05215nas|a2200445 i 4500 20260817162500.0 040806s2003 th uu m rtt 00| a1eng d .b11935984 AIT Diss. no.SR-03-02 Waktola, Daniel Kassahun Analysis of the spectral signature of soils and prediction of nutrients through remote sensing and GIS based models Pathum Thani, Thailand : Asian Institute of Technology, 2003 101 p. Dissertation ; no. SR-03-02 Submitted in partial fulfillment of the requirement for the degree of Doctor of Philosophy, School of Advanced Technologies Employing remote sensing tools for monitoring and mapping of soil fertility parameters could offer enhanced possibilities. This is due to the objectivity of data, wider area coverage, continuous monitoring, and faster acquisition capabilities than the conventional methods. However, apart from the challenges induced from plant cover, other obstacles like indiscriminability of soil nutrients from satellite platform and the incompatibility of the sensors' resolutions considerably hinder the direct application of the technology. This research was undertaken with a prime objective of developing predictive models for Soil Organic Matter (SOM), phosphorus (P), potassium (K), and iron (Fe), from quantified spectral-chemical patterns. Data were computed from multi sources of detecting platforms, viz., laboratory-based spectrometer, field-based photometer, and optical satellite-based sensors. Samples were collected from plough layers of Lop Buri tropical soils, Thailand, during a satellite-synchronized ground survey. Both radiometric and chemical analysis were carried out following the standard field and laboratory procedures. The first part of the research addressed the modeling of nutrients from the field and laboratory generated reflectance spectra. The data were synthesized across a 10, 20, 50, and 100 nm bandwidth categories. Accordingly, a single, double, and 100 nm-based bandwidth categories were synthesized from the field spectral data. Stepwise Multiple Regression, Polynomial models, and Artificial Neural Network (ANN) analysis were employed for the identification of nutrient-sensitive bands and subsequent model development. The results revealed higher degree of predictions obtainable from the laboratory than the field conditions. ANN appeared to offer better prediction than the Multiple Regression and Polynomial models. Furthermore, the narrower bandwidth categories have outperformed the broader bandwidth category, where the trend, in this research, is termed as "bandwidth decay effect''. In the second pa1t, the radiometrically, geometrically, and atmospherically corrected IRS-ID satellite data were processed through several indices to yield nutrient-specific prediction models. These models were built through the synthetically cloned channels, called "Spech·al Band Cloning" (SBC). The SBC had interwoven the fine-scaled spectrometer signatures with the course-scaled satellite data. This enabled the development of an original modeling approach. The conclusion that emerges from this model is that, although SBC has performed lower than the spectrometer-based models, it has produced adequate results, which were impossible to realize from the satellite alone. An R2 of 0.72, 0.62, 0.70, and 0.68 were attained for SOM, P, K, and Fe, respectively. Measured and predicted maps of each soil nutrient type, along with the overall weighted fertility surface, were generated from the interpolated nutrient surfaces, performed on a GIS environment. Models were validated on unused (independent) dataset, vis-a-vis the conventionally measured soil nutrients, and had attained an R2 of0.69, 0.49, 0.64, and 0.60 for SOM, P, Kand Fe, respectively. Thesis (Ph.D.) - Asian Institute of Technology, 2003 Soils Analysis Soil fertility Tripathi, Nitin Kumar, Chairperson Honda, Kiyoshi, Examination Committee Apisit Eiumnoh, Examination Committee Alemaya University, Scholarship donor World Bank, Scholarship donor Asian Institute of Technology. Dissertation ; no. SR-03-02 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B07850 .b11935984 mnait u 240419 0 030806 m a u 0 mnait mnait mnarc 22 40 20 Barcode : 30050120561245 CREATED : 2012-08-31 RECORD # : i12691641 LPATRON : 1025974 LCHKIN : 2016-01-22 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 2 TOT RENEW : 4 Barcode : 30050120236459 CREATED : 2016-03-23 RECORD # : i12905070 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050121017510 CREATED : 2020-06-07 RECORD # : i13280144 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 5167 5167 0 0 0 0 MAIN MAIN mnait 2026-08-17 0 AIT Diss. no.SR-03-02 30050120561245 2026-08-17 16:25:00 3 2026-08-17 22 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT Diss. no.SR-03-02 30050120236459 2026-08-17 16:25:00 1 2026-08-17 40 0 0 0 0 MAIN MAIN mnait 2026-08-17 0 AIT Diss. no.SR-03-02 30050121017510 2026-08-17 16:25:00 1 2026-08-17 20