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Estimation of Potato Yield in and Around Munshigonj Using Remote Sensing and GIS Techniques

Sujit Kumar BALA
Bangladesh University of Engineering and Technology, Bangladesh

Mohammad ALI
Bangladesh University of Engineering and Technology, Bangladesh

A.K.M. Saiful ISLAM
Bangladesh University of Engineering and Technology, Bangladesh

Abstract/ Executive Summary:

Monitoring of crop growth and forecasting its yield well before harvest is very important for crop and food management. Remote sensing images are capable of identifying crop health as well as predicting its yield. Normalized Difference Vegetation Index (NDVI) calculated from remote sensing images has been widely used to monitor crop growth and relate to crop yield. This study used 16-days Terra MODIS data for 2006 to estimate the yield of potato in Munshigonj area of Bangladesh. This satellie data has been validate using ground truthing in 50 farmers field and phenological growth of potato has been studied using NDVI metrics. Regression model was developed between NDVI and field level potato yield collected from Department Agriculture Extension (DAE) for 6 upazillas of Munshigonj during 2006. The results showed that there is significant correlation (R²=0.76) between remotely sensed NDVI and field level potato yield. Hence, remotely sensed NDVI data may be an effective tool for early prediction of potato yield

Keywords: NDVI, NDVI Metrics, Potato yield, Terra MODIS, Upazilla

Location: Munshiogonj, Dhaka

Start Date: 03-12-2005

End Date: 06-03-2006

Program Area: Knowledge Management

Non-commodity: GIS

Objectives:

Objective of the study was to estimate potato yield in and around Munshigonj district using TERRA MODIS 16-days NDVI data. Spatial and temporal pattern of the potato productivity in and around Munshigonj district was also studied and a relationship was established between NDVI of potato crop and yield of potato.

Methodology:

The field study area is located at Munshigonj sadar between 90°28´ E to 90°36´ E and 23°36´ N to 23°22´ N, while the study was conducted covering the whole Munshigonj district of Bangladesh. The area is covered with different soils. As per soil structure, three types of soil are in the Munshiogonj district. Heavy loamy soil prevails over the major part of the study area. Heavy clayey soil occupies the second position in the Munshigonj area, while light clayey soil prevails over a smaller area. Agriculture is the main activity in the study area. The area is characterized by two growing seasons. The main growing season (potato) starts in November and ends in April (Rabi). Satellite: Field and Secondary Data Satellite images used for this study include MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid images taken from 3rd December 2005 to 6th March 2006 in total 9 images. The image is the input for product generation for several of the land products including Vegetation Indices (VIs), Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI). The image is a composite using sixteen consecutive daily images. The “best” observation during each sixteen day period, for every cell in the image, is retained. Data on crop information was collected from Department of Agricultural Extension (DAE) at Munshigonj Upazila sadar from 1993 to 2006. GPS was used for positioning and receiving data from satellite for on field digitizing and truthing. Fifty numbers of farmer’s fields were digitized using Hand GPS to collect primary data. Selection of farmer’s field was made in three remote ends of the study field (Munshigonj sadar) during 2005–2006. The phenological growth stage of potato was ascertained through these ground measurements. Tools and Techniques: ERDAS Imagine 8.4 and ArcGIS 9.0 software were used for image processing and spatial analyzing. Tera MODIS images are not geo-referenced and provided in a rectangular gird. Using ERDAS imagine, Terra MODIS images were geo-referenced to Lambert Conformal Conic projections with GCS_Indian (Bangladesh) reference system. Finally, geo-referenced data has been re-sampling using nearest neighbour method. Each cell value of the image represents a 16- day average Normalized Difference Vegetation Index, or NDVI. The difference between the nearinfrared (Band2) and the visible – red (Band1) bands, over their sum is called NDVI. Value of band 1 for Terra MODIS vary from 0.62-0.67 μm, while for band2 from 0.841-0.876 μm. The formula for computing NDVI is as follows: NDVI = (Band 2 Band1)/(Band 2 + Band1) (1) NDVI value of zero means no green vegetation and close to +1 (0.8 - 0.9) indicates the highest possible density of green leaves. Finally this processed NDVI data are analysed spatially using ArcGIS spatial analysis tool (Zonal Statistics, Extractions, Condition, etc.).

Source of Information: International Conference on Water & Flood Management (ICWFM-2007) 12 - 14 March 2007, BUET, Dhaka, Bangladesh

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The study has developed phenological stages of potato for the study area of Munshigonj district and derived its growth metrics. This growth metrics can be very helpful to study the behaviour of potato in the study area. This study also developed a linear regression model to predict yield from NDVI. Regression model shows a good correlation (R²=0.76) between NDVI and yield of potato. Hence, it like to conclude that 16-day average NDVI data from Tera MODIS can be successfully used to predict yield of potato with fairly good accuracy.

Knowledge Management: Report/Proceedings