03711nas|a2200469 i 4500 20260818155451.0 090301s2000 th uu m rtt 00| a1eng d .b11822193 AIT Thesis no.SR-00-06 Rajapakse, Rajapakse Mudiyanselage Sepalika Sandhya A model for estimating tea yield by combining remote sensing parameters and GIS : a case study of a tea plantation in Sri Lanka Bangkok : Asian Institute of Technology, 2000 87 leaves Thesis ; no. SR-00-06 A thesis submitted in partial fulfillment of the requirement for the degree of Master of Science, School of Advanced Technologies Thesis (M.Sc.) - Asian Institute of Technology, 2000 Tea is very important cash crop for Sri Lanka as it is the number one foreign exchange earner for the country. Monitoring tea yield is vital from both management of tea plantation and commercial purpose. Tea yield depends on various land use and environment parameters. Remote sensing provides useful information on existing crop condition. In this analysis an attempt has been made to predict tea yield using remote sensing and other key parameters in GIS environment. Leaf area index (LAI) is one main key factor useful in crop growth models that may be derived from optical remote sensing data. The LAI during the plucking stage is an important state variable in tea yield modeling. The LAI is a major factor determining crop reflectance and is often used in crop reflectance modeling. Therefore, the relationship between tea LAI and optical remote sensing parameter (NDVI) was investigated and this is very important in developing yield prediction models for tea. A model with a logarithmic function was adopted to find the relationship between NDVI (satellite image) and measured LAI. Satellite derived LAI values and existing spatial, meteorological and agronomic variables with statistical regression analysis and analytical capabilities of GIS were used to develop a model for tea yield estimation. Although different methods were tried to find the best model by using multiple regression, a model develop by using weights of considered variables selected as the suitable model for predicting tea yield as it gives a 95% level of significance. Tea Sri Lanka Tea Remote sensing Tea Yields Geographic information systems Tripathi, Nitin Kumar, Chairperson Honda, Kiyoshi, Examination Committee Lal Samarakoon, Examination committee Schumann, Robert L. G., Examination Committee AIT Partial Scholorship, Scholarship Donor Asian Institute of Technology. Thesis ; no. SR-00-06 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B06824 .b11822193 mnait u 240401 0 010309 m a u 0 mnait mnait mnarc 22 40 20 Barcode : 30050120694632 CREATED : 2014-04-28 RECORD # : i12792494 LPATRON : 1025965 LCHKIN : 2015-04-10 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 1 TOT RENEW : 3 Barcode : 30050160022835 CREATED : 2016-01-04 RECORD # : i12919500 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050121017924 CREATED : 2020-10-07 RECORD # : i13281574 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 77390 77390 0 0 0 0 MAIN MAIN mnait 2026-08-18 50.00 0 AIT Thesis no.SR-00-06 30050120694632 2026-08-18 15:54:51 3 2026-08-18 22 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT Thesis no.SR-00-06 30050160022835 2026-08-18 15:54:51 1 2026-08-18 40 0 0 0 0 MAIN MAIN mnait 2026-08-18 0 AIT Thesis no.SR-00-06 30050121017924 2026-08-18 15:54:51 1 2026-08-18 20