Comparison of the Continuity of Vegetation Indices Derived from Landsat 8 OLI and Landsat 7 ETM+ Data among Different Vegetation Types

Abstract

Landsat 8, the most recently launched satellite of the series, promises to maintain the continuity of Landsat 7. However, in addition to subtle differences in sensor characteristics and vegetation index (VI) generation algorithms, VIs respond differently to the seasonality of the various types of vegetation cover. The purpose of this study was to elucidate the effects of these variations on VIs between Operational Land Imager (OLI) and Enhanced Thematic Mapper Plus (ETM+). Ground spectral data for vegetation were used to simulate the Landsat at-senor broadband reflectance, with consideration of sensor band-pass differences. Three band-geometric VIs (Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI)) and two band-transformation VIs (Vegetation Index based on the Universal Pattern Decomposition method (VIUPD), Tasseled Cap Transformation Greenness (TCG)) were tested to evaluate the performance of various VI generation algorithms in relation to multi-sensor continuity. Six vegetation types were included to evaluate the continuity in different vegetation types. Four pairs of data during four seasons were selected to evaluate continuity with respect to seasonal variation. The simulated data showed that OLI largely inherits the band-pass characteristics of ETM+. Overall, the continuity of band-transformation derived VIs was higher than OPEN ACCESSRemote Sens. 2015, 7 13486 band-geometry derived VIs. VI continuity was higher in the three forest types and the shrubs in the relatively rapid growth periods of summer and autumn, but lower for the other two non-forest types (grassland and crops) during the same periods.

Role of Climate Variability and Human Activity on Poopó Lake Droughts between 1990 and 2015 Assessed Using Remote Sensing Data

“…Regarding the OLI and ETM+, good radiometric compatibility was found between their respective bands [22] and can be used as complementary data [23]. OLI was found to largely inherit the band-pass characteristics of ETM+ and achieve continuity of Landsat data [24]. On the other hand, TM and ETM + were found to exhibit excellent data continuity [25], and the measurements of SR obtained by these sensors could be combined with minimal error without sacrificing product accuracy [26][27][28].…”

Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand

“…Optical sensor images of moderate resolution (30 m Significant advancements have been made in the Landsat satellite series in the last few decades, including the launch and operation of Landsat 1-5, 7, and 8 [37]. It is important to study the continuity between different sensors of the same Landsat series by considering the major sensor characteristics and their behavior with regard to various landforms; this is especially critical in mountainous regions, where accessibility is limited.…”

Multitemporal Analysis in Mediterranean Forestland with Remote Sensing

“…It is difficult to comprehensively model their spectral reflectance differences, which also depend on the surface reflectance and atmospheric state [54]. Recent studies have modeled the relationship between the vegetation indices images obtained from ETM+ and OLI [54][55][56]. This information is very important for future applications of remote sensing to assess landscape temporal dynamics.…”

“…This information is very important for future applications of remote sensing to assess landscape temporal dynamics. Vegetated areas had better NDVI agreement than non-vegetated surfaces (especially water areas) [55], and the seasonal agreement of both sensors is better for forest and shrub areas during growth periods than for others land covers [56]. In addition, OLI images are very infrequently saturated [54], and hence more precise quantitative applications of remote sensing are expected for complex landscapes such as wetlands, mountainous areas and forest.…”