Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh

Nurul Hamid; Md. Redwanur Rahman

doi:doi:10.11648/j.ajrs.20261402.15

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Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh

Nurul Hamid

, Md. Redwanur Rahman^*

Published in American Journal of Remote Sensing (Volume 14, Issue 2)

Received: 12 August 2026 Accepted: 28 August 2026 Published: 20 September 2026

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Abstract

The southeastern coastal landscape of Bangladesh particularly the Cox’s Bazar district Ukhiya-Teknaf region is a globally important yet extremely fragile biodiversity zone in the Indo-Burma hotspot. Habitat conditions have changed dramatically due to rapid expansion of Rohingya settlements, forest fragmentation and climate-related environmental stresses. However, there is little understanding of the quantitative relationship between satellite-derived ecological changes and taxon-specific faunal responses. The study uses multi-source geospatial data and statistical modelling to evaluate the environmental drivers of vertebrate faunal diversity between 2015 and 2026. Vegetation, thermal, moisture and ecological indicators comprising the Normalized Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), evapotranspiration (ET) and Ecological Health Index (EHI) were derived from Sentinel-2A, Landsat-8/9 and MODIS datasets. These were integrated with secondary biodiversity data standardised from Cox’s Bazar South Forest Division, Teknaf Wildlife Sanctuary, Inani National Park, Nishorgo conservation databases, UNDP/UNHCR reports and published scientific research. The temporal study indicates a Substantial habitat transformation with a reduction of dense vegetation from 36,791 to 24,306 pixels (−33.9%) and an expansion of built-up by 121.2%, from 2015 to 2025. The maximum land surface temperature increased from 35.50°C to 48.99°C, indicating increasing thermal pressure. Correlation analysis, regression modelling, and multivariate analysis indicated potential associations between vegetation condition (NDVI/TDVI/EHI), heat stress (LST), moisture variability (ET), and faunal responses; however, statistically significant evidence for these relationships was limited. The observed patterns demonstrated comparably larger connections of mammal and bird responses with vegetation degradation and habitat fragmentation, whereas reptile and amphibian responses exhibited greater correspondence with heat and moisture variability. The integrated geospatial-statistical approach identifies biodiversity sensitive zones and provides scientific basis for habitat restoration and climate resilient conservation planning in rapidly changing tropical environments.

Published in	American Journal of Remote Sensing (Volume 14, Issue 2)
DOI	10.11648/j.ajrs.20261402.15
Page(s)	78-98
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Geospatial Indicators, Vertebrate Diversity, Remote Sensing, Climate Stress, Ecological Health Index, Rohingya Settlement Landscape

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APA Style

Hamid, N., Rahman, M. R. (2026). Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh. American Journal of Remote Sensing, 14(2), 78-98. https://doi.org/10.11648/j.ajrs.20261402.15

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ACS Style

Hamid, N.; Rahman, M. R. Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh. Am. J. Remote Sens. 2026, 14(2), 78-98. doi: 10.11648/j.ajrs.20261402.15

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AMA Style

Hamid N, Rahman MR. Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh. Am J Remote Sens. 2026;14(2):78-98. doi: 10.11648/j.ajrs.20261402.15

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@article{10.11648/j.ajrs.20261402.15,
  author = {Nurul Hamid and Md. Redwanur Rahman},
  title = {Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh},
  journal = {American Journal of Remote Sensing},
  volume = {14},
  number = {2},
  pages = {78-98},
  doi = {10.11648/j.ajrs.20261402.15},
  url = {https://doi.org/10.11648/j.ajrs.20261402.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20261402.15},
  abstract = {The southeastern coastal landscape of Bangladesh particularly the Cox’s Bazar district Ukhiya-Teknaf region is a globally important yet extremely fragile biodiversity zone in the Indo-Burma hotspot. Habitat conditions have changed dramatically due to rapid expansion of Rohingya settlements, forest fragmentation and climate-related environmental stresses. However, there is little understanding of the quantitative relationship between satellite-derived ecological changes and taxon-specific faunal responses. The study uses multi-source geospatial data and statistical modelling to evaluate the environmental drivers of vertebrate faunal diversity between 2015 and 2026. Vegetation, thermal, moisture and ecological indicators comprising the Normalized Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), evapotranspiration (ET) and Ecological Health Index (EHI) were derived from Sentinel-2A, Landsat-8/9 and MODIS datasets. These were integrated with secondary biodiversity data standardised from Cox’s Bazar South Forest Division, Teknaf Wildlife Sanctuary, Inani National Park, Nishorgo conservation databases, UNDP/UNHCR reports and published scientific research. The temporal study indicates a Substantial habitat transformation with a reduction of dense vegetation from 36,791 to 24,306 pixels (−33.9%) and an expansion of built-up by 121.2%, from 2015 to 2025. The maximum land surface temperature increased from 35.50°C to 48.99°C, indicating increasing thermal pressure. Correlation analysis, regression modelling, and multivariate analysis indicated potential associations between vegetation condition (NDVI/TDVI/EHI), heat stress (LST), moisture variability (ET), and faunal responses; however, statistically significant evidence for these relationships was limited. The observed patterns demonstrated comparably larger connections of mammal and bird responses with vegetation degradation and habitat fragmentation, whereas reptile and amphibian responses exhibited greater correspondence with heat and moisture variability. The integrated geospatial-statistical approach identifies biodiversity sensitive zones and provides scientific basis for habitat restoration and climate resilient conservation planning in rapidly changing tropical environments.},
 year = {2026}
}

