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Delineation of Water Area to Enhance Fish Production Through Rs and GIS Technique in Mymensingh Region

Akter, T.
Sylhet Agicultural University, Sylhet, Bangladesh.

M. A. Salam
Bangladesh Agricultural University, Mymensingh, Bangladesh

S. Hashem
Bangladesh Agricultural University, Mymensingh, Bangladesh

Abstract/ Executive Summary:

Water availability is one of the key factors for traditional aquaculture which act as a limiting factor in most places. The rainfall is considered the main source of water for traditional aquaculture. Season wise Moderate Resolution Imaging Spectroradiometer (MODIS AQUA 250 m) images of 2001 and 2002 were used to drawing different scenarios of water availability round the year in Mymensingh region, Bangladesh. NDVI and Iso-cluster images were prepared using near infrared (NIR), mid infrared (MIR) and blue brands for interpretation and analysis. Both the NDVI and Iso-cluster images were reclassified into five land use classes. The water receding trends from rainy to spring and spring to winter season in both the NDVI and Iso-cluster images were observed. In an average 8 and 18% water areas were obtained in winter and rainy season of 2001 and 2002 images respectively. Total 345, 524 and 436 km² areas were found water logged which could be used for traditional aquaculture in winter, rainy and spring season without any water installation cost. Extracted water areas can be used to enhance fast growing fish culture in short duration. Planning should be directed to utilize the available water areas for growing fish.

Keywords: GIS, RS, Aquaculture, Water availability

Location: Mymensingh region, Bangladesh

Start Date: 00-00-2010

End Date: 00-00-2010

Program Area: Animal Health and Management

Non-commodity: GIS

Objectives:

To draw different scenarios of water availability round the year in Mymensingh region,

Methodology:

The Study Area: The study area is situated in the northern side of the country where the climate is sub tropical. Its location is in between the latitude 24°15' and 25°15' North and 90°05" and 90°50' East longitude. It consisted of 12 Upazillas, 146 Unions and 2,709 Villages. There are 8,370 ha ponds, 774 ha Pangus farm, 2817 ha beels, 5,215 ha Rivers and 48,582 ha floodplains which are used for fish culture in this district. Climate in the study area: The seasonal weather patterns in the area governed by the Southwest and the Northeast monsoon. The dry winter season starts from December to February when rainfall is infrequent. The wind blows from northeasterly direction at the beginning of the season, changes to northerly or westerly. Temperatures remain in the low twenties during the day and in the low teens at the night. The humidity gradually decreases during this season. The transitional period from March to May is termed the pre-monsoon season and is characterized by short-duration thunderstorms. The monsoon season starts from June to September characterized by heavy rainfall under the influence of Southwest monsoon, with 75% of the total annual rainfall in this period. The second transitional period is from October to November, this transitional period is termed as post monsoon since it follows the monsoon season. Data sources: The MODIS AQUA images were collected from Stirling University, Scotland. These images of different seasons were analyzed to extract availability of water in different seasons in Mymensingh district. The methodology of this study was based on Remote Sensing image interpretation which was supported by the secondary data collected from a range of sources like field visit, literature review, internet search and consultation with the relevant reports. Image analysis techniques: MODIS AQUA images of Red, NIR, MIR and Blue bands were used for this study. The spatial resolution of the images was 250 × 250 m which used in this study. Image enhancement (FCC) for visual interpretation, NDVI (Normalized Dense Vegetation Index) preparation, unsupervised image classification, etc. were also done to estimate the availability of water. Image Enhancements: The images were subject to preliminary digital enhancements in order to enable their visual interpretation. False colour composite (FCC) using the MODIS AQUA images (visible red, near infrared and infra red respectively) has been found to give a clear visual discrimination of the vegetation, water and water-bare land boundary. An associated contrast stretch of 5% was also applied to give a better visual representation. Normalized Difference Vegetation Index: The Normalized Difference Vegetation Index (NDVI) was applied to calculate the state of vegetation on the land surface for each image from the RED and MIR bands of the satellite data using equation 1. NDVI expresses the vegetated ground and the vegetation condition which is closely related to the leaf area index (LAI). The land use changes between the years were studied by NDVI ratios. Dense vegetation showed up very strongly in the imagery and areas with little or no vegetation were clearly visible. NDVI was also effective to identify water and bare land clearly. The NDVI took values between -1 to 1, the value 0.5 indicating dense vegetation and value <0 indicating no vegetation. Produced NDVI maps was reclassified in to five land use categories depending on the digital number (DN) as water, bare land, very low vegetation, moderate vegetation and high vegetation types. Unsupervised image classification: This module groups together features with similar reflectance patterns. The module used to produce unsupervised images. The logic by which unsupervised classification works is known as cluster analysis and this provided in IDRISI Andes by the ISOCLUSTER classification from the image bands of infrared, mid infrared and near infrared and this provided an interpretation of the number of spectral classes in the raw data. This was conducted in several steps. Iso-cluster was used with the option of user selecting the number of classes for the final images. The module then classified the images into discrete categories. This process was conducted using 15 fine clusters. Following the cluster, a 3 x 3 mode FILTER was carried out to eliminate small clusters with less than 9 pixels. The clusters were then identified and further reclassified into five land cover classes based on the colour composite image and field data to have the water and land use images.

Source of Information: IRJALS (ISSN: 1839-8499) | July 2012 | Vol. 1 | Issue 3, 14-26

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

It is concluded that as water is the critical factor for living organisms, therefore it’s the time to utilize our water resources in a proper way. By using rainfall water we can culture fish in our natural water bodies without any cost. For this reason it is important to find out the extent and duration of water availability. The findings of the present study will be helpful to the traditional fish farmers. A further study needs to be carried to select the suitable species of fish to culture in those water area considering water depth and duration.

Knowledge Management: Journal