Skip to main content

Advertisement

SpringerLink
Log in

Assessment of the responses of spatiotemporal vegetation changes to climatic variability in Bangladesh

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Understanding the effects of vegetative land cover in Bangladesh on climatic variability and dynamics is still a critical issue for environmental sustainability as well as global and regional climate policy formulation. This study aimed to gain a better understanding of the responses of vegetation changes and built-up area changes to climatic variability in Bangladesh during 1990–2020. Based on the Normalized Difference Vegetation Index (NDVI) dataset, we analyzed the spatiotemporal characteristics of vegetation dynamics and the proportion of urban land changes across all the urban and rural areas of Bangladesh and investigated the relationships between the variability of temperature, precipitation, and humidity through Pearson’s correlation (PC) and geographically weighted regression (GWR) models. This study found complex variations in growing-season NDVI and climatic factors across the country. The results indicate a declination of vegetation areas and precipitation, with an increase in built-up areas (12.60% in urban and 11.68% in rural areas), temperature, and humidity. The correlation between growing-season NDVI and climatic factors demonstrates a strong inverse influence of temperature up to − 0.78; and positive influences of rainfall up to + 0.51 and humidity up to + 0.06, but in the case of built-up area changes, temperature change is positively correlated, while rainfall and humidity are negatively correlated to built-up expansion. Findings suggest that climatic factors are more responsive to built-up land expansion than vegetation dynamics in the urban and rural areas of Bangladesh. The unplanned development activities would persist and continue to affect the environment and sustainability. This study provides policymakers and the Bangladesh government with critical information on environmental development and sustainability improvements that will lead to the long-term sustainability of natural resources and environmental health.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Availability of data and material

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Will be available on reasonable request.

References

  • Abir, F.A., Ahmmed, S., Sarker, SH, Fahim, AH. (2021) Thermal and ecological assessment based on land surface temperature and quantifying multivariate controlling factors in Bogura, Bangladesh. Heliyon, 7(9). https://doi.org/10.1016/j.heliyon.2021.e08012

  • Ahasan MN, Chowdhary Md AM, Quadir DA (2010) Variability and trends of summer monsoon rainfall over Bangladesh. J Hydrol Meteorol 7(1):1–17

    Article  Google Scholar 

  • Alamgir M, Shahid S, Hazarika MK, Nashrrullah S, Harun SB, Shamsudin S (2015) Analysis of meteorological drought pattern during different climatic and cropping seasons in Bangladesh. J Am Water Resour Assoc 51:794–806

    Article  Google Scholar 

  • Ameen RF, Mourshed M (2017) Urban environmental challenges in developing countries. A Stakeholder Perspective Habitat International 64:1–10

    Article  Google Scholar 

  • Amera, A. M., & Tefera, B. (2013). The role of environmental impact assessment for sustainable development. IAIA13 Conference At: Calgary Stampede BMO Centre, 33. Calgary, Alberta, Canada.

  • Barros VR, Field CB (2014) Climate Change 2014: Impacts, adaptation, and vulnerability. Part B: Regional Aspects; Cambridge University Press: Cambridge, UK, 2014

  • Chen T, Ren L, Yuan F, Yang X, Jiang S, Tang T, Liu Y, Zhao C, Zhang L (2017) Comparison of Spatial Interpolation Schemes for Rainfall Data and Application in Hydrological Modeling. Water 9(5):342. https://doi.org/10.3390/w9050342

  • Choubin, B., Soleimani, F. et al. (2019) Effects of drought on vegetative cover changes: investigating spatiotemporal patterns. Extreme Hydrology and Climate Variability. 213-222. https://doi.org/10.1016/B978-0-12-815998-9.00017-8

  • Chikoore H, Jury MR (2010) Intraseasonal variability of satellite-derived rainfall and vegetation over Southern Africa. Earth Interact 14:1–26. https://doi.org/10.1175/2010EI267.1

    Article  Google Scholar 

  • Curtarelli M, Leão J, Ogashawara I, Lorenzzetti J, Stech J (2015) Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management. ISPRS Int J Geo-Information 4(1):220–235. https://doi.org/10.3390/ijgi4010220

  • Endo N, Matsumoto J, Hayashi T, Terao T, Murata F, Kiguchi M, Yamane Y, Alam S (2015) Trends in precipitation characteristics in Bangladesh from 1950 to 2008. SOLA 11:113–117. https://doi.org/10.2151/sola.2015-027

    Article  Google Scholar 

  • Engelbrecht CJ, Engelbrecht FA, Dyson LL (2013) High-resolution model-projected changes in mid-tropospheric closed-lows and extreme rainfall events over southern Africa. Int J Clim 33:173–187. https://doi.org/10.1002/joc.3420

