Comparative evaluation of operational land imager sensor on board landsat 8 and landsat 9 for land use land cover mapping over a heterogeneous landscape

Figures & data

Figure 1. Locational aspect of the experimental study area.

Table 1. Details of the Landsat satellite data used.

Satellite	Sensor	Date of Acquisition	Path/ ROW	Spatial Resolution	Radiometric Resolution	Temporal Resolution	Cloud Cover
Landsat 8	OLI/TIRS	13-02-2022	148/47	30/100	12 bit	16 days	0.03%
Landsat 9	OLI-2/TIRS-2	21-02-2022	148/47	30/100	14 bit	16 days	0.00%

Figure 2. The schematic diagram of the process of wavelet-PCA for generating the high-resolution multispectral images.

Figure 3. False color composite after fusion of (a) Landsat 8 OLI and (b) Landsat 9 OLI-2 data.

Figure 4. Methodological flow chart for the study.

Figure 5. Classified LULC maps using multispectral bands of (a) Landsat 8 OLI and (b) Landsat 9 OLI-2.

Figure 6. Comparison of the LULC classification with google earth.

Figure 7. Land discrepancy analysis between Landsat 8 and 9 using Markovian transition matrix.

Figure 8. Visualization of spatial discrepancy of land detection between Landsat 8 and Landsat 9.

Figure 9. Quantification of land detection discrepancy between the LULC of Landsat 8 OLI and Landsat 9 OLI-2.

Figure 10. Surface biophysical parameters calculated from Landsat 8 OLI and Landsat 9 OLI-2 data sets.

Table 2. Validation of LULC map of landsat OLI.

LULC classes	Water body	Dense vegetation	Sparse vegetation	Built-up area	Cropland	Open land	Total	User’s Accuracy	Kappa
Water body	32	4	2	0	0	0	38	0.84	–
Dense vegetation	0	29	4	0	2	0	35	0.828	–
Sparse vegetation	0	4	43	0	3	0	50	0.86	–
Built-up	0	0	0	109	0	8	117	0.932	–
Cropland	0	0	6	0	32	0	38	0.842	–
Open land	0	0	0	7	0	25	32	0.781	–
Total	32	37	55	116	37	33	310	0	–
Producer’s Accuracy	1	0.784	0.782	0.939	0.864	0.581	0	0.87	–
Kappa	–	–	–	–	–	–	–	–	0.834

Table 3. Validation of LULC map of landsat OLI-2.

LULC classes	Water body	Dense vegetation	Sparse vegetation	Built-up area	Cropland	Open land	Total	User’s Accuracy	Kappa
Water body	38	2	0	0	0	0	40	0.95	–
Dense vegetation	1	37	2	0	0	0	40	0.925	–
Sparse vegetation	0	0	41	0	2	0	43	0.953	–
Built-up	0	0	2	116	0	2	120	0.972	–
cropland	0	0	3	0	32	0	35	0.967	–
Open land	0	0	0	3	1	28	32	0.875	–
Total	39	39	48	119	35	30	310	0	–
Producer’s Accuracy	0.974	0.948	0.854	0.975	0.914	0.933	0	0.941	–
Kappa	–	–	–	–	–	–	–	–	0.924

Figure 11. Significance analysis using bivariate local Moran’s I for (a) LULC-MNDWI, (b) LULC-NDVI, (c) LULC-SAVI, and (d) LULC-NDBI, and cluster-dispersion analysis for I LULC-MNDWI, (f) LULC-NDVI, (g) LULC-SAVI, and (h) LULC-NDBI for Landsat 8.

Figure 12. Significance analysis using bivariate local Moran’s I for (a) LULC-MNDWI, (b) LULC-NDVI, (c) LULC-SAVI, and (d) LULC-NDBI, and cluster-dispersion analysis for I LULC-MNDWI, (f) LULC-NDVI, (g) LULC-SAVI, and (h) LULC-NDBI for Landsat 9.

Data availability statement

The data will be available upon reasonable request through corresponding authors.