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Performance of MODIS-Landsat Blending of Vegetation Indices in the Coastal Zone of Ganges Delta

Indian Agricultural Research Journals

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Title Performance of MODIS-Landsat Blending of Vegetation Indices in the Coastal Zone of Ganges Delta
 
Creator PEÑA-ARANCIBIA, J.L.
YU, Y.
 
Subject Image processing
Monitoring
Remote sensing
Vegetation indices
Satellites
 
Description Blending of temporal high-frequency-low-spatial resolution MODIS with temporal low-frequency-high-spatial resolution Landsat satellite imagery enhances the frequency and resolution of spatial data, thus enabling continuous monitoring of dynamic and rapidly changing environmental conditions. Blending can be particularly useful in areas with high cloud cover, such as during the monsoon season in the coastal zone of the Ganges Brahmaputra Delta (CZGBD). In this study, MODIS-Landsat blending of reflectance-derived remote sensing indices is trialled and evaluated in the CZGBD. The Sub-pixel class fraction change information Flexible Spatiotemporal DAta Fusion (SFSDAF) algorithm is used to obtain gap free 30 m and 16-day frequency vegetation, salinity and water indices for the entire CZGBD. Pixels obtained through blending were compared to the observed pixels (i.e., not contaminated by clouds to evaluate the accuracy of SFSDAF). Results during the ‘dry’ months (October to March) had a combined mean coefficient of determination, R2 = 0.65 and mean root squared error, RMSE = 0.09 for vegetation indices, whereas the results during the ‘wet’ months (April to September) had a combined mean R2 = 0.33 and mean RMSE = 0.12. The reduced accuracy of the blending during the monsoon months showcases the effects of cloudy conditions. Results for salinity and water indices showed similar behaviour as the vegetation indices, influenced by the cloudy monsoon season. The main cause of low accuracy during the ‘wet’ months is the paucity of data to perform the blending, even at the daily MODIS frequency. In addition, remote sensing indices with equations that normalised the range (generally between -1 and 1) had better results when compared to remote sensing indices that had less constrained ranges.
 
Publisher Indian Society of Coastal Agricultural Research
 
Date 2024-06-20
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://epubs.icar.org.in/index.php/JISCAR/article/view/147381
10.54894/JISCAR.42.1.2024.147381
 
Source Journal of the Indian Society of Coastal Agricultural Research; Vol. 42 No. 1 (2024): Special Issue
2584-0320
0972-1584
 
Language eng
 
Relation https://epubs.icar.org.in/index.php/JISCAR/article/view/147381/54808
 
Rights Copyright (c) 2024 Indian Society of Coastal Agricultural Research (ISCAR)
https://creativecommons.org/licenses/by-nc-sa/4.0