    Article  Google Scholar 

  • Escobedo F, Nowak D (2009) Spatial heterogeneity and air pollution removal by an urban forest. Landsc Urban Plan 90(3–4):102–110

    Article  Google Scholar 

  • Fabricante I, Oesterheld M, Paruelo JM (2009) Annual and seasonal variation of NDVI explained by current and previous precipitation across Northern Patagonia. J Arid Environ 73: 745e753. https://doi.org/10.1016/j.jaridenv.2009.02.006

  • Faisal AA et al (2021) Assessing and predicting land use/land cover, land surface temperature and urban thermal field variance index using Landsat imagery for Dhaka Metropolitan area. Environmental Challenges 4:100192. https://doi.org/10.1016/j.envc.2021.100192

    Article  Google Scholar 

  • Fattah M, Morshed SR, Morshed SY (2021a) Multi-layer perceptron-Markov chain-based artificial neural network for modelling future land-specific carbon emission pattern and its influences on surface temperature. SN Appl Sci 3:359. https://doi.org/10.1007/s42452-021-04351-8

    Article  Google Scholar 

  • Fattah M, Morshed SR, Morshed SY (2021b) Impacts of land use-based carbon emission pattern on surface temperature dynamics: experience from the urban and suburban areas of Khulna, Bangladesh. Remote Sensing Applications: Society and Environment 22:100508. https://doi.org/10.1016/j.rsase.2021.100508

    Article  Google Scholar 

  • Fotheringham AS, Brunsdon C, Charlton M (2003) Geographically weighted regression: the analysis of spatially varying relationships. John Wiley & Sons

    Google Scholar 

  • Fu Y et al (2013) Assessment impacts of weather and land use/land cover (LULC) change on urban vegetation net primary productivity (NPP): a case study in Guangzhou. China Remote Sensing 5(8):4125–4144

    Article  Google Scholar 

  • Gaughan AE, Waylen PR (2012) Spatial and temporal precipitation variability in the Okavangoe-Kwandoe-Zambezi catchment. Southern Africa. J Arid Environ. 82:19e30

    Google Scholar 

  • Georganos S, Abdi AM, Tenenbaum DE, Kalogirou K (2017) Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression. J Arid Environ 146(64–74). https://doi.org/10.1016/j.jaridenv.2017.06.004

  • Ghose B, Islam ARMT, Kamruzzaman M, Moniruzzaman M, Hu Z (2021) Climate-induced rice yield anomalies linked to large-scale atmospheric circulation in Bangladesh using multi-statistical modeling. Theor Appl Climatol 144:1077–1099. https://doi.org/10.1007/s00704-021-03584-2

    Article  Google Scholar 

  • Hasan S et al (2017) Projections of future land use in Bangladesh under the background of baseline, ecological protection and economic development. Sustainability 9(4):505

    Article  Google Scholar 

  • Hasan MK, Kumar L (2020) Perceived farm-level climatic impacts on coastal agricultural productivity in Bangladesh. Clim Change 161:617–636. https://doi.org/10.1007/s10584-020-02708-3

    Article  Google Scholar 

  • Hossain MS et al (2019) Climate change and crop farming in Bangladesh: an analysis of economic impacts. Climate Change and Crop Farming in Bangladesh: an Analysis of Economic Impacts 11(3):424–440. https://doi.org/10.1108/IJCCSM-04-2018-0030

    Article  Google Scholar 

  • Hu M, Li Z, Wang J, Jia L, Liao Y, Lai S, Guo Y, Zhao D, Yang W (2012) Determinants of the incidence of hand, foot and mouth disease in China using geographically weighted regression models. PLoS One 7:e38978

    Article  Google Scholar 

  • Igbawua T, Zhang J, Chang Q et al (2016) Vegetation dynamics in relation with climate over Nigeria from 1982 to 2011. Environ Earth Sci 75:518. https://doi.org/10.1007/s12665-015-5106-z

    Article  Google Scholar 

  • Islam, ARMT; Islam, HMT et al. (2021) Spatiotemporal nexus between vegetation change and extreme climatic indices and their possible causes of change. Journal of Environmental Management. 289 (112505). https://doi.org/10.1016/j.jenvman.2021.112505

  • Jammes, S.C., Fritz, H. Murindagomo, F. (2006) Spatial patterns of the NDVI–rainfall relationship at the seasonal and interannual time scales in an African savanna. International Journal of Remote Sensing. 27(23). https://doi.org/10.1080/01431160600702392

  • Jenerette G, et al (2011). Ecosystem services and urban heat riskscape moderation: water, green spaces, and social inequality in Phoenix, USA. Ecological Applications, 21(7)

  • Jin K, Wang F, Li P (2018) Responses of vegetation cover to environmental change in large cities of China. Sustainability 10(1):270. https://doi.org/10.3390/su10010270

