Suitability of NDVI and OSAVI as estimators of green biomass and coverage in a semi-arid rangeland. (November 2018)

• Record Type: Journal Article
• Authors: Fern, Rachel R.; Foxley, Elliott A.; Bruno, Andrea; Morrison, Michael L.
• Is Part Of: Ecological indicators. Volume 94(2018)Part 1
• Page Start: 16
• Page End: 21
• Publication Date: 2018-11
• Subjects: Normalized Difference Vegetation Index -- Optimized Soil Adjusted Vegetation Index -- Semi-arid rangelands -- Green biomass -- Rangeland management; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2018.06.029
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: We assessed suitability of NDVI and OSAVI as biomass indicators in a semi-arid rangeland. We generated coverage estimates using VIs and traditional ground survey methods. We compared coverage estimates of herbaceous, woody, and bare vegetative classes across 2 years. OSAVI outperformed NDVI in both years for most vegetative classes. We argue OSAVI to be most appropriate VI-based estimator of green biomass in semi-arid rangelands. Abstract: Rangelands are often too large and inaccessible to determine biomass accumulation and vegetation cover by ground surveys alone, particularly in semi-arid regions where productivity per unit area is typically low and highly variable. Thus, the development of remote sensing derived spectral indices have been of particular interest to rangeland managers as a more cost-effective means of measuring the characteristics, biomass, and extent of vegetation. The Normalized Difference Vegetation Index (NDVI) is the most widely used spectral vegetation index (VI) by ecologists and agriculturalists today. However, regions with sparse vegetation or soils that generate high reflectance values (e.g., dry sandy soils) can severely hinder the reliability of the NDVI as an accurate estimator of green biomass, saturate remote sensors or produce biased estimates of green biomass and vegetative cover. The Optimized Soil Adjusted Vegetation Index (OSAVI) is a newly formed alternative that can accommodate greater variability due to high soil background values. We evaluated the suitability of the NDVI and OSAVI as potential estimators of green biomass and vegetative coverage in a semi-arid rangeland in south Texas. We compared coverage estimates of herbaceous, bare-ground, and woody vegetation calculated from classified satellite images stacked with either an NDVI or OSAVI band to those from traditional ground surveys. OSAVI-derived coverage estimates of herbaceous and woody vegetation did not significantly differ from those produced by ground surveys in 2015. However, NDVI-based estimates for woody vegetation, as well as bare ground, did differ significantly from estimates generated from ground surveys ( p = 0.012, 0.018). In 2016, the OSAVI-derived estimates for all three land cover classes were not significantly different than those produced by ground surveys. Our results suggest the OSAVI to be the most appropriate VI-based estimator of green biomass and vegetative coverage in the semi-arid regions of southern Texas.