Precipitation-sensitive dynamic threshold: A new and simple method to detect and monitor forest and woody vegetation cover in sub-humid to arid areas

Ron Drori*, Harel Dan, Michael Sprintsin, Efrat Sheffer

*Corresponding author for this work

Research output: Contribution to journalLetterpeer-review

9 Scopus citations


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 diαerent levels of vegetation cover as a result of concurrent changes in the leaf density (Leaf Area Index-LAI) 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 Diαerence 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.

Original languageAmerican English
Article number1231
JournalRemote Sensing
Issue number8
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020 by the authors.


  • Leaf area index
  • NDVI
  • Precipitation gradient
  • Rainfall
  • Semi-arid


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