Abstract
Optical remote sensing indices play an important role in vegetation information extraction and have been widely serving ecology, agriculture and forestry, urban monitoring, and other communities. Remote sensing indices are constructed from individual bands depending on special characteristics to enhance the typical spectral features for the identification or distinction of surface land covers. With the development of quantitative remote sensing, there is a rapid increasing requirement for accurate data processing and modeling. It is well known that the geometry-induced variation observed in surface reflectance is not ignorable, but the situation of uncertainty thereby introduced into these indices still needs further detailed understanding. We adopted the ground multi-angle hyperspectrum, spectral response function (SRF) of Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+), Operational Land Imager (OLI), Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multi-Spectral Instrument (MSI) optical sensors and simulated their sensor-like spectral reflectance; then, we investigated the potential angle effect uncertainty on optical indices that have been frequently involved in vegetation monitoring and examined the forward/backward effect over both the ground-based level and the actual Landsat TM/ETM+ overlapped region. Our results on the discussed indices and sensors show as following: (1) Identifiable angle effects exist with a more elevated influence than that introduced by band difference among sensors; (2) The absolute difference between forward and backward direction can reach up to −0.03 to 0.1 within bands of the TM/ETM+ overlapped region; (3) The investigation at ground level indicates that there are different variations of angle effect transmitted to each remote sensing index. Regarding cases of crop canopy at various growth phases, most of the discussed indices have more than a 20% relative difference to nadir value except Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) with the magnitude lower than 10%, and less than 16% of Normalized Burn Ratio (NBR). For the case of wax maturity stage, the relative difference to nadir value of Enhanced Vegetation Index (EVI), Soil-Adjusted Vegetation Index (SAVI), Ratio Vegetation Index (RVI), Char Soil Index (CSI), NBR, Normalized Difference Moisture Index (NDMI), and SWIR2/NIR exceeded 50%, while the values for NBR and NDMI can reach up to 115.8% and 206.7%, respectively; (4) Various schemes of index construction imply different propagation of angle effect uncertainty. The “difference” indices can partially suppress the directional influence, while the “ratio” indices show high potential to amplify the angle effect. This study reveals that the angle-induced uncertainty of these indices is greater than that induced by the spectrum mismatch among sensors, especially under the case of senescence. In addition, based on this work, indices with a suppressed potential of angle effect are recommended for vegetation monitoring or information retrieval to avoid unexpected effects.
Highlights
Optical remote sensing indices play an important role in the information extraction and dynamic monitoring processes of land surface vegetation and have been widely utilized by ecology, agriculture and forestry, urban monitoring, and other communities.The visible and near-infrared (NIR) bands contained in optical remote sensing are frequently used for distinguishing the vegetation features of land covers
This work investigated the potential uncertainty of angle effects on optical indices using directional sensor-like multi-band reflectance simulated from ground hyperspectrum data and top-of-atmosphere (TOA) measurements collected by adjacent Landsat Thematic Mapper (TM)/ETM+
Sensor-like directional data were simulated from ground multi-angle hyperspectral observations for TM, ETM+, Operational Land Imager (OLI), Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multi-Spectral Instrument (MSI) optical sensors, and used to calculate 12 typical indices that have been frequently serving for vegetation monitoring
Summary
Optical remote sensing indices play an important role in the information extraction and dynamic monitoring processes of land surface vegetation and have been widely utilized by ecology, agriculture and forestry, urban monitoring, and other communities. The visible and near-infrared (NIR) bands contained in optical remote sensing are frequently used for distinguishing the vegetation features of land covers. Hyperspectrum with nanometer spectral resolution has the potential to capture the distinct absorption and reflection characteristics over rocks [1], minerals, and impervious surfaces [2], and as well the weak fluorescence effect of vegetation [3], and the eutrophication components existing in water bodies [4].It contributes significantly to improving our understanding of ground spectral features, albeit with a high cost of money and labor, while satellite-based remote sensing has an innate advantage serving for regional surface monitoring due to its high performance/price ratio, objectivity, timeliness, regular revisits, and spatial extended observation. The pioneer studies have contributed efforts to construct indices via ratios or spectral band differences, such as the Ratio Vegetation Index (RVI) [5], Difference Vegetation Index (DVI) [6], and Normalized Difference Vegetation
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