Monitoring Vegetation Phenological Cycles in Two Different Semi-Arid Environmental Settings Using a Ground-Based NDVI System: A Potential Approach to Improve Satellite Data Interpretation

Abstract

Abstract:In semi-arid environmental settings with sparse canopy covers, obtaining remotely sensed information on soil and vegetative growth characteristics at finer spatial and temporal scales than most satellite platforms is crucial for validating and interpreting satellite data sets. In this study, we used a ground-based NDVI system to provide continuous time series analysis of individual shrub species and soil surface characteristics in two different semi-arid environmental settings located in the Great Basin (NV, USA). The NDVI system was a dual channel SKR-1800 radiometer that simultaneously measured incident solar radiation and upward reflectance in two broadband red and near-infrared channels comparable to Landsat-5 TM band 3 and band 4, respectively. The two study sites identified as Spring Valley 1 site (SV1) and Snake Valley 1 site (SNK1) were chosen for having different species composition, soil texture and percent canopy cover. NDVI time-series of greasewood (Sarcobatus vermiculatus) from the SV1 site allowed for clear distinction between the main phenological stages of the entire growing season during the period from January to November, 2007. NDVI time series values were significantly different between sagebrush (Artemisia tridentata) and rabbitbrush (Chrysothamnus viscidiflorus) at SV1 as well as between the two bare soil types at the two sites. Greasewood NDVI from the SNK1 site produced significant correlations with chlorophyll index (r = 0.97), leaf area index (r = 0.98) and leaf xylem water potential (r = 0.93). Whereas OPEN ACCESSRemote Sens. 2010, 2 991 greasewood NDVI from the SV1 site produced lower correlations (r = 0.89, r = 0.73), or non significant correlations (r = 0.32) with the same parameters, respectively. Total percent cover was estimated at 17.5% for SV1 and at 63% for SNK1. Results from this study indicated the potential capabilities of using this ground-based NDVI system to extract spatial and temporal details of soil and vegetation optical properties not possible with satellite derived NDVI.

Analysis and Mapping of the Spectral Characteristics of Fractional Green Cover in Saline Wetlands (NE Spain) Using Field and Remote Sensing Data

“…Vegetation in arid environments is characterized by open canopies with significant background (leaf litter, dead branches, shadows, and soil) making it difficult to isolate the green vegetation reflectance signal from the canopy background signal [34]. Mapping and estimating vegetation cover in arid areas at detailed scales is hindered by the sparsity of vegetation and the influence of soil background reflectance in the spectral data [15,17,[35][36][37][38][39].…”

Intercomparison of Seven NDVI Products over the United States and Mexico

“…Research has shown strong relationships between NDVI and biophysical properties such as leaf area index (LAI) [9], fraction of photosynthetically active radiation (fPAR) [10], areal vegetation fraction [11][12][13][14], net and gross primary productivity [15], chlorophyll abundance [16], and biomass [17]. It should be pointed out that areas not covered by vegetation may still show variations in NDVI due to atmospheric variations such as water vapor and aerosols, soil conditions as well as sensor characteristics [18].…”

Relation between Seasonally Detrended Shortwave Infrared Reflectance Data and Land Surface Moisture in Semi‑Arid Sahel

“…This is further supported by the in situ NDVI time series, where no straight forward relation between NDVI, either the maximum or the seasonal integral, is observed as compared to biomass e.g., the maximum NDVI values were observed on the year of lowest biomass production (2006), but the four years of data are insufficient for conclusions. Previous study using in situ data in a semi-arid environment has shown high temporal resolution NDVI to be able to distinguish between the same species exposed to different growing conditions, but for sites where the vegetation is dominated by the perennial Sarcobatus vermiculatus (greasewood) [62]. Therefore study into the extent that natural variation in species composition affects satellite based vegetation water indices and vegetation greenness indices, would provide some important perspectives for interpreting these indices for the Sahel.…”