Spectral recognition of Nipa palm plantation using machine learning of high-resolution remote sensing data and modelling status and yield | |
| Author | Kiran, Kona Venkata Anantha |
| Call Number | AIT Thesis no.RS-22-05 |
| Subject(s) | Mangrove forests--Remote sensing--Thailand--Nakhon Si Thammarat Machine learning |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | The utilization of Nipa palm (Nypa fruticans) is the major livelihood for many people in Khanap Nak area of Pak Phanang District in Nakhon Si Thammarat Province of Thailand. The Nipa palm, which is traditionally used for thatching houses, fuel wood and making handicrafts, provide economically important by-products like biofuel, sugar, vinegar, molasses, charcoal, etc. The nipa palm is also suitable to be farmed at many other places, but the cultivation of the nipa palm and the benefits of nipa palm have remained unstudied. this study mainly aims to detect the nipa palm trees from the remote sensing data using Machine learning models and find the best fit model among the Random Forest model and the Support Vector machine model. The Machine learning models are rigid and complex to classify large data sets. After the detection of trees, Classification of the detected trees (from the best fit model) on basis of the health of the tree will be done using the Vegetation Health Index (VHI). On basis of the classified detected trees, the financial model stating all the income that can be attained using the by-products of the nipa palm farms at the Khanap Nak area can be calculated. This study mainly focuses on the accuracy attained using different models and the total classified information of the nipa palm trees of the study area using a high-resolution satellite image of the study area and machine learning models. |
| Year | 2022 |
| 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) | Tripathi, Nitin Kumar |
| Examination Committee(s) | Mozumder, Chitrini;Hossain, Md. Zakir |
| Scholarship Donor(s) | AIT Partial Scholarship |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2022 |