The Role of Lower Plants in Remote Sensing of Arid Lands Vegetation

Project Number: 
Project Duration: 
41 Months
May 1, 1994 to September 30, 1997
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

The effect of biogenic crust on imagery acquired by spaceborne sensors is demonstrated in Chapter 1 of the final report. The crust consists mostly of microphytes such as cyanobacteria. The macrophytes (higher vegetation) on the sand dunes are sparse and have a relatively low spectral reflectance response. However, since a considerable portion of the ground is covered by this biogenic crust (which has a different spectral reflectance from that of the mobile sands) a sharp brightness contrast is created between the two areas. It is concluded that the well-known contrast between Sinai (Egypt) and the Negev (Israel) that has long drawn the attention of many observers, is not a direct result of vegetation cover but is caused by an almost complete cover of biogenic crust in the Negev, and a lack of this crust in Sinai, largely due to man's activities.

Identification of cyanobacterial soil crusts is important for mapping apparently barren soils. Chapter 2 presents a diagnostic tool for the identification of cyanophyte within soil crusts by means of in vivo reflectance spectrophotometry measurements. Spectral reflectance spectra of the crust samples were measured under several conditions - dry, after wetting, after their phycobilin pigments had been removed, and after the crust had been immersed in paraffin oil. Differences in the reflectance were enhanced by calculating ratio spectra. It is shown that relative higher reflectivity of the crust in the blue region is caused due to the spectral characteristics of the phycobilins. This work is a first step towards mapping biogenic crusts by using airborne or spaceborne sensors which have the capability to detect in the blue band.

The Normalized Difference Vegetation Index (NDVI) which is derived from satellite sensor images is widely used as a measure of vegetation and ecosystem dynamics, change in land use, desertification, and climatic change processes on a regional or global scale. Surprisingly, in semi-arid regions, relatively high values of NDVI were measured in landscapes where little, if any photosynthetic activity of higher plants exists. In Chapter 3 we tested the hypothesis that the high NDVI values may be caused by the photosynthetic activity of microphytes (lower plants), consisting of mosses, lichens, algae, and cyanobacteria, which cover most of the rock and soil surfaces in semi-arid regions. We found that the spectral reflectance curves of lower plants can be similar to those of the higher ones and their derived NDVI values can be as high as 0.30 units. We conclude that in semi-arid environments, the reflectance of lower plant communities may lead to misinterpretation of the vegetation dynamics and overestimation of ecosystem productivity.

Advantage is taken of a unique spectral feature of soil biogenic crust containing cyanobacteria. Chapter 4 shows that the special phycobilin pigment in cyanobacteria contributes in producing a relatively higher reflectance in the blue spectral region than the same type of substrate without the biogenic crust. A spectral crust index (CI) has been developed, based on the normalized difference between the RED and the BLUE spectral values: CI = 1 - (RED - BLUE)(RED + BLUE). Applying the index to a sand dune environment, it has been shown that the CI can be used to detect and to map, from remote sensing imagery, different lithologic/morphologic units such as active sands, crusted interdune areas and playas, which are expressed in the topography. As a mapping tool the CI image is much more sensitive to the ground features than the original image. The absence, existence, and distribution of soil crust are an important source of information for desertification and climate change studies. They also provide highly valuable information for developing agricultural regions and/or infrastructures in arid environments since soil crusts contribute to soil stability, soil build-up, soil fertility, and to the soil water regime. The application of the proposed CI can be performed with imagery acquired by any sensor which contains the blue band. Currently, the most common data courses are color aerial photographs and Landsat-TM images as demonstrated in this paper. However, CI should be applicable to other sensors such as the SPOT-VEGETATION, MOMS-2P, Sea WiFS and MODIS which will be available in the coming years.

