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Greening and browning trend with physio-climatic drivers in Chattogram division, Bangladesh.

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Title: Greening and browning trend with physio-climatic drivers in Chattogram division, Bangladesh.
Authors: Rashid, Kazi Jihadur1,2 (AUTHOR) jihadrashid.gis@gmail.com, Tuli, Rajsree Das2,3 (AUTHOR), Nasher, N. M. Refat4 (AUTHOR), Akter, Tahmina1 (AUTHOR), Karim, K. H. Razimul5 (AUTHOR), Hasan, Md. Mahmudul4 (AUTHOR), Talha, MD4 (AUTHOR), Chowdhury, Shah Imran Ahsan1 (AUTHOR), Musharrat, Mahiba6 (AUTHOR)
Source: Environment, Development & Sustainability. Jun2026, Vol. 28 Issue 6, p13407-13429. 23p.
Subject Terms: *Vegetation dynamics, *Normalized difference vegetation index, *Remote sensing, *Rainfall, *Altitudes, *Surface temperature, *Climate change, *Soil classification
Geographic Terms: Bangladesh, Chittagong (Bangladesh)
Abstract: As a significant aspect of global change, climate change poses substantial risks to vegetation extent and health, affecting ecosystem services and stability. While numerous studies have explored the immediate and time-lagged impacts of climatic factors on vegetation growth, there is a noticeable gap in understanding the cumulative change, which is crucial to monitoring vegetation dynamics. Furthermore, the limitations of traditional change detection methods pose a significant barrier to effectively utilizing time series approaches in remote sensing. The main aim of the study was to examine changes in vegetation composition and the potential physio-climatic drivers in the southeastern region of Bangladesh due to its diversified landscape by establishing baseline conditions and identifying shifts over time. This research employs the directional persistence technique at a regional scale on 22 years of MODIS NDVI to determine season-wise cumulative greening and browning from 2000 to 2022 by considering the initial 5-year average as the benchmark NDVI for each season. Moreover, the influence of driving forces is studied using Pearson's correlation between post-monsoon NDVI with rainfall and LST, as well as Geodetector factor analysis of NDVI with soil, elevation, LST, and rainfall. The result from these analyses identifies that the post-monsoon season has the highest significant vegetation change (combining greening and browning) with 65% of the area, followed by winter, pre-monsoon, and monsoon, whereas the highest browning season was winter. Additionally, rainfall and surface temperature show a negative correlation with NDVI. Among the spatial factors, elevation (q statistic = 0.37, p < 0.001) shows the highest influence in shaping vegetation distribution, with soil types and temperature having a similar impact. Although these interactions are mutually dependent on each other, rainfall (q statistic = 0.08, p < 0.001) seems to have lesser direct influence over the spatiality of vegetation. This research contributes to a deeper understanding of vegetation interactions with physiography and climate in the Chattogram region as well as provides a monitoring framework for sustainable land management in the face of ongoing climatic challenges. These findings can guide foresters, agriculturalists, ecologists, and policymakers in understanding regional vegetation dynamics and developing adaptive strategies for mitigating the adverse effects of climate alteration by integrating climate projections into land-use planning. [ABSTRACT FROM AUTHOR]
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  Label: Title
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  Data: Greening and browning trend with physio-climatic drivers in Chattogram division, Bangladesh.
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  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Rashid%2C+Kazi+Jihadur%22&quot;&gt;Rashid, Kazi Jihadur&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; jihadrashid.gis@gmail.com&lt;/i&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Tuli%2C+Rajsree+Das%22&quot;&gt;Tuli, Rajsree Das&lt;/searchLink&gt;&lt;relatesTo&gt;2,3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Nasher%2C+N%2E+M%2E+Refat%22&quot;&gt;Nasher, N. M. Refat&lt;/searchLink&gt;&lt;relatesTo&gt;4&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Akter%2C+Tahmina%22&quot;&gt;Akter, Tahmina&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Karim%2C+K%2E+H%2E+Razimul%22&quot;&gt;Karim, K. H. Razimul&lt;/searchLink&gt;&lt;relatesTo&gt;5&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Hasan%2C+Md%2E+Mahmudul%22&quot;&gt;Hasan, Md. Mahmudul&lt;/searchLink&gt;&lt;relatesTo&gt;4&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Talha%2C+MD%22&quot;&gt;Talha, MD&lt;/searchLink&gt;&lt;relatesTo&gt;4&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Chowdhury%2C+Shah+Imran+Ahsan%22&quot;&gt;Chowdhury, Shah Imran Ahsan&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Musharrat%2C+Mahiba%22&quot;&gt;Musharrat, Mahiba&lt;/searchLink&gt;&lt;relatesTo&gt;6&lt;/relatesTo&gt; (AUTHOR)
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Environment%2C+Development+%26+Sustainability%22&quot;&gt;Environment, Development &amp; Sustainability&lt;/searchLink&gt;. Jun2026, Vol. 28 Issue 6, p13407-13429. 23p.
