Normalized Difference Vegetation Index Continuity of the Landsat 4-5 MSS and TM: Investigations Based on Simulation
<p>Spectral response functions (SRFs) for the MSS multispectral channels and the approximately corresponding TM channels onboard Landsat 4 (L4) and Landsat 5 (L5), including the channels located within Green, Red, and near-infrared (NIR) regions respectively. Additional channels of the TM (<a href="#remotesensing-11-01681-t001" class="html-table">Table 1</a>) are not shown in this figure. The data were obtained from <a href="https://landsat.gsfc.nasa.gov" target="_blank">https://landsat.gsfc.nasa.gov</a>.</p> "> Figure 2
<p>Temporal distribution of the valid Landsat 4-5 MSS and TM scenes over the Worldwide Reference System (WRS)-2 Path/Row 123/032, in the Landsat Collection 1 Level-1 data product (<a href="https://earthexplorer.usgs.gov/" target="_blank">https://earthexplorer.usgs.gov/</a>). The valid scene was manually selected in terms of cloud cover and imagery quality through visual discrimination.</p> "> Figure 3
<p>Illustrations of channel reflectance for the approximately corresponding channels of MSS and TM, onboard Landsat 4 (L4) (top row) and Landsat 5 (L5) (bottom row). The channels over red and NIR regions are presented, which were used for normalized difference vegetation index (NDVI) calculation. General differences are presented, including the median difference (MdD, Equation (7)) and the median relative difference (MdRD, Equation (8)). To get the difference measures, variables for TM were used as references respectively. The black dashed lines in all subplots are 1:1 lines superimposed for reference. Data density is indicated by color, with color from blue to red representing the data density from low to high.</p> "> Figure 4
<p>NDVI difference (MdRD) between the MSS and TM of Landsat 4 before (top row) and after (bottom row) transformation. Improvements associated with four transformation models are shown as “After,” which include the univariate ordinary least squares (OLS) regression models (left) and the bivariate models (through OLS and ridge regression respectively). The histograms are based on 10,000 times K-fold (K = 5) cross-validation tests, while the equally spaced steps (with 10 bins) for the histograms are 0.104%, 0.305%, 0.127%, 0.278%, 0.072%, and 0.067% respectively. The vertical lines show the median values of NDVI difference correspondingly. The median MdRD with lower and upper bounds (taken as 2.5% and 97.5% percentiles respectively) for cross-validation tests are −13.61% (−13.84%, −13.38%) and 7.40% (6.67%, 8.11%) before transformation (top row), while −1.32% (−1.62%, −1.02%), 1.05% (0.38%, 1.71%), −0.24% (−0.43%, −0.08%), and −0.12% (−0.30%, 0.03%) after transformation through respective models (bottom row).</p> "> Figure 5
<p>NDVI difference (MdRD) between MSS and TM of Landsat 5 before (top row) and after (bottom row) transformation. The histograms are based on 10,000 times K-fold (K = 5) cross-validation tests, while the equally spaced steps for the histograms are 0.094%, 0.326%, 0.123%, 0.326%, 0.073%, and 0.069% respectively. The vertical lines show the median values of NDVI difference correspondingly. The median MdRD with lower and upper bounds for cross-validation tests are −11.44% (−11.65%, −11.23%) and 8.68% (7.90%, 9.50%) before transformation (top row), while −1.15% (−1.43%, −0.88%), 1.11% (0.42%, 1.78%), −0.23% (−0.40%, −0.07%), and −0.11% (−0.28%, 0.04%) after transformation through respective models (bottom row).</p> "> Figure 6
<p>NDVI comparisons derived from the valid samples randomly selected for the cases (labeled as from 1 to 8) listed in <a href="#remotesensing-11-01681-t002" class="html-table">Table 2</a>. In each subplot, transformed MSS NDVI(s) as well as original MSS NDVI(s) are shown with comparison to TM NDVI. For cases 7 and 8, only MSS32 NDVI is shown, due mainly to the data problem of the MSS NIR2 imagery. The dashed lines are 1:1 lines superimposed for reference.</p> "> Figure 7
