Application of remote sensing and geographic information systems to forecast dry season paddy yield in the central plain of Thailand

Author: Sudchai Naikaset

AIT Library Call Number: AIT Thesis no.RD-00-1

Year: 2000

Academic Program: Regional and Rural Development Planning (RRDP)

Type: Thesis (M.Sc.) – Asian Institute of Technology, 2000

Examination Committee: Apisit Eiumnoh (Chairperson); Lal Samarakoon, Surat Lertlurn, Wiboon Boonyatharokul(Examination Committee Members)

Abstract: Remote sensing satellite data have been used to generate the MO}: yield models in various part of the world. As the crop yields are affected by several other factors, such as climatic and soil related variables, generation of such models need to be carried out at local level. A study was carried out to examine the relation between satellite derived Spectral information and soil-related properties with the yield of dry season rice in the central plain of Thailand. Landsat TM data acquired in April 1997 and March 1998, and soil information available at the series level were used to regress with the yield statistics available at sub-district level of the study area. Several yield models containing both Spectral and soil-related variables as predictor variables were generated. The models were applied to predict the yield of dry season rice for the year 1999 by using the spectral information derived from Landsat TM image acquired in February 1999. Digital image classification of three sets of images gave quite satisfactory overall classification accuracy of 93, 95 and 95 percent for the year 1997, 1998 and 1999, respectively. The class accuracy for dry season rice was 95, 97 and 99 percent, respectively for these images. Since the area is under irrigation, cultivation of second crop of rice is the major land use activity during the dry season, thus easily discriminable with high class accuracies. The areas classified as standing rice crop were 40.1, 56.4 and 40.2 percent of the total study area for 1997, 1998 and 1999 images, respectively. Of the 12 independent variables including spectral and soil-related, near-infrared and red bands either alone or in ratio showed higher correlation with rice yield among rest of the Spectral bands in general. Of the soil related variables, organic matter content of the soil showed higher correlation with the yield where as soil depth and soil texture were not found significantly correlated with rice yield. However, in case of 1997 data, a weak correlation was obser

Scholarship Donor(s): AIT Fellowship

Note: A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science

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Search keywords index: Sudchai Naikaset Application of remote sensing and geographic information systems to forecast dry season paddy yield in the central plain of Thailand Regional and Rural Development Planning (RRDP) Rice — Thailand, Central;”Geographic information systems — Thailand, Central”;