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TY  - JOUR
T1  - Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh
AU  - Nurul Hamid
AU  - Md. Redwanur Rahman
Y1  - 2026/09/20
PY  - 2026
N1  - https://doi.org/10.11648/j.ajrs.20261402.15
DO  - 10.11648/j.ajrs.20261402.15
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 78
EP  - 98
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20261402.15
AB  - The southeastern coastal landscape of Bangladesh particularly the Cox’s Bazar district Ukhiya-Teknaf region is a globally important yet extremely fragile biodiversity zone in the Indo-Burma hotspot. Habitat conditions have changed dramatically due to rapid expansion of Rohingya settlements, forest fragmentation and climate-related environmental stresses. However, there is little understanding of the quantitative relationship between satellite-derived ecological changes and taxon-specific faunal responses. The study uses multi-source geospatial data and statistical modelling to evaluate the environmental drivers of vertebrate faunal diversity between 2015 and 2026. Vegetation, thermal, moisture and ecological indicators comprising the Normalized Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), evapotranspiration (ET) and Ecological Health Index (EHI) were derived from Sentinel-2A, Landsat-8/9 and MODIS datasets. These were integrated with secondary biodiversity data standardised from Cox’s Bazar South Forest Division, Teknaf Wildlife Sanctuary, Inani National Park, Nishorgo conservation databases, UNDP/UNHCR reports and published scientific research. The temporal study indicates a Substantial habitat transformation with a reduction of dense vegetation from 36,791 to 24,306 pixels (−33.9%) and an expansion of built-up by 121.2%, from 2015 to 2025. The maximum land surface temperature increased from 35.50°C to 48.99°C, indicating increasing thermal pressure. Correlation analysis, regression modelling, and multivariate analysis indicated potential associations between vegetation condition (NDVI/TDVI/EHI), heat stress (LST), moisture variability (ET), and faunal responses; however, statistically significant evidence for these relationships was limited. The observed patterns demonstrated comparably larger connections of mammal and bird responses with vegetation degradation and habitat fragmentation, whereas reptile and amphibian responses exhibited greater correspondence with heat and moisture variability. The integrated geospatial-statistical approach identifies biodiversity sensitive zones and provides scientific basis for habitat restoration and climate resilient conservation planning in rapidly changing tropical environments.
VL  - 14
IS  - 2
ER  -

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Author Information

Nurul Hamid

Institute of Environmental Science, University of Rajshahi, Rajshahi, Bangladesh

http://orcid.org/0009-0009-5611-4836
Md. Redwanur Rahman

Institute of Environmental Science, University of Rajshahi, Rajshahi, Bangladesh

Contact Email

http://orcid.org/0009-0008-6542-7087

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Hamid, N., Rahman, M. R. (2026). Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh. American Journal of Remote Sensing, 14(2), 78-98. https://doi.org/10.11648/j.ajrs.20261402.15

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ACS Style

Hamid, N.; Rahman, M. R. Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh. Am. J. Remote Sens. 2026, 14(2), 78-98. doi: 10.11648/j.ajrs.20261402.15

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AMA Style

Hamid N, Rahman MR. Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh. Am J Remote Sens. 2026;14(2):78-98. doi: 10.11648/j.ajrs.20261402.15

