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

Fattah, Md. Abdul; Morshed, Syed Riad

doi:10.1007/s00704-022-03943-7

Cited by 12 publications

(11 citation statements)

References 59 publications

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“…The monsoons are caused by differences in air pressure caused by the differential heating of land and sea in Bangladesh. Annual rainfall has ranged between 32,800 mm and 47,800 mm per year over the last 50 years (Fattah and Morshed, 2022). Dhaka, the capital city of Bangladesh (Figure 1), is one of the fastest-growing megacities in the world and has been chosen as a study area in this research.…”

Section: Study Areamentioning

confidence: 99%

“…351 1.437 H (2) .242 H(3) -.012 H (4) .027 H (5) -.018 H (6) -.011 H (7) .007 H (8) .748 H(9) -3.852 H (10) -16.762 a. Displays the center vector for each hidden unit.…”

Section: Function Of Hidden Layer In Parameter Estimatesmentioning

confidence: 99%

“…The input layer work as the container of input variables, radial layer contains the function of the radial basis. The output layer is linked with the radial basis nodes by linear weights and shows the output of the problem (Mustafa et al 2012).In Figure6, the notation SO2, PM2.5, PM10, O3, NOx, NO, NO2, CO, …... V_wind_speed represents the input layers, H(1), H(2), H(3),….. H(10) represents the hidden layers contains the radial basis function, and the Rain is the output layer. If we represent the output as R, the relation between the input variables and output for the i th radial basis layer of the RBFNN model is as follows:…”

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confidence: 99%

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Multilayer perception and radial basis function models for predicting trends of rainfall in Asian megacity Dhaka, Bangladesh

Towfiqul

Pal

Chakrabortty

et al. 2022

Preprint

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Rainfall prediction is a fascinating topic, particularly in an urban city experiencing climate change; it is also required for hydrologic system analysis and design. Most real-time rainfall prediction algorithms use conceptual models that simulate the hydrological cycle in a changing climate. However, calibration of “conceptual” or “physically based models” is typically challenging and time-consuming due to the large number of variables and factors. Simpler “artificial neural network (ANN)” predictions may thus seem promising. To this end, this study aimed to evaluate the performance of two of the most commonly used ANN models, namely “Multilayer Perception (MLP)” and “Radial Bias Function (RBF)”, by predicting the rainfall trend patterns in the mega city of Dhaka, Bangladesh. In this perspective, rainfall is considered as a dependent variable and the rest of the parameters are considered as independent variables for predicting the trends of rainfall in this region. In the prediction models, fifteen conditioned atmospheric and meteorological parameters were used, and the multi-collinearity of these parameters was checked by the “Variance Inflation Factor” and “Tolerance” methods. The performance of the ANN models was evaluated by comparing the predicted and residuals and also by using AOC and ROC curves. The importance study from the MLP model revealed that PM10, O3, PM2.5, NOx, and wind speed are the highest causal factors influencing the rainfall changes in Dhaka, Bangladesh. Though both ANN models produced similar robustness in rainfall prediction, results showed that MLP performed well with an AUC value of 0.941, compared to the RBF model with an AUC value of 0.915. Therefore, the application of the MLP model can be suggested as an alternative to predict the pattern of rainfall as well as meteorological and atmospheric variables based on historical recorded datasets.

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Section: Study Areamentioning

confidence: 99%

“…351 1.437 H (2) .242 H(3) -.012 H (4) .027 H (5) -.018 H (6) -.011 H (7) .007 H (8) .748 H(9) -3.852 H (10) -16.762 a. Displays the center vector for each hidden unit.…”

Section: Function Of Hidden Layer In Parameter Estimatesmentioning

confidence: 99%

mentioning

confidence: 99%

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Multilayer perception and radial basis function models for predicting trends of rainfall in Asian megacity Dhaka, Bangladesh

Towfiqul

Pal

Chakrabortty

et al. 2022

Preprint

Self Cite

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“…Recent decades have seen a significant increase in humidity, rainfall, and temperature due to climatic changes brought on by human activity on a regional and global scale (Kalisa, Igbawua, & Henchiri, 2019). Rapid global vegetation cover change during the past few decades has had an impact on ecology, biodiversity as well as to the environment (Morshed & Fattah, 2021;Fattah & Morshed, 2022). These expected effects pose a threat to the persistence and long-term expansion of vegetation in fragile places, particularly in climatically delicate and vulnerable regions (Fattah & Morshed, 2022).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variability of Climatic Factors in Response to Vegetation Cover Change In Bangladesh

Rimi,

Hossain

2024

Preprint

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Climate change and its impact on environment is become the hot topic in the world. Bangladesh is a highly populated developing and agro-based economic country. Impact of several climatic factors such as rainfall, air temperature, humidity on agriculture is immense. But changes found in the trend of these climatic factors in here. This research aimed to detect the trend of three climatic factors, rainfall, temperature, and humidity over last 42 years (1981–2022) and along this, to explore the relation between vegetation coverage and climatic factors. The entire analysis is conducted for Upazilla level in Bangladesh. Maan-Kendal Test and Sen slope estimation is followed to detect the trend of three climatic factors and multiple regression model, Geographically Weighted Regression (GWR) Model and Ordinary Least Square (OLS) Regression Model is applied to explore the relationship between vegetation coverage and climatic factors. Positive trend is found for rainfall (24–147 mm/year) and humidity (0.16% − 0.47%) but negative trend is detected for temperature (− 0.03 to 0.00 ℃) for some Upazilla in Bangladesh. By GWR model, ranges of very weak to weak influence of vegetation coverage on the climatic factors are found for most of the Upazilla in Bangladesh. From the results of OLS, very strong correlation is found between the change rate of vegetation coverage and climatic factors for most of the Upazilla in Bangladesh especially the Upazilla of Sylhet and Chittagong Division. As Upazilla Master Plan is initiated in Bangladesh for each Upazilla, the outcomes of this research will help the policy makers to take the suitable plan for environment as well as agricultural development for each Upazilla through which sustainable development can be ensured.

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“…Changes in land use and land cover (LULC) can affect and can be affected by climate. At various temporal and spatial dimensions, these changes interact; however, improper LULC change is the primary reason for climate change ( Thakur et al., 2019 ; Mondal et al., 2021a , b ; Fattah and Morshed 2022 ). The problem is most prominent in urban areas, especially in emerging cities.…”

Section: Introductionmentioning

confidence: 99%

A GIS and remote sensing approach for measuring summer-winter variation of land use and land cover indices and surface temperature in Dhaka district, Bangladesh

Sresto¹,

Siddika²,

Fattah³

et al. 2022

Heliyon

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

Cited by 12 publications

References 59 publications

Multilayer perception and radial basis function models for predicting trends of rainfall in Asian megacity Dhaka, Bangladesh

Multilayer perception and radial basis function models for predicting trends of rainfall in Asian megacity Dhaka, Bangladesh

Spatiotemporal Variability of Climatic Factors in Response to Vegetation Cover Change In Bangladesh

A GIS and remote sensing approach for measuring summer-winter variation of land use and land cover indices and surface temperature in Dhaka district, Bangladesh

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