Large areas of sand fields in arid and semi-arid regions are covered by cyanobacteria soil crusts. The objective of Chapter 5 is to analyze (systematically throughout the VIS, NIR and the SWIR regions of the spectrum) the unique spectral features of cyanobacteria crust relative to bare sands and under different moisture conditions. It was found that: (1) When biogenic soil crusts are wet, their NDVI value can reach 30% due to their photosynthetic activity; (2) The closer the red edge inflection point is to the longer wavelengths, the higher the relative abundance and distribution of the microphytic community; (3) The phycobilin pigments, which are unique to cyanobacteria, contribute to higher reflectance in the blue region relative to the sand substrate. A crust index based on this uncommon spectral feature can be useful for detecting and mapping, from remote sensing imagery, different lithologic/morphologic units; (4) Although most dune sand areas are generally made of quartz, other notable features appear on their spectra. In the study area, there are absorption features representing the minerals (iron oxides at 860 nm, and clay minerals at 220 nm) and biogenic crusts (chlorophyll at 670 nm and organic matter at 1720, 2180 and 2309 nm).

In Chapter 6, the optical properties of various microphytic crusts (mosses, lichens, cyanobacteria) were examined in dry and wet conditions and at nadir view as well as over a range of viewing angles at the principal plane. In an attempt to decouple the soil background influence on the normalized difference vegetation index (NDVI) from the photosynthetic signal, additional VIs were employed, including the first derivative spectral index, soil-adjusted vegetation index (SAVI) and the perpendicular vegetation index (PVI). All crusts demonstrated increased photosynthetic activity upon wetting with the cyanobacteria showing the weakest VI signal while the moss crust showed the highest VI response. All indices had some soil-related problems which warranted caution in VI interpretation. All indices also had significant and dissimilar anisotropy behavior and view angle variations in VI responses exceeded, at times, those variations associated with wetting of the crust surface. This demonstrates the need to be cautious in proper interpretation of the wide swath view data from the AVHRR sensor satellite system.


Articles in Journals

De Oliveira-Accioly L.J. and A.R. Huete. 2000. "Soil spectral response in relation to viewing angle, soil moisture and surface roughness." Pesquisa Agropecuaria Brasileira 35(12):2473-2484.

Qi, J., Y.H. Kerr, M.S. Moran, M. Weltz and A.R. Huete, A. Sorooshian, S. and R. Bryant. 2000. "Leaf area index estimates using remotely sensed data and BRDF models in a semiarid region. Remote Sensing of Environment 73(1):18-30.

Yoshioka H., A.R. Huete and T. Miura. 2000. "Derivation of vegetation isoline equations in red-NIR reflectance space." IEEE Transactions on Geoscience and Remote Sensing 38(2):838-848.

Yoshioka, H., T. Miura, A.R. Huete and B. Ganapol. 2000, "Analysis of vegetation isolines in red-NIR reflectance space." Remote Sensing of Environment 74(2):313-326.

Sano E.E., A.R. Huete, D. Troufleau, M.S. Moran and A. Vidal. 1998. "Relation between ERS-1 synthetic aperture radar data and measurements of surface roughness and moisture content of rocky soils in a semiarid rangeland." Water Resources Research 34(6):1491-1498.

van Leeuwen, W.J.D., A.R. Huete, C.L. Walthall, S.D Prince, A. Bégué and J.L. Roujean. 1997. "Deconvolution of remotely sensed spectral mixtures for retrieval of LAI, fAPAR and soil Brightness." Journal of Hydrology 189(1-4):697-724.

Begue, A., J.L. Roujean, N.P. Hanan, S.D. Prince, M. Thawley, A.R. Huete,  and D. Tanré. 1996. "Shortwave radiation budget of Sahelian vegetation during HAPEX-Sahel - 1. Techniques of measurement and results." Agric. and Forest Meteorology 79:79-96.


Huete, A. R. 1996. "Soil radiative transfer influences in satellite monitoring of vegetation." In Elements of change, eds. S. J. Hassol and J. Katzenberger, 1995, Aspen Global Change Institute.


Miura, T., H. Yoshioka and A.R. Huete. 2000. "On the statistical nature of NDVI and SAVI variations induced by canopy background brightness." Poster, Second International Conference on Geospatial Information in Agriculture and Forestry, ERIM, January. Lake Buena Vista FL.


Support for this project came from the USDA Cooperative State Research, Education, and Extension Service