<p>Demonstration of the transforming models to estimate the TM NDVI from the MSS NDVI of Landsat 4 (L4). Two univariate models are in the top row, in which the red lines show ordinary least squares (OLS) regression of the MSS NDVIs (MSS32 and MSS42) against the TM NDVI (TM43) respectively, while the dashed lines are 1:1 lines superimposed for reference. The bivariate models through OLS regression and ridge regression respectively are in the bottom row, in which the planes with red edge show regression models. Similar as in <a href="#remotesensing-11-01681-f003" class="html-fig">Figure 3</a>, the color from blue to red is representing the data density from low to high.</p> "> Figure 8
<p>Cumulative distributions of the coefficients for the bivariate models of Landsat 4, including the offset (left), the coefficient of MSS32 (center), and the coefficient of MSS42 (right). The probabilities were estimated according to 10,000 times K-fold (K = 5) cross-validation tests. To show the distribution difference, the coefficients were shifted by subtracting the median values respectively. For OLS regression model and ridge model, the median offset estimates are −0.0065 and −0.0051, the median estimates of MSS32 are 0.7724 and 0.7023, and the median estimates of MSS42 are 0.3226 and 0.3767 respectively, as shown in <a href="#remotesensing-11-01681-t004" class="html-table">Table 4</a>.</p> "> Figure 9
<p>Interpretation for three subsets extracted from the Landsat 5 MSS and TM Quality Assessment (QA) band information: color image (R: NIR channel, G: Green channel, B: Red channel) and the interpreted information. Specifically, the QA interpretations for TM are cloud (green), cloud shadow (blue), and “clear terrain” (red), while for MSS are cloud (cyan) and clear terrain (red). Generally, QA information for TM imagery is more reliable. All subsets illustrated are for the MSS and TM pairs of Case 3 (<a href="#remotesensing-11-01681-t003" class="html-table">Table 3</a>).</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Spectral Response Function (SRF) of Landsat 4-5 MSS, TM, and Hyperion
2.2. Hyperion Spectra Collection
2.3. Paired MSS and TM Observations of Landsat 5 for Case Studies
2.4. Channel Reflectance Simulation
2.5. NDVI Estimation of the Landsat 4-5 MSS and TM
2.6. Between-Sensor Difference Measures
2.7. Transformation Models
3. Results
3.1. Intra-Platform Differences
3.2. Inter-Platform Differences
3.3. Transformation Models and Comparison
3.4. Application Cases
4. Discussion
4.1. Channel Reflectance Simulated from Hyperion Spectra
4.2. Transformation Modeling and Application
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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MSS | TM | |
---|---|---|
Blue | -- | B1: 450–520 nm (30 m) |
Green | B1: 500–600 nm (60 m) | B2: 520–600 nm (30 m) |
Red | B2: 600–700 nm (60 m) | B3: 630–690 nm (30 m) |
NIR | B3 (NIR1): 700–800 nm (60 m) B4 (NIR2): 800–11000 nm (60 m) | B4: 760–900 nm (30 m) -- |
SWIR | -- -- | B5: 1550–1750 nm (30 m) B7: 2080–2350 nm (30 m) |
Thermal infrared | -- | B6: 10.40–12.50 μm (120 m 1) |
Case | Landsat 5 MSS | Landsat 5 TM |
---|---|---|
1 | LM05_L1TP_123032_19850312_20180405_01_T2 | LT05_L1TP_123032_19850312_20170219_01_T1 |
2 | LM05_L1TP_123032_19851022_20180407_01_T2 | LT05_L1TP_123032_19851022_20170218_01_T1 |
3 | LM05_L1TP_123032_19880421_20180326_01_T2 | LT05_L1TP_123032_19880421_20170221_01_T1 |
4 | LM05_L1TP_123032_19881014_20180327_01_T2 | LT05_L1TP_123032_19881014_20170206_01_T1 |
5 | LM05_L1TP_123032_19900105_20180323_01_T2 | LT05_L1TP_123032_19900105_20170201_01_T1 |
