Yield estimation in Longan using remote sensing and Geographic Information System | |
| Author | Khanittha Saengmanee |
| Call Number | AIT Thesis no.RS-16-14 |
| Subject(s) | Longan--Yields--Remote sensing Geographic information system |
| Note | A thesis submitted 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 |
| Series Statement | Thesis ; no. RS-16-14 |
| Abstract | Thailand is the world's largest exporter of Longan. They can produce the out of season Longan and can assign the time to harvest the Longan in needed of markets time. However, the quantity of Longan yield always fluctuates, farmers cannot estimate their yield precisely. The objectives of this research were to generate the Longan yield estimation model at the farm scale and the individual trees level. The weather data, NDVI value and the characteristics of Longan trees such as crown size, tree height, diameter, and age was used in the stepwise multiple regression model. The result of model at the farm scale used only 2 factors which were NDVI and age of trees. for predicting the yields. Both of factors were statistically acceptable tp-value < 0.05). This model represented the relationship between independent and dependent variable with the R 2 adj value of 96.6% and the average percentage error of the model is approximately 8.7 %. The result of yield estimation model of the individual trees level used only 2 factors that were significant related to use to predict the Longan yields which were NDVI and crown size diameter of Longan trees. Both of factors were statistically acceptable rp-value < 0.1). The model represented the relationship between independent and dependent variable with the R2adj value of 53.4 % the average percentage error of the model is approximately 15 % which demonstrated that the result from this model is very precisely with the actual yield. |
| Year | 2016 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-16-14 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Nagai, Masahiko |
| Examination Committee(s) | Sarawut Ninsawat;Soni, Peeyush;Apichon Witayangkurn |
| Scholarship Donor(s) | Royal Thai Government Fellowship;Asian Institute of Technology Fellowship |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2016 |