Cross-Comparison of Vegetation Indices Derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) Sensors

Abstract

Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are currently operational for routine Earth observation. There are substantial differences between instruments onboard both satellites. The enhancements achieved with Landsat-8 refer to the scanning technology (replacing of whisk-broom scanners with two separate push-broom OLI and TIRS scanners), an extended number of spectral bands (two additional bands provided) and narrower bandwidths. Therefore, cross-comparative analysis is very necessary for the combined use of multi-decadal Landsat imagery. In this study, 3,311 independent sample points of four major land cover types (primary forest, unplanted cropland, swidden cultivation and water body) were used to compare the spectral bands of ETM+ and OLI. Eight sample plots with different land cover types were manually selected for comparison with the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), the Land Surface Water Index (LSWI) and the Normalized Burn Ratio (NBR). These indices were calculated with six pairs of ETM+ and OLI cloud-free images, which were acquired over the border area of Myanmar, Laos and Thailand just two days apart, when Landsat-8 achieved operational obit. Comparative results showed that: (1) the average surface reflectance of each band differed slightly, but with a high degree of similarities between both sensors. In comparison with ETM+, the OLI had higher values for the near-infrared band for vegetative land cover types, but lower values for non-vegetative types. The new sensor had lower values for the shortwave infrared (2.11-2.29 µm) band for

Yield variability prediction by remote sensing sensors with different spatial resolution

“…WV-2 and QB satellite images were purchased from the ArcDATA Company (Table 2). For atmospheric correction, the Fast Line-of-sight Atmospheric Analysis of Hypercubes was used (Dominguez et al, 2015;Li et al, 2014). All image pre-processing was implemented with ENVI SW (ENVI; version 5.3, Excelis, Inc., McLean, VA, USA).…”

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

“…It is important to study continuity among sensors from the same series of satellites by considering of the important parameters including sensor characteristics, over-pass time, scanning system, angular affect and etc. A few studies related to the continuity of Landsat 8 have been conducted, including preflight and post-launch calibrations [28][29][30][31][32][33]. Most of these studies have shown that the continuity between the Landsat-8 OLI and Landsat-7 ETM+ is good.…”

“…Markham conducted a pre-launch and on-orbit radiometric characterization and calibration of Landsat 8 and found that the uncertainty of radiance calibration performance was within 2%, while for the reflectance calibration it was within 3% [29]. Li compared the consistency of four spectral indices for four land cover types in southeast Asia and found the correlation coefficients (R 2 ) to be a maximum of 0.96 for measurements over a two-day period [33]. However, few comparison of the continuity of various VIs for Landsat series data has been addressed.…”

Large-scale indicators for monitoring forest diversity of the main forest types in Calabria (Italy)

“…Un ulteriore strato informativo derivato da OT è costituito dal dato Landsat 8 (L8) OLI, che è stato utilizzato per il calcolo dell'indice NDVI (Normalized Difference Vegetation Index - Li et al 2013).…”