","unstructured":"Goldreich, Y. (2012). The climate of Israel: Observation, Research and Application, Springer Science & Business Media."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"S56","DOI":"10.1016\/j.rse.2008.01.026","article-title":"PROSPECT+SAIL models: A review of use for vegetation characterization","volume":"113","author":"Jacquemoud","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.rse.2006.01.003","article-title":"Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction","volume":"101","author":"Jiang","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1126\/science.1179998","article-title":"Contribution of Semi-Arid Forests to the Climate System","volume":"327","author":"Rotenberg","year":"2010","journal-title":"Science"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/S0034-4257(98)00110-2","article-title":"Spectral Characteristics of Cyanobacteria Soil Crust in Semiarid Environments","volume":"69","author":"Karnieli","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1078\/0176-1617-01176","article-title":"Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical Characteristics of Vegetation","volume":"161","author":"Gitelson","year":"2004","journal-title":"J. Plant Physiol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/BF00036048","article-title":"The potential contribution of satellite remote sensing to the understanding of arid lands processes","volume":"91","author":"Verstraete","year":"1991","journal-title":"Vegetatio"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/8\/1231\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:30:38Z","timestamp":1760362238000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/8\/1231"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,12]]},"references-count":30,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["rs12081231"],"URL":"https:\/\/doi.org\/10.3390\/rs12081231","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,12]]}}}