Precision mapping of mangroves and shoreline dynamics in the Sundarbans using cloud based vegetation indices analysis and advanced geospatial techniques
Bibliographic record
Abstract
• A novel approach is taken for fusing multiple raster indices in Google Earth Engine dense time series datasets. • A new raster index, CBMMI (Cloud-Based Mangrove Mapping Index), is developed for accurate mapping of mangroves. • Fifty years of Landsat datasets were used from the GEE’s repository for time series analysis to quantify the mangrove loss and island boundary delineation. • Accurate island boundaries are delineated, minimizing the tidal effect using image averaging using the best representative datasets. • Precise island boundaries are analyzed in DSAS to map the boundary change metrics. Mangrove ecosystems play a crucial role in sustaining ecological balance, protecting coastlines from erosion and natural disasters, and conserving biodiversity. Presently, the Indian Sundarban, particularly the southern region within the Tiger Reserve and Territorial Division, has witnessed alarming erosion rates and substantial loss of mangrove cover. This study focuses on the STR (Sundarban Tiger Reserve), the southernmost part of the Indian Sundarban region. This research introduces a novel methodology by applying dense temporal remote sensing datasets and geospatial analysis performed through Google Earth Engine (GEE) and further analyzing the output datasets through the GIS-based DSAS (Digital Shoreline Analysis System) using a newly developed raster-based mangrove index named CBMMI (Cloud Based Mangrove Mapping Index). This study further aimed to leverage the potential of the time series data, integrating it into the DSAS to analyse the island boundary change metrics, studying multiple parameters, and further relate the change to the mangrove cover. The cloud-based approach in GEE enables efficient estimation of the mangrove cover with the most representative annual dataset, thereby enhancing the mapping accuracy and reducing the bias in a spatio-temporal space. Integration of DSAS identifies the mangrove change hotspots and their pattern over a 50-year span from 1973 to 2023. An alarming shift in the island boundary of 2,321 m and 2,369 m was observed at Dalhousie Island and Bhangaduni Island, located in the southern part of the STR. These change hotspots were further analysed using bathymetric and cyclone data to identify the transformation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".