Mapping the "BORO Season" paddy cultivation area in Bangladesh form 2011 to 2017 using multi-temporal MODIS IMAGERY | |
| Author | Rahman, Mizanur |
| Call Number | AIT Thesis no.RS-20-06 |
| Subject(s) | Time-series analysis--Data processing Crops--Remote sensing--Bangladesh--2011-2017 |
| Note | A thesis submited in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | Knowledge on paddy and spatial appropriation of paddy fields is required for carbon pollution assessment, water management managers and food safety. Boro paddy fields are defined as the fundamental time of flooding and transplantation during the relevant period by surface water and paddy crops. The Moderate Resolution Imaging Spectroradiometer (MODIS) data sensor was being used since it has shortwave infrared bands, near infrared bands and visible bands. The Enhanced Vegetation Index (EVI) Land Surface Water Index (LSWI) has been estimated to be immune to soil moisture and leaf water quality. In this analysis, the LSWI+0.01 > EVI paddy area monitoring method was implemented and used time series vegetation indices (EVI and LSWI) generated from the MODIS data to detect the primary stages of flooding and transplantation in paddy fields. Algorithms used to delineate paddy fields at district level in Bangladesh using 8-day MODIS Surface Reflectance composites. During the Boro paddy season, the selected threshold value was applied to the mapping paddy area in Bangladesh. Boro seasonal paddy transplantation durations have been identified as 329-65 DAYs of every year. A total of 13 MODIS 8-day composite images were also used to produce the Boro season paddy production area. The average accuracy of the MODIS calculated paddy map was assessed on the basis of the observable BBS data at the district and nation levels. The average accuracy index values of R2, NSE, MBE, RMSE and MAE were found to be 0.89, 0.84,-2.48 km2, 223.18 km2 and 161.76 km2 correspondingly. The results of this research suggested that the MODIS estimation of the paddy area detection technique could assist scientists, decision makers, developers and administrations estimate the paddy area before harvesting time to make sure food safety at the national scale. |
| Year | 2020 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Virdis, Salvatore G.P. |
| Examination Committee(s) | Tripathi, Nitin Kumar;Mozumder, Chitrini |
| Scholarship Donor(s) | Bangabandhu Science & Technology Fellowship Trust, Bangladesh |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2020 |