6 | LM05_L1TP_123032_19901121_20180324_01_T2 | LT05_L1TP_123032_19901121_20180620_01_T1 |
7 | LM05_L1TP_123032_19950916_20180315_01_T2 | LT05_L1TP_123032_19950916_20170107_01_T1 |
8 | LM05_L1TP_123032_19951221_20180315_01_T2 | LT05_L1TP_123032_19951221_20170106_01_T1 |
MSS42(L4) | MSS32(L4) | TM43(L4) | MSS42(L5) | MSS32(L5) | TM43(L5) | |
---|---|---|---|---|---|---|
MSS42(L4) | -- | 0.9870 | 0.9908 | 1.0000 | 0.9870 | 0.9907 |
MSS32(L4) | 24.39% | -- | 0.9981 | 0.9868 | 1.0000 | 0.9981 |
TM43(L4) | 7.40% | −13.61% | -- | 0.9907 | 0.9981 | 1.0000 |
MSS42(L5) | −0.84% | −21.16% | −8.13% | -- | 0.9868 | 0.9905 |
MSS32(L5) | 21.79% | −2.12% | 13.09% | 22.81% | -- | 0.9982 |
TM43(L5) | 7.79% | −13.32% | 0.42% | 8.68% | −11.44% | -- |
Intra-Platform Transformation | MSE1 | MdD | MdRD | |
L4 OLS | TM43 = 0.0012 + 1.1380MSS32 | 0.0213 | −0.0032 | −1.32% |
OLS | TM43 = −0.0106 + 0.9703MSS42 | 0.0379 | 0.0008 | 1.04% |
OLS | TM43 = −0.0065 + 0.7724MSS32 + 0.3226MSS42 | 0.0123 | −0.0006 | −0.24% |
Ridge | TM43 = −0.0051 + 0.7023MSS32 + 0.3767MSS42 | 0.0128 | −0.0003 | −0.12% |
L5 OLS | TM43 = −0.0006 + 1.1181MSS32 | 0.0198 | −0.0028 | −1.15% |
OLS | TM43 = −0.0116 + 0.9628MSS42 | 0.0390 | −0.0010 | −1.11% |
OLS | TM43 = −0.0076 + 0.7888MSS32 + 0.2939MSS42 | 0.0118 | −0.0006 | −0.23% |
Ridge | TM43 = −0.0064 + 0.7097MSS32 + 0.3564MSS42 | 0.0124 | −0.0003 | −0.10% |
Inter-Platform Transformation (L4 to L5) | MSE | MdD | MdRD | |
OLS | TM43(L5) = −0.0011 + 1.0001TM43(L4) | 0.0007 | 0.00002 | 0.02% |
OLS | TM43 = 0.0001 + 1.1384MSS32 | 0.0208 | −0.0032 | −1.30% |
OLS | TM43 = −0.0115 + 0.9701MSS42 | 0.0384 | −0.0008 | 1.08% |
OLS | TM43 = −0.0074 + 0.7845MSS32 + 0.3122MSS42 | 0.0122 | −0.0007 | −0.26% |
Ridge | TM43 = −0.0061 + 0.7102MSS32 + 0.3699MSS42 | 0.0127 | −0.0003 | −0.12% |
MSS32 | MSS42 | MSS32 (After) | MSS42 (After) | MSS32+MSS42 (OLS) | MSS32+MSS42 (Ridge) | ||
---|---|---|---|---|---|---|---|
1 | MdD | −0.0303 | 0.0223 | −0.0233 | 0.0064 | −0.0170 | −0.0135 |
MdRD | −32.27% | 24.02% | −24.91% | 6.91% | −18.30% | −14.59% | |
2 | MdD | −0.0523 | 0.0427 | −0.0391 | 0.0230 | −0.0224 | −0.0172 |
MdRD | −30.70% | 25.06% | −22.90% | 13.51% | −13.02% | −9.96% | |
3 | MdD | −0.0486 | 0.0440 | −0.0382 | 0.0255 | −0.0215 | −0.0161 |
MdRD | −34.46% | 31.12% | −27.14% | 18.02% | −15.30% | −11.45% | |
4 | MdD | −0.0524 | 0.0398 | −0.0398 | 0.0207 | −0.0240 | −0.0189 |
MdRD | −31.81% | 24.46% | −24.12% | 12.71% | −14.51% | −11.45% | |
5 | MdD | −0.0202 | 0.0782 | −0.0115 | 0.0600 | 0.0074 | 0.0135 |
MdRD | −20.39% | 78.31% | −11.58% | 59.74% | 7.41% | 13.50% | |
6 | MdD | −0.0306 | 0.0738 | −0.0212 | 0.0552 | −0.0008 | 0.0055 |
MdRD | −26.43% | 62.73% | −18.25% | 46.75% | −0.70% | 4.70% | |
7 | MdD | −0.1131 | -- | −0.0508 | -- | -- | -- |
MdRD | −18.14% | -- | −8.57% | -- | -- | -- | |
8 | MdD | −0.0205 | -- | −0.0117 | -- | -- | -- |
MdRD | −20.53% | -- | −11.74% | -- | -- | -- |
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Chen, F.; Lou, S.; Fan, Q.; Wang, C.; Claverie, M.; Wang, C.; Li, J. Normalized Difference Vegetation Index Continuity of the Landsat 4-5 MSS and TM: Investigations Based on Simulation. Remote Sens. 2019, 11, 1681. https://doi.org/10.3390/rs11141681
Chen F, Lou S, Fan Q, Wang C, Claverie M, Wang C, Li J. Normalized Difference Vegetation Index Continuity of the Landsat 4-5 MSS and TM: Investigations Based on Simulation. Remote Sensing. 2019; 11(14):1681. https://doi.org/10.3390/rs11141681
Chicago/Turabian StyleChen, Feng, Shenlong Lou, Qiancong Fan, Chenxing Wang, Martin Claverie, Cheng Wang, and Jonathan Li. 2019. "Normalized Difference Vegetation Index Continuity of the Landsat 4-5 MSS and TM: Investigations Based on Simulation" Remote Sensing 11, no. 14: 1681. https://doi.org/10.3390/rs11141681