Agricultural Research Management Information System

Home
Research Summary
Search
About Us
- ARMIS
- Brochure
Contact Us
Report
User Request
Data Input
Help
- Operation Manual
  - PDF
  - Video
- Program Area & Commodity
We have reached 37600 number of research entries at this moment.

- Logout

Research Detail

Home
Research
Detail

Relationship Between Boro Rice Production and Modis Derived Ndvi for Rice Production Forecasting: a Case Study on Bangladesh

BM Refat Faisal
Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-a-Bangla Nagar, Dhaka-1207, Bangladesh

Hafizur Rahman
Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-a-Bangla Nagar, Dhaka-1207, Bangladesh

Sukumar Dutta
Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-a-Bangla Nagar, Dhaka-1207, Bangladesh

Nasrin Sultana
Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-a-Bangla Nagar, Dhaka-1207, Bangladesh

Md Abu Taleb Pramanik
Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-a-Bangla Nagar, Dhaka-1207, Bangladesh

Abstract/ Executive Summary:

The present investigation illustrates an inclusive approach to extract remotely sensed Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) (AQUA/TERRA) imageries to find out a relationship with Boro rice production for forecasting crop production in the context of Bangladesh. This study utilizes AQUA/TERRA MODIS reflectance data (250 m resolution) for the month of March (Peak-greenness period) to calculate the average NDVI values by following MODIS based algorithm at district level during 2011-2016. The linear regression analysis of calculated average NDVI and BBS estimated Boro rice production statistics reveals a significant positive relationship due to maximize photosynthetic activities. Among the regression equations from (2011-2016), the highest regression coefficients R2=0.87 and R2=0.85 for AQUA and TERRA MODIS data have been found respectively in 2015. Therefore this regression equation can be used for future estimation of Boro rice production at country scale. However, further testing and simulation of this regression model is required to generate Boro rice production forecasting dataset on timely basis. Hence this study summarizes that, NDVI based regression equation may be an effective process to forecast the Boro rice production which can play an important role in decision-making process relevant to the food security issues of Bangladesh.

Keywords: Boro Rice, MODIS, NDVI, Rice Production Forecasting, Food security

Location: Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-a-Bangla Nagar, Dhaka-1207, Bangladesh

Start Date: 00-00-2011

End Date: 00-00-2016

Program Area: Knowledge Management

Non-commodity: Adoption and mitigation technology

Objectives:

The objective of this research are to a) develop a methodological framework to derive the satellite based rice crop information, and b) to find relationship between the satellite images derived Normalized Difference Vegetation Index (NDVI) and ground-based (BBS estimated) Boro rice crop production at country scale for rice production forecasting to improve the food security information of Bangladesh.

Methodology:

The study area was bounded between 20°34'and 26°38 ' North latitude and 88°01' and 92°41 ' East longitude and the territory is situated on one of the largest as well as complex deltas in the world where the Ganges, Brahmaputra, and Meghna rivers enter the Bay of Bengal. The climate of Bangladesh is sub- tropical warm, wet and humid and experiences natural disasters frequently such as excessive rainfall (floods), droughts and tropical cyclones; which creates a negative impact on agricultural yield and production. Bangladesh has three seasons: a hot or summer (March to June), a warm and humid monsoon (June to September) and a cold and dry (October to February) (Ahmed, 2006). The annual average rainfall varies from 1,500 mm to 5,000 mm; temperature and humidity ranges from 12-30°C and 65-90% (Rahman et al., 2006), respectively. In recent years, the weather pattern has become erratic as the cool and dry season have been noticeably decreased which is probably attributable to the climate change (World Bank, 2011). The satellite images of MODIS (AQUA/TERRA) have been selected for this study over the period of (2011- 2016) at the month of March (peak greenness period) as it is the Boro cropping seasons in Bangladesh. These imageries have been selected as it provides daily global imagery at spatial resolutions of 250-m (red and NIR1) and 500-m (blue, green, NIR2, SWIR1, SWIR2) and has improved atmospheric correction (Vermote and Vermeulen, 1999). These MODIS (AQUA and TERRA) imageries have been downloaded and processed by following the standard procedure in ERDAS Imagine software (ERDAS, 2017). Therefore, NDVI has been calculated for the stipulated time period by following specific Equation-1. On the other hand, the country scale ground-based Boro rice production statistics from (2011-2016) have been collected from Bangladesh Bureau of Statistics (BBS) published documents.

Source of Information: The Dhaka University Journal of Earth and Environmental Sciences, Vol. 8(1), 2019, P 33-40

Article Link (Online Journal): DOI: https://doi.org/10.3329/dujees.v8i1.50759

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

This research work focuses on the development of MODIS-NDVI based effective methods to estimate Boro rice production from remote sensing based regression equation. This study concludes that, significant positive relationship exists between the MODIS derived NDVI and Boro rice production. Hence, (TERRA/AQUA) MODIS-NDVI based regression models can be used to estimate the Boro rice production at the country scale. Hereafter, the crop production can be estimated earlier than official crop statistics which can play a vital role in the food security issues of Bangladesh. Though the regression equation needs to be simulated and validated prior to use it for crop forecasting purpose. However, more studies are required on times series analysis of MODIS-NDVI and ground-based estimated statistics based regression model to test its suitability and crop production forecasting capacity.

Knowledge Management: Journal