Detailed mapping of riparian vegetation in the middle Rio Grande River using high resolution multi-spectral airborne remote sensing

O. Z. Akasheh, C. M.U. Neale, H. Jayanthi

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

This paper describes procedures used to map riparian vegetation in the middle Rio Grande River, New Mexico. Airborne multi-spectral digital images were acquired at 0.5 m spatial resolution over the riparian corridor of the Middle Rio Grande River in July 2001. The images were corrected for lens vignetting effects, lens radial distortions, rectified to a base map, mosaicked, calibrated in terms of reflectance and classified. The classification accuracy was assessed using ground truth information obtained through comprehensive field campaigns and independent ground truth information. Surface areas of vegetation classes and in-stream features were extracted from the classified imagery. A longitudinal vegetation distribution analysis was conducted to study the changes in vegetation and water surface areas along the river. This analysis showed an increase in surface areas of the invasive type of vegetation Tamarisk (Tamarix ramosissima) in the downstream direction corresponding to decreases in water surface areas and flow. This indicates significant impacts on the river ecosystem due to many factors. The high resolution airborne remote sensing proved to be a powerful tool for mapping riparian vegetation which is very hard to map using satellite imagery due to its complexity, high diversity, and spatial variability occurring at finer scales.

Original languageEnglish (US)
Pages (from-to)1734-1744
Number of pages11
JournalJournal of Arid Environments
Volume72
Issue number9
DOIs
StatePublished - Sep 2008
Externally publishedYes

Keywords

  • Airborne multi-spectral digital imagery
  • Cottonwood
  • Rio Grande River
  • Riparian vegetation
  • Tamarisk

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Earth-Surface Processes

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