Integrated Application of Remote Sensing and GIS in Crop Information System—A Case Study on Aman Rice Production Forecasting Using MODIS-NDVI in Bangladesh

B M Refat Faisal,Nur Hossain Sharifee,Nasrin Sultana,S M Ahsan Habib,Hafizur Rahman,Mohammad Imrul Islam,Tofayel Ahammad

doi:10.3390/agriengineering2020017

Abstract

This research work studies the integrated application of satellite Remote Sensing (RS) and Geographic Information System (GIS) for the monitoring and forecasting of rice crop (Aman) production in Bangladesh. Normalized Difference Vegetation Index (NDVI) images of Terra MODIS products MOD13A1 (h25v06 and h26v06) with 500 m spatial resolution, composed using Maximum Value Composite (MVC) techniques, were used to cover Bangladesh for the period of 2011–2017. Country scale NDVI (district-wise summation) was calculated pixel-by-pixel to draw a regression curve while using Bangladesh Bureau of Statistics (BBS) estimations of Aman production for the months of September–November. The regression study of district-wise pixel-based summation of MODIS-NDVI and ground-based BBS-estimated Aman production shows a strong correlation (R2 = 0.54–0.78); for the months of September and October, most of the regression coefficient indicates significant correlation due to maximum photosynthetic activities. Therefore, based on the highest regression coefficient value of September and October, Aman Crop Production (ACP) models were developed and the ACP Model-2 was exploited (from the derived set of coefficient values) to acquire year-wise rice production for all the years (2011–2017). The simulated ACP Model-2 demonstrates good agreement between the estimated and predicted yearly Aman rice production for the 2011–2017 time period with Mean Bias Error (MBE) = (−9435 to 23,156) M.Ton; Root Mean Square Error (RMSE) = 253–4426 M.Ton; Model Efficiency (ME) = (0.89–0.93); and, Correlation Coefficients = (0.72–0.94). Hence, the MODIS–NDVI-based regression model seems to be effective for Aman crop production forecasting in the context of food security issues in Bangladesh. The applied system is simple, rationally accurate, and fit for the generation of nationwide crop statistics.

Highlights

Rice production is of essential importance in Bangladesh and in the context of economy and food security issues [1], where the grain solely occupies 76.7% of total area under cultivation [2]
The present study focuses on Normalized Difference Vegetation Index (NDVI), because it is widely used in phenological works [25,26,27] and it is known to be more sensitive to small increases in the amount of photosynthetic vegetation [28,29]
The maximum NDVI values can be found during peak greenness period of crop life cycle, which is around the month of October

Summary

Introduction

Rice production is of essential importance in Bangladesh and in the context of economy and food security issues [1], where the grain solely occupies 76.7% of total area under cultivation [2]. Aman or monsoon rice) is grown from July to December, mostly under rain-fed conditions [3]. Monsoon rains are very important for the Aman crop, which is harvested in November/December. A maximum amount of Aman is transplanted between the end of June to mid-August, planting can occur as late as the last week of September and harvested in November/December [5]. In view of the above, early assessment of Aman crop production in the context of Bangladesh is very important due to food security issues

Objectives

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Results

Conclusion