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  Data: *&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Vegetation+dynamics%22&quot;&gt;Vegetation dynamics&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Normalized+difference+vegetation+index%22&quot;&gt;Normalized difference vegetation index&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Remote+sensing%22&quot;&gt;Remote sensing&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Rainfall%22&quot;&gt;Rainfall&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Altitudes%22&quot;&gt;Altitudes&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Surface+temperature%22&quot;&gt;Surface temperature&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Climate+change%22&quot;&gt;Climate change&lt;/searchLink&gt;&lt;br /&gt;*&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Soil+classification%22&quot;&gt;Soil classification&lt;/searchLink&gt;
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  Data: &lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Bangladesh%22&quot;&gt;Bangladesh&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Chittagong+%28Bangladesh%29%22&quot;&gt;Chittagong (Bangladesh)&lt;/searchLink&gt;
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: As a significant aspect of global change, climate change poses substantial risks to vegetation extent and health, affecting ecosystem services and stability. While numerous studies have explored the immediate and time-lagged impacts of climatic factors on vegetation growth, there is a noticeable gap in understanding the cumulative change, which is crucial to monitoring vegetation dynamics. Furthermore, the limitations of traditional change detection methods pose a significant barrier to effectively utilizing time series approaches in remote sensing. The main aim of the study was to examine changes in vegetation composition and the potential physio-climatic drivers in the southeastern region of Bangladesh due to its diversified landscape by establishing baseline conditions and identifying shifts over time. This research employs the directional persistence technique at a regional scale on 22 years of MODIS NDVI to determine season-wise cumulative greening and browning from 2000 to 2022 by considering the initial 5-year average as the benchmark NDVI for each season. Moreover, the influence of driving forces is studied using Pearson&#39;s correlation between post-monsoon NDVI with rainfall and LST, as well as Geodetector factor analysis of NDVI with soil, elevation, LST, and rainfall. The result from these analyses identifies that the post-monsoon season has the highest significant vegetation change (combining greening and browning) with 65% of the area, followed by winter, pre-monsoon, and monsoon, whereas the highest browning season was winter. Additionally, rainfall and surface temperature show a negative correlation with NDVI. Among the spatial factors, elevation (q statistic = 0.37, p &lt; 0.001) shows the highest influence in shaping vegetation distribution, with soil types and temperature having a similar impact. Although these interactions are mutually dependent on each other, rainfall (q statistic = 0.08, p &lt; 0.001) seems to have lesser direct influence over the spatiality of vegetation. This research contributes to a deeper understanding of vegetation interactions with physiography and climate in the Chattogram region as well as provides a monitoring framework for sustainable land management in the face of ongoing climatic challenges. These findings can guide foresters, agriculturalists, ecologists, and policymakers in understanding regional vegetation dynamics and developing adaptive strategies for mitigating the adverse effects of climate alteration by integrating climate projections into land-use planning. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10668-024-05505-5
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
        StartPage: 13407
    Subjects:
      – SubjectFull: Vegetation dynamics
        Type: general
      – SubjectFull: Normalized difference vegetation index
        Type: general
      – SubjectFull: Remote sensing
        Type: general
      – SubjectFull: Rainfall
        Type: general
      – SubjectFull: Altitudes
        Type: general
      – SubjectFull: Surface temperature
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Soil classification
        Type: general
      – SubjectFull: Bangladesh
        Type: general
      – SubjectFull: Chittagong (Bangladesh)
        Type: general
    Titles:
      – TitleFull: Greening and browning trend with physio-climatic drivers in Chattogram division, Bangladesh.
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          Dates:
            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
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              Value: 28
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