04218nas|a2200433 a 4500 20260818143613.0 060223s2005 th uu|m rtt 0| a1eng d .b11980710 AIT Thesis no.RS-05-12 Juthasinee Thanyapraneedkul Integration of remote sensing data with forest growth model to estimate the growth productivity Pathum Thani, Thailand : Asian Institute of Technology, 2005 82 leaves : ill. Thesis ; no. RS-05-12 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Engineering and Technology Thesis (M.Sc.) - Asian Institute of Technology, 2005 Process Based Models (PBMs) can be driven with information derived from satellite sensors. In particular, Absorbed photosynthetically active radiation (APAR) was estimated from global solar radiation, derived from an established empirical relationship based on average maximum and minimum temperatures, and from a linear relation with the satellite-derived normalised difference vegetation index (NDVI) which represents the photosynthetic capacity of all vegetation and is often correlated with the fraction of PAR absorbed FPAR. 3-PGS is a production model driven by remote sensing data, running at monthly time steps and have many advantages and reduce fields work that take time and laborious. The using should be considered in each parameter that are site specific and type of satellite sensor. In this study, has been use d LANDSAT ETM+ to derived NDVI. For 3PG model output showed the good relationship between measured (groundbased measurements) and simulated (modeled) values by Coefficient of determination (R) more than 0.7 and The root mean square errors (RMSE) is less than other models for all parameters (Net Primary production ;NPP ,Aboveground Biomass ; Wabv , Mean Annual Increment ;MAI and Stand Volume ;SV ). For 3PGS model output showed the not that good relationship between measured (ground-based measurements) and simulated (modeled) values by Coefficient of determination (R) less than 0.5 in Eucalyptus plot and The root mean square errors (RMSE) is more than 3PG model for all parameters. Because of low NDVI value that is effected by soil reflectance. Acacia mangium (plot A1) showed highly correlated between measured (ground-based measurements) and simulated (modeled) values; more than Eucalyptus camaldulensis (plot E2 to E6), for Wabv and NPP A were in near 1:1 agreement with Coefficient of determination (R) more than 0.8. Remote sensing data are utilized in these types of models providing 4 alternatives strategies (1) To estimate input variables (2) To test and validate predictions (3) To update or adjust ecological models (4) To apply ecological models to understand RS respond. Forests and forestry Remote sensing Forests and forestry Growth Tripathi, Nitin Kumar, Chairperson Borne, Frederic, Examination committee Hazarika, Manzul Kumar, Examination committee Thongchai Charuppat, Examination committee His Majesty the King of Thailand, Scholarship donor Asian Institute of Technology. Thesis ; no. RS-05-12 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B09703 .b11980710 mnait u 240329 0 060203 m a u 0 mnait mnait mnarc 20 40 Barcode : 30050120332647 CREATED : 2006-03-02 RECORD # : i12475099 LPATRON : 1014538 LCHKIN : 2018-09-10 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 13 TOT RENEW : 9 Barcode : 30050120591135 CREATED : 2006-03-02 RECORD # : i12475105 LPATRON : 1026222 LCHKIN : 2016-05-24 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 9 TOT RENEW : 13 Barcode : 30050120241665 CREATED : 2016-03-30 RECORD # : i12912694 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 61751 61751 0 0 0 0 MAIN MAIN mnait 2026-08-18 50.00 0 AIT Thesis no.RS-05-12 30050120332647 2026-08-18 14:36:13 1 2026-08-18 20 0 0 0 0 MAIN MAIN mnait 2026-08-18 50.00 0 AIT Thesis no.RS-05-12 30050120591135 2026-08-18 14:36:13 2 2026-08-18 20 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT Thesis no.RS-05-12 30050120241665 2026-08-18 14:36:13 2026-08-18 40