    Article  Google Scholar 

  • Kalisa W, Igbawua T, Henchiri, M et al (2019) Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015. Sci Rep 9(1). https://doi.org/10.1038/s41598-019-53150-0

  • Khan MJU, Islam AS, Das MK, Mohammed K, Bala SK, Islam GT (2019a) Observed trends in climate extremes over Bangladesh from 1981 to 2010. Clim Res 77(1):45–61

    Article  Google Scholar 

  • Khan MJU, Islam AKMS, Bala SK, Islam GMT (2020) Changes in climate extremes over Bangladesh at 1.5 °C, 2 °C, and 4 °C of global warming with high- resolution regional climate modeling. Theor Appl Climatol 140:1451–1466. https://doi.org/10.1007/s00704-020-03164-w

    Article  Google Scholar 

  • Kafy A-A, et al (2020). Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh. Remote Sensing Applications: Society and Environment, 18(2)

  • Kafy AA, Rakib AA et al (2021) Monitoring the effects of vegetation cover losses on land surface temperature dynamics using geospatial approach in Rajshahi City, Bangladesh. Environmental Challenges 4(100187). https://doi.org/10.1016/j.envc.2021.100187

  • Kamruzzaman M et al (2019) Future changes in precipitation and drought characteristics over Bangladesh under CMIP5 climatological projections. Water 11(11):2219

    Article  Google Scholar 

  • Li H, Li Y, Gao Y, Zou C, Yan S, Gao J (2016) Human Impact on Vegetation Dynamics around Lhasa Southern Tibetan Plateau China. Sustainability 8(11):1146. https://doi.org/10.3390/su8111146

  • Li S, Zhang J, Zhang S, Bai Y, Cao D, Cheng T, Sun Z, Liu Q, Sharma TPP (2021) Impacts of Future Climate Changes on Spatio-Temporal Distribution of Terrestrial Ecosystems over China. Sustainability 13(6):3049. https://doi.org/10.3390/su13063049

  • Ly S, Charles C, Degré A (2011) Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments Belgium. Hydrol Earth Syst Sci 15(7):2259–2274. https://doi.org/10.5194/hess-15-2259-2011

  • Mahmud K, Saha S, Ahmad T, Satu US (2018) Historical trends and variability of temperature extremes in two climate vulnerable regions of Bangladesh. J Bangladesh Agric Univ 16:283–292

    Article  Google Scholar 

  • Mallick J, Islam ARMT, Ghose B et al (2022) Spatiotemporal trends of temperature extremes in Bangladesh under changing climate using multi-statistical techniques. Theor Appl Climatol 147(1–2):307–324. https://doi.org/10.1007/s00704-021-03828-1

    Article  Google Scholar 

  • Martiny N, Camberlin P, Richard Y, Philippon N (2006) Compared regimes of NDVI and rainfall in semi-arid regions of Africa. Int J Remote Sens 27:5201e5223. https://doi.org/10.1080/01431160600567787

  • Mojid MA, Parvez MF, Mainuddin M, Hodgson G (2019) Water table trend—a sustainability status of groundwater development in North-West Bangladesh. Water 11(6):1182. https://doi.org/10.3390/w11061182

    Article  Google Scholar 

  • Mondol MAH, Mamun A, Iqbal M, Jang DH (2018) Precipitation concentration in Bangladesh over different temporal periods. Advances in Meteorology. 2018 (1849050). https://doi.org/10.1155/2018/1849050

  • Morshed, S.R., Fattah, M.A., Haque, M.N., Morshed, S.Y. (2021) Future ecosystem service value modeling with land cover dynamics by using machine learning based artificial neural network model for Jashore city, Bangladesh. Physics and Chemistry of the Earth, Parts A/B/C. 103021. https://doi.org/10.1016/j.pce.2021.103021

  • Mukhopadhyay A et al (2018) Land Cover and Land Use Analysis in Coastal Bangladesh. In: Nicholls R, Hutton C, Adger W, Hanson S, Rahman M, Salehin M (eds) Ecosystem services for well-being in deltas. Palgrave Macmillan, Cham, pp 367–381

    Chapter  Google Scholar 

  • NASA Earth Observatory (2020) Measuring vegetation (NDVI & EVI). [Online] Available at: https://earthobservatory.nasa.gov/features/MeasuringVegetation. Accessed 20 Dec 2021

  • Ndayisaba F, Guo H, Bao A, Guo H, Karamage F, Kayiranga A (2016) Understanding the spatial temporal vegetation dynamics in Rwanda. Remote Sens 8:129. https://doi.org/10.3390/rs8020129

