Remote Sensing Techniques Specific to Vegetation Detection in Arid Regions

Project Number: 
Project Duration: 
39 Months
May 15, 1998 to August 14, 2001
Institution of Principle Investigator while on this project: 
University of Arizona

Investigators (most current known information)

Professor, Soil, Water, & Environmental Sciences, The University of Arizona, Shantz 430, Tucson AZ 85721
TEL: +1-520-621-3228, FAX: +1-520-621-1647, Email:
Head, Remote Sensing Laboratory, Remote Sensing Laboratory, Ben-Gurion University of the Negev, Sede J. Blaustein Institute for Desert Research, Sede Boker Campus 84990, ISRAEL
TEL: +972-8-659-6855, FAX: +972-8-659-6704, Email:
Professor, Ben-Gurion University of the Negev, Mitrani Center for Desert Ecology, Institute for Desert Research, Sede Boqer 84990, ISRAEL
TEL: +972-8-659-6786, FAX: +972-8-659-6772, Email:

Proposal Abstract

Arid ecosystems are characterized by strong spatial and temporal variability mainly due to the scarcity of water. The need for long-term and widespread collection of data to monitor the state of arid vegetation can be readily implemented by remote sensing techniques. Remote sensing enables long-term studies at relatively low costs and the above-ground, synoptic views reach vast and remote areas that may be inaccessible because of morphological or political reasons. It enables us to monitor seasonal and inter- annual changes related to land cover and various biophysical properties, including leaf area index (LAI), fraction of absorbed photosynthetically-active radiation (fAPAR), and net primary production (NPP). In this study we analyzed some of the opportunities and limitations in remote sensing monitoring of arid and semi-arid environments. Our goal was to establish and develop a quantitative basis for optimizing vegetation index (VI) performance in arid and semiarid regions. Vegetation indices are one of the more important products in monitoring temporal and spatial variations of vegetation canopy biophysical parameters and arid regions generally are very dynamic in vegetation activity with rapid green-up and growing season periods.

Multi-scale satellite, aircraft, and ground-measured reflectances were collected over several arid regions, including the Negev and Sinai deserts (Israel, Egypt), Sonoran and Chihuahuan deserts (Arizona, New Mexico), and arid Mongolia. This effort was to assess the usefulness and performance of remote sensing and spectral vegetation indices and thermal bands in arid lands from high and low-resolution satellite sensors such as the AVHRR, MODIS, and ETM+. We were able to couple the ground- and aircraft-based measurements with those from the satellite and found that all of the sites fell onto a common VI - biophysical parameter regression line with most deviations attributed to the proportion of senesced plant material and shrub contents. The usefulness of combining NDVI and land surface temperature (LST) data was demonstrated using the NOAA-AVHRR sensor over the Negev (Israel) and Sinai (Egypt) deserts. The two areas were identical from pedology and climatic points of view, however they exhibited different land management uses with the Negev under continuous rehabilitation process while the Sinai is undergoing desertification.. The NDVI was used to monitor vegetation reactions to rainfall, while LST proved to be a good indicator of seasonal climatic fluctuations. Within the LST-NDVI space it was shown that the Sinai was positioned similar to the Sahara biome and the Negev similar to the Sahel biome. The NDVI-rainfall relationship was also a sensitive indicator of rainfall inter-annual variability.

We approached the optimization of vegetation indices by employing both the atmosphere resistance and first order background-canopy corrections. A new vegetation index called the weighted average soil adjusted vegetation index (WASAVI) was developed and effectively minimized both canopy background and atmospheric influences on the VI. This index uses multiple SAVI-like indices to minimize canopy background and atmospheric influences. These are demonstrated in this final report and are the focus of continuing studies and development.


Articles in Journals

Gao, X., A.R. Huete and K. Didan. 2003. "Multisensor comparisons and validation of MODIS vegetation indices at the semiarid Jornada experimental range." IEEE Transactions on Geoscience and Remote Sensing 41(10):2368-2381.

Huete, A.R., T. Miura, X. Gao. 2003. "Land cover conversion and degradation analyses through coupled soil-plant biophysical parameters derived from hyperspectral EO-1 Hyperion." IEEE Transactions on Geoscience and Remote Sensing 41(6):1268-1276.

Yoshioka H., T. Miura. and A.R. Huete. 2003. "An isoline-based translation technique of spectral vegetation index using EO-1 Hyperion data." IEEE Transactions on Geoscience and Remote Sensing 41(6):1363-1372.

Zamora-Arroyo. F., P.L. Nagler, M. Briggs, D. Radtke, H. Rodriquez, J. Garcia, C. Valdez, A.R. Huete and E. Glenn. 2001. "Regeneration of native trees in response to flood releases from the United States into the delta of the Colorado River, Mexico." Journal of Arid Environments 49(1):49-64.


Huete, A.R. 2004. "Remote sensing of soils and soil processes." In Remote Sensing for Natural Resources Management and Environmental Monitoring: Manual of Remote Sensing, ed. S. Ustin, 3 edition, Chapter 1:1-48. John Wiley & Sons, Inc.


Huete, A.R., X. Gao, H.H. Kim, T. Miura, C. Borghi R. and Ojeda. 2002. "Characterization of land degradation in central Argentina with hyperspectral AVIRIS and EO-1 data." In Proceedings of the 17th World Congress of Soil Science, Bangkok, 987:1-8. 14-21 August. Thailand.

Huete, A.R., T. Miura, X. Gao, C. Borghi and R. Ojeda. 2002. "Characterization of land degradation at the Ñacuñán and Chancani reserves in Argentina with AVIRIS and EO-1 hyperion data." In Proceedings 2002 AVIRIS earth science and applications workshop. March. Pasadena CA.

Huete, A.R., X. Gao, T. Miura, R. Ross Bryant, S. Moran and C. Holifield. 2002. "Multiple scale analyses of land degradation at the Nacuñan reserve, Argentina with hyperspectral EO-1 and MODIS data." In Proceedings 29th international symposium on remote sensing of environment, 633-636, April. Buenos Aires, Argentina.

Rodriguez, E. P., K. Didan, A.R. Huete and T. Miura. 2002. "Application of MODIS vegetation indices to monitor the seasonal responses and water use impacts over the Colorado delta area, NW Mexico." In Proceedings 29th international symposium on remote sensing of environment, April. Buenos Aires, Argentina.

Rodriguez, E.P., A.R. Huete, D. Schaub, K. Didan, T. Miura, E. Glenn and P. Nagler. 2002, "Application of MODIS vegetation indices to monitor seasonal responses and water use impacts over the Colorado River delta area, Mexico." Poster, MODIS Outreach on MODIS Vegetation Variables (VI/LAI/FPAR/NPP), July. University of Montana, Missoula MT.

Huete, A.R., X. Gao, G. Asner, H.J. Kim and T. Miura. 2001. "Characterization of vegetation conditions at the Nacunan and Chancani reserves in Argentina with ground- air- and EO-1 Hyperion Data." In Proceedings IEEE international geoscience and remote sensing symposium, July. Sydney, Australia.


Support for this project came from the USDA Forest Service