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@article{10.11648/j.ajrs.20261402.15,
  author = {Nurul Hamid and Md. Redwanur Rahman},
  title = {Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh},
  journal = {American Journal of Remote Sensing},
  volume = {14},
  number = {2},
  pages = {78-98},
  doi = {10.11648/j.ajrs.20261402.15},
  url = {https://doi.org/10.11648/j.ajrs.20261402.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20261402.15},
  abstract = {The southeastern coastal landscape of Bangladesh particularly the Cox’s Bazar district Ukhiya-Teknaf region is a globally important yet extremely fragile biodiversity zone in the Indo-Burma hotspot. Habitat conditions have changed dramatically due to rapid expansion of Rohingya settlements, forest fragmentation and climate-related environmental stresses. However, there is little understanding of the quantitative relationship between satellite-derived ecological changes and taxon-specific faunal responses. The study uses multi-source geospatial data and statistical modelling to evaluate the environmental drivers of vertebrate faunal diversity between 2015 and 2026. Vegetation, thermal, moisture and ecological indicators comprising the Normalized Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), evapotranspiration (ET) and Ecological Health Index (EHI) were derived from Sentinel-2A, Landsat-8/9 and MODIS datasets. These were integrated with secondary biodiversity data standardised from Cox’s Bazar South Forest Division, Teknaf Wildlife Sanctuary, Inani National Park, Nishorgo conservation databases, UNDP/UNHCR reports and published scientific research. The temporal study indicates a Substantial habitat transformation with a reduction of dense vegetation from 36,791 to 24,306 pixels (−33.9%) and an expansion of built-up by 121.2%, from 2015 to 2025. The maximum land surface temperature increased from 35.50°C to 48.99°C, indicating increasing thermal pressure. Correlation analysis, regression modelling, and multivariate analysis indicated potential associations between vegetation condition (NDVI/TDVI/EHI), heat stress (LST), moisture variability (ET), and faunal responses; however, statistically significant evidence for these relationships was limited. The observed patterns demonstrated comparably larger connections of mammal and bird responses with vegetation degradation and habitat fragmentation, whereas reptile and amphibian responses exhibited greater correspondence with heat and moisture variability. The integrated geospatial-statistical approach identifies biodiversity sensitive zones and provides scientific basis for habitat restoration and climate resilient conservation planning in rapidly changing tropical environments.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Integrating Geospatial Indicators and Statistical Modelling to Assess Environmental Drivers of Faunal Diversity Responses in the Rohingya Influx of Bangladesh
AU  - Nurul Hamid
AU  - Md. Redwanur Rahman
Y1  - 2026/09/20
PY  - 2026
N1  - https://doi.org/10.11648/j.ajrs.20261402.15
DO  - 10.11648/j.ajrs.20261402.15
T2  - American Journal of Remote Sensing
JF  - American Journal of Remote Sensing
JO  - American Journal of Remote Sensing
SP  - 78
EP  - 98
PB  - Science Publishing Group
SN  - 2328-580X
UR  - https://doi.org/10.11648/j.ajrs.20261402.15
AB  - The southeastern coastal landscape of Bangladesh particularly the Cox’s Bazar district Ukhiya-Teknaf region is a globally important yet extremely fragile biodiversity zone in the Indo-Burma hotspot. Habitat conditions have changed dramatically due to rapid expansion of Rohingya settlements, forest fragmentation and climate-related environmental stresses. However, there is little understanding of the quantitative relationship between satellite-derived ecological changes and taxon-specific faunal responses. The study uses multi-source geospatial data and statistical modelling to evaluate the environmental drivers of vertebrate faunal diversity between 2015 and 2026. Vegetation, thermal, moisture and ecological indicators comprising the Normalized Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature (LST), evapotranspiration (ET) and Ecological Health Index (EHI) were derived from Sentinel-2A, Landsat-8/9 and MODIS datasets. These were integrated with secondary biodiversity data standardised from Cox’s Bazar South Forest Division, Teknaf Wildlife Sanctuary, Inani National Park, Nishorgo conservation databases, UNDP/UNHCR reports and published scientific research. The temporal study indicates a Substantial habitat transformation with a reduction of dense vegetation from 36,791 to 24,306 pixels (−33.9%) and an expansion of built-up by 121.2%, from 2015 to 2025. The maximum land surface temperature increased from 35.50°C to 48.99°C, indicating increasing thermal pressure. Correlation analysis, regression modelling, and multivariate analysis indicated potential associations between vegetation condition (NDVI/TDVI/EHI), heat stress (LST), moisture variability (ET), and faunal responses; however, statistically significant evidence for these relationships was limited. The observed patterns demonstrated comparably larger connections of mammal and bird responses with vegetation degradation and habitat fragmentation, whereas reptile and amphibian responses exhibited greater correspondence with heat and moisture variability. The integrated geospatial-statistical approach identifies biodiversity sensitive zones and provides scientific basis for habitat restoration and climate resilient conservation planning in rapidly changing tropical environments.
VL  - 14
IS  - 2
ER  -

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