    Article  Google Scholar 

  • Nzabarinda V, Bao A, Xu W, Uwamahoro S, Udahogora M, Umwali ED, Nyirarwasa A, Umuhoza J (2021) A spatial and temporal assessment of vegetation greening and precipitation changes for monitoring vegetation dynamics in climate zones over Africa. ISPRS Int J Geo-Inf 10:129. https://doi.org/10.3390/ijgi10030129

    Article  Google Scholar 

  • Rahman MR, Lateh H (2017) Climate change in Bangladesh: a spatio-temporal analysis and simulation of recent temperature and rainfall data using GIS and time series analysis model. Theoret Appl Climatol 128(1–2):27–41

    Article  Google Scholar 

  • Rahman MA, Yunsheng L, Sultana N (2016) Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman’s rho tests and ARIMA model. Meteorol Atmos Phys 129:409–424. https://doi.org/10.1007/s00703-016-0479-4

    Article  Google Scholar 

  • Salam R, Islam ARMT, Pham QB, Dehghani M, Al Ansari N, Linh NTT (2020) The optimal alternative for quantifying reference evapotranspiration in climatic sub-regions of Bangladesh. Sci Rep 10(1):20171. https://doi.org/10.1038/s41598-020-77183-y

    Article  Google Scholar 

  • Shahid S, Wang XJ, Harun SB et al (2016) Climate variability and changes in the major cities of Bangladesh: observations, possible impacts and adaptation. Reg Environ Change 16:459–471. https://doi.org/10.1007/s10113-015-0757-6

    Article  Google Scholar 

  • Sun J et al (2011) NDVI indicated characteristics of vegetation cover change in China’s metropolises over the last three decades. Environ Monit Assess 179:1–14

    Article  Google Scholar 

  • Udelhoven T, Stellmes M, del Barrio G, Hill J (2009) Assessment of rainfall and NDVI anomalies in Spain (1989e1999) using distributed lag models. Int J Remote Sens. 30:1961e1976. https://doi.org/10.1080/01431160802546829

    Article  Google Scholar 

  • Vrieling A, De Leeuw J, Said MY (2013) Length of growing period over Africa: variability and trends from 30 years of NDVI time series. Remote Sens. 5:982e1000. https://doi.org/10.3390/rs5020982

    Article  Google Scholar 

  • Wang T, Kou X, Xiong Y, Mou P, Wu J, Ge J (2010) Temporal and spatial patterns of NDVI and their relationship to precipitation in the Loess Plateau of China. Int. J. Remote Sens. 31:1943e1958. https://doi.org/10.1080/01431160902929263

    Article  Google Scholar 

  • Wang J et al (2008) Assessing vegetation dynamics impacted by climate change in the southwestern karst region of China with AVHRR NDVI and AVHRR NPP time-series. Environ Geol 54:1185–1195

    Article  Google Scholar 

  • Xu X, Shrestha S, Gilani H et al (2020) Dynamics and drivers of land use and land cover changes in Bangladesh. Reg Environ Chang 20(2). https://doi.org/10.1007/s10113-020-01650-5

  • Zhang B, Cao J, Bai Y et al (2013) Effects of rainfall amount and frequency on vegetation growth in a Tibetan alpine meadow. Clim Change 118:197–212. https://doi.org/10.1007/s10584-012-0622-2

    Article  Google Scholar 

  • Zheng K et al (2019) Impacts of climate change and human activities on grassland vegetation variation in the Chinese Loess Plateau. Sci Total Environ 660:236–244

    Article  Google Scholar 

  • Zhou L et al (2001) Variation in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. J Geophys Res Atmos 106(D17):20069–20084

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to Md. Esraz-Ul-Zannat, Assistant Professor, Department of Urban and Regional Planning, for his help regarding the improvement of the quality of the manuscript. We are very much thankful to the employees of the Bangladesh Meteorological Department for providing climatic data. Finally, the authors are very much grateful to the two respected reviewers for their constructive comments, which helped us to improve the quality and readership of this study.

Author information

Authors and Affiliations

  1. Department of Urban and Regional Planning, Khulna University of Engineering and Technology, Khulna, Bangladesh

    Md. Abdul Fattah & Syed Riad Morshed

Authors
  1. Md. Abdul Fattah
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Syed Riad Morshed
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization; writing—original draft preparation; resources; graphs and charts writing—review and editing (Md. Abdul Fattah). Formal analysis and investigation, methodology (Syed Riad Morshed).

Corresponding author

Correspondence to Md. Abdul Fattah.

Ethics declarations

Ethics approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fattah, M., Morshed, S.R. Assessment of the responses of spatiotemporal vegetation changes to climatic variability in Bangladesh. Theor Appl Climatol 148, 285–301 (2022). https://doi.org/10.1007/s00704-022-03943-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-022-03943-7

Search

Navigation