| Autor: |
MN Amin, Md. Abdul Mottalib, Md. Ayub Hossain, Chayan Kumer Saha, Md. Monjurul Alam |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 ASABE Annual International Virtual Meeting, July 13-15, 2020. |
| Popis: |
Sustainable agricultural development management requires strong and systematic agricultural planning of land use activities and appropriate use of modern agricultural technologies. Satellite remote sensing (RS) technology, geographical information system (GIS) and global positioning system (GPS) are powerful devices to gain accurate and timely information on the spatial distribution of land use activities for decision making of any agricultural applications. A study was carried out at two sites (Atlia union of Dumuria upazila in Khulna district and Nilganj union of Kolapara upazila in Patuakhali district) in the southern region of Bangladesh and acquisition of satellite image was captured at peak vegetation stage of crop for mapping during Rabi and Kharif-1 season of the year 2019. This article presents an innovative method to classify a land-use and land-cover (LULC) map of each area and estimate crop land area; then asses the scope of adaptability for CA planter using Sentinel-2A satellite imagery analysis. The unsupervised classification algorithm was used for RS of the LULC classification through ArcGIS 10.3.1 software. Water body was found dominant type of land use which covers about (54% and 32%) of the total area followed by fallow land areas (26% and 28%) settlement (10% and 24%), while the smallest amount was jute and mungbean field which accounts for 10% and 16% in both study areas, respectively. On the basis of this result, the quantity of CA planter was worked out as 21 and 26 numbers, respectively for next season of crop planting. The overall classification accuracy was found about 81% and 84% and with Kappa values of 0.74 and 0.79 for Atlia and Nilganj, respectively. According to standard value of Kappa, the classification results were found satisfactory and hence the classified image was found robust for further research. The results conclusively reveal that the efficiency and applicability of computer-aided spatial analysis techniques for identifying and estimating crop areas are suitable for making best decisions for appropriate modern agricultural technologies adoption, dissemination and management planning. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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