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Variations of Ndvi and Its Association with Rainfall and Evapotranspiration Over Bangladesh

Md. Monirul Islam
Department of Applied Physics & Electronic Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh.

Md. Mainul Islam Mamun
Department of Applied Physics & Electronic Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh.

Abstract/ Executive Summary:

This paper deals with the variability of Normalized Difference Vegetation Index (NDVI) and its association with rain rate and total evapotranspiration over Bangladesh during the period of 2003-2011 using MODerate-resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM) and Global Land Assimilation System (GLDAS) data. NDVI shows higher concentration in eastern parts of the country. The maximum NDVI is found in the month of October and minimum in February. It reveals excellent periodic variation in relation to rain rate and total evapotranspiration. NDVI shows strong spatial and temporal correlation with rain rate and total evapotranspiration especially in northwestern part of the country. Total evapotranspiration is more strongly correlated with vegetation than rain rate as it integrates rainfall, temperature and soil water statistics during the entire period. Thus, NDVI is an important variable for agronomical and climate applications. Also, it is important to study the vegetation for different seasons and different agro-ecological areas to investigate the variables affecting the vegetation types and growth rate.

Keywords: NDVI, Rainfall, Total Evapotranspiration, MODIS, TRMM, GLDAS

Location: All over Bangladesh

Start Date: 00-00-2003

End Date: 00-00-2011

Program Area: Conservation and Biodiversity

Non-commodity: Rainfall

Objectives:

Objective of the study was to investigate the spatial and temporal variation of normalized difference vegetation index (NDVI) over Bangladesh and its association with rainfall and ET response to interannual variability during the last decade.

Methodology:

MODerate-resolution Imaging Spectroradiometer NDVI data is used to analyze the vegetation over Bangladesh because it indicates the greenness of the surface which always signifies the presence of green plants. MODIS sensor onboard NASA’s Terra and Aqua satellites have 36 spectral channels. NDVI is calculated from MODIS radiation data with a 5.6 × 5.6 km spatial resolution. In this paper it use MODIS-Terra 0.05^o NDVI level 3 monthly data products. MODIS provides the NDVI data with comparatively lower spatial resolution, but with a daily temporal resolution. This vegetation indices product is generated at 1^o spatial resolution from the 0.05^o Climate Modeling Grid coverage product. Tropical Rainfall Measuring Mission rain rate data is used for understanding the relationship of rainfall with vegetation. TRMM is a joint US-Japan satellite mission which is using to monitor the precipitation over tropical and subtropical areas. TRMM 3B43 V7 rainfall data product is used in this paper. 3B43 is used to produce the best estimation of rain rate in mmhr^-1. It is version 7 data product with a spatial resolution of 25^o × 25^o. In this paper it used the Global Land Assimilation System (GLDAS) for total evapotranspiration data which is simulated by the National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic research Lab (NOAH) model. GLDAS is generating various land surface state and flux parameters from various land surface models. The GLDAS data has spatial resolution of 0.25^o and 1^o, temporal resolution of 3-hourly and monthly, latitude extent between -60^o to 90^o and longitude extent between -180^o to 180^o. NOAH is 1-D column model which can be executed in either coupled or uncoupled mode. The model uses finite-difference spatial discretization methods with a Crank-Nicholson time integration scheme for numerical integration of the governing equations of physical processes of the soil-vegetation-snowpack medium. Monthly GLDAS NOAH10 M.001 data product is used which has a spatial resolution of 0.25^o.

Source of Information: Rajshahi University Journal of Science & Engineering, Vol. 43: 21-28, 2015; ISSN 2309-0952

Article Link (Online Journal): http://www.banglajol.info/index.php/RUJSE/article/download/26160/17589

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Spatial and temporal variations of vegetation are observed over Bangladesh. Eastern parts of the country show higher NDVI. The maximum NDVI is in October and minimum in February. The NDVI shows a good correlation with both rain rate and total evapotranspiration. It shows a good interannual periodic variation with rain rate and total evapotranspiration. NDVI is higher during good rainfall receiving months while it is lower during low rainfall receiving winter months. The vegetation increases with both rain rate and total evapotranspiration. The Northwestern parts of Bangladesh reveal highest spatial correlation of NDVI with rain rate and total evapotranspiration. NDVI show its highest spatial correlation with rain rate in northern Rajshahi division while with total evapotranspiration in northern Rangpur division. The higher rainfall receiving areas show lower correlation between NDVI and rain rate. The scatter plots report that the correlation coefficient of NDVI with rain rate is 0.37 and with total evapotranspiration is 0.58. Vegetation is positively associated with both rain rate and total evapotranspiration in every year during the study period. The highest correlation coefficients of NDVI with rain rate are 0.54 in 2007 and with total evapotranspiration is 0.72 in 2004. Total evapotranspiration shows best agreement with NDVI in correspondence with rain rate, possibly due to the fact that this variable integrates information of rainfall, temperature and water content of soil. This study is an attempt to analyze and monitor the relationships between vegetation, rainfall and evapotranspiration which can be consider a good step toward the study of climate-soil-vegetation dynamics over Bangladesh.

Knowledge Management: Journal