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Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh

Bangladesh, known for its remarkable ecological diversity, is faced with the pressing challenges of contemporary climate change. It is crucial to understand how vegetation dynamics respond to different climatic factors. Hence, this study aimed to investigate the spatio-temporal variations of vegetat...

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Autores principales: Das, Swadhin, Sarkar, Showmitra Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391951/
https://www.ncbi.nlm.nih.gov/pubmed/37533977
http://dx.doi.org/10.1016/j.heliyon.2023.e18412
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author Das, Swadhin
Sarkar, Showmitra Kumar
author_facet Das, Swadhin
Sarkar, Showmitra Kumar
author_sort Das, Swadhin
collection PubMed
description Bangladesh, known for its remarkable ecological diversity, is faced with the pressing challenges of contemporary climate change. It is crucial to understand how vegetation dynamics respond to different climatic factors. Hence, this study aimed to investigate the spatio-temporal variations of vegetation and their interconnectedness with a range of hydroclimatic factors. The majority of the dataset used in this study relies on MODIS satellite imagery. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), precipitation (PPT), evapotranspiration (ET), and land surface temperature (LST) data from the years 2001 to 2020 have been obtained from Google Earth Engine (GEE). In this study, the temporal variations of the NDVI, EVI, PPT, ET, and LST have been investigated. The findings of the Mann-Kendall trend test indicate noticeable trends in both the NDVI and the EVI. Sen's slope value for NDVI and EVI is 0.00424/year and 0.00256/year, respectively. Compared to NDVI, EVI has shown a stronger connection with hydroclimatic factors. In particular, EVI exhibits a better relationship with ET, as indicated by a r(2) value of 0.37 and a P-value of 6.81 × 10(−)(26), whereas NDVI exhibits a r(2) value of 0.17 and a P-value of 2.96 × 10(−)(11). Furthermore, ET can explain 17% of the fluctuation in NDVI, and no correlation between NDVI and PPT has been found. The results clarify the significant relationship between the EVI and hydroclimatic factors and highlight the efficiency of the EVI for detecting vegetation changes.
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spelling pubmed-103919512023-08-02 Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh Das, Swadhin Sarkar, Showmitra Kumar Heliyon Research Article Bangladesh, known for its remarkable ecological diversity, is faced with the pressing challenges of contemporary climate change. It is crucial to understand how vegetation dynamics respond to different climatic factors. Hence, this study aimed to investigate the spatio-temporal variations of vegetation and their interconnectedness with a range of hydroclimatic factors. The majority of the dataset used in this study relies on MODIS satellite imagery. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), precipitation (PPT), evapotranspiration (ET), and land surface temperature (LST) data from the years 2001 to 2020 have been obtained from Google Earth Engine (GEE). In this study, the temporal variations of the NDVI, EVI, PPT, ET, and LST have been investigated. The findings of the Mann-Kendall trend test indicate noticeable trends in both the NDVI and the EVI. Sen's slope value for NDVI and EVI is 0.00424/year and 0.00256/year, respectively. Compared to NDVI, EVI has shown a stronger connection with hydroclimatic factors. In particular, EVI exhibits a better relationship with ET, as indicated by a r(2) value of 0.37 and a P-value of 6.81 × 10(−)(26), whereas NDVI exhibits a r(2) value of 0.17 and a P-value of 2.96 × 10(−)(11). Furthermore, ET can explain 17% of the fluctuation in NDVI, and no correlation between NDVI and PPT has been found. The results clarify the significant relationship between the EVI and hydroclimatic factors and highlight the efficiency of the EVI for detecting vegetation changes. Elsevier 2023-07-19 /pmc/articles/PMC10391951/ /pubmed/37533977 http://dx.doi.org/10.1016/j.heliyon.2023.e18412 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Das, Swadhin
Sarkar, Showmitra Kumar
Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh
title Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh
title_full Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh
title_fullStr Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh
title_full_unstemmed Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh
title_short Spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in Bangladesh
title_sort spatio-temporal variability of vegetation and its relation to different hydroclimatic factors in bangladesh
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391951/
https://www.ncbi.nlm.nih.gov/pubmed/37533977
http://dx.doi.org/10.1016/j.heliyon.2023.e18412
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