05116nas a2200433 a 4500 20260817163642.0 170919s2014 th uu m rtt 000 a|eng d .b1219170x AIT Diss. no.RS-14-07 Walaiporn Phonphan Assessment of soil salinity in a Tropical zone using ALOS PALSAR satellite imagery and ANN model Pathum Thani, Thailand : Asian Institute of Technology, 2014 1 online resource (104 leaves) : ill. Dissertation ; no. RS-14-07 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Remote Sensing and Geographic Information Systems Thesis (Ph. D.) - Asian Institute of Technology, 2014 Soil salinity is akey agricultural issuein many areas and,without effective investigation and management,canaggravateandexpand. Soil scientists categorize thesoil salinity level by Electrical Conductivity (EC) measurement.However, field measurements of EC values require extensive time, cost, resources, and experience. Thus, remote sensing is an attractive alternativeforcollecting and investigatingspatial data inlarger areas within short time. Due to constraints inoptical image data,microwave remote sensing data was chosen as a tool to study the tropical zone as the area of interest, which is intensely influenced by rainfall and humidity. ALOS L-band provides long wavelength with deep penetrationconsidered as reliable and useful forstudying the field under theaboveconditions.According to soil theory, the EC value isrelatedtosurface roughness and soil moisture.Severalresearchers estimated soil moisture through microwave remote sensing data, but there are fewstudies investigatingthe direct relationship between EC and Backscattering Coefficient(BC). Other researchers have studied through various models or variables that provednot quitesuccessful in derivingEC directly from BC data due to incorporating a large number of inputs and a complex multistage examination to identify salinesoil areasthroughout the learning process.Thus, the study aims to propose anestimation of EC directly from BC of microwave remote sensing data,i.e., arelationship between EC obtained from field survey and BC from microwavedata. Implementation of the study startedbyanalyzingstatistical data comprising EC data from asaline soil field survey and BC of PALSAR-ALOS databy statisticbased methods to investigate therelationship between EC and BC values. Various advanced statistical measurements such as Pearson correlation, regression modeland model fitting (polynomial, logarithm)were applied in this research. The research found thattheregression model gives an r-square value of0.743forthe relationship of EC and BC. Ther-square values were subjecttoanincrease asthepolynomialwas adjusted in the model. Artificial Neural Network (ANN) is one of the techniques to figure out the EC -BC relationshipproposed in this study.The ANN model presented anr-squarevalue of0.93,which was regarded high. BC from radar is influenced bymoisture and surface roughness, which are the main factors in identifying whether anarea has asoil salinity issue or not. Results of the research also reaffirmthe potentialof Radar BC in estimating and monitoring salineareas throughtheANN modellearning process.Therefore, the relationship between BC and EC wasused to develop asalinity modelsuitingthe real-time scenario,whichcan be successfully utilized as an effective analytical tool for EC estimation from microwave remote sensing (PALSAR ALOS) data. Soil salinization Remote sensing Thailand, Northeastern Tripathi, Nitin Kumar, Chairperson Apisit Eiumnoh, Examination Committee TaravudhTipdecho, Examination Committee Nakamura, Shinichi, Examination Committee SuanSunandhaRajabhat University, Thailand, Scholarship Donor Asian Institute of Technology. Dissertation ; no. RS-14-07 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B00773 .b1219170x mnait m 240418 0 170919 m a m 0 000:001:PDF:b1219170:003399:0:0:0:0:0:0 Click to view Abstract n mnait mnait mnarc 20 40 Barcode : 30050120517213 CREATED : 2017-09-19 RECORD # : i13102382 LPATRON : 1026331 LCHKIN : 2020-03-17 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 1 TOT RENEW : 8 Barcode : 30050120517189 CREATED : 2017-09-19 RECORD # : i13102394 LPATRON : 1029963 LCHKIN : 2020-01-31 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 3 TOT CHKOUT : 4 TOT RENEW : 4 Barcode : 30050120397871 CREATED : 2018-10-22 RECORD # : i13143049 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 9356 9356 0 0 0 0 MAIN MAIN mnait 2026-08-17 50.00 0 AIT Diss. no.RS-14-07 30050120517213 2026-08-17 16:36:43 1 2026-08-17 20 0 0 0 0 MAIN MAIN mnait 2026-08-17 50.00 0 AIT Diss. no.RS-14-07 30050120517189 2026-08-17 16:36:43 2 2026-08-17 20 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT Diss. no.RS-14-07 30050120397871 2026-08-17 16:36:43 2026-08-17 40