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A methodology for classifying rainfed paddy fields based on their hydrological conditions is lacking. This study analysed the behaviour of synthetic aperture radar (SAR) backscatter coefficients at each polarisation and cross-polarisation ratio index in a rainfed rice paddy field with a partially waterlogged surface. The SAR polarisations used were the VH and VV of the C-band SAR Sentinel-1 and the HV and HH of the L-band SAR Palsar-2. The relationship between backscatter coefficient and terrains including topographic categories and local relative elevation, which affect waterlogging conditions in rainfed paddy fields, were evaluated. The VV of C-band, and HH and HV of L-band showed different patterns in the time series variation according to the topographic categories. We observed that the combination of L-band HH and HV could be used to assess waterlogging conditions because they differ depending on variations in local elevation. The study results suggest that future studies can evaluate the microtopography and associated local hydrological environment using the combination of L-band HH and HV backscatter coefficient. [ABSTRACT FROM AUTHOR]

Salt-affected soil maps for Northeast Thailand focus on the percentage of salt crusts. Investigation was done to find the field-scale spatial variability of the electrical conductivity of saturation extract (ECe) in salt-affected areas (percentage salt crusts: very severely = class 1; severely = class 2, and moderately = class 3). Two study sites were selected for each class (n = 6). Soil samples (n = 100) were collected at each site using stratified, systematic, unaligned sampling, and analyzed for ECe. Variations in ECe were assessed using basic statistics and geostatistics. At the field-scale, in every class, the best-fit semivariogram model generated was satisfactory (R2 > 0.8). Interpretation from the relevant model parameters (i.e., nugget, sill, and effective range), together with the interpolated (kriged) maps, demonstrated that the characteristics of spatial variability of soil ECe were inconsistent, even between different sites of the same salt-affected soil class. In general, various degrees of small-scale variation were observed, very high variation of ECe was common, spatial dependence was strong to moderate, while the spatial distribution pattern was in distinctive patches. The size of patches depended on the effective range at each site. This study also revealed that the class 1 areas were entirely, very strongly saline (ECes range, 56.70 and 433.00 dS·m-1), whereas the areas of class 3 were non-saline to moderately saline (range, 0.11 - 5.26 dS·m-1). Class 2 areas were much more complex; the soils varied from non-saline to very strongly saline (range, 0.16 - 49.00 dS·m-1). Information on the nature and characteristics in the spatial variability of soil ECe is useful for developing strategies for management of salt-affected soils in precision agriculture in this region. [ABSTRACT FROM AUTHOR]

This paper aims to introduce the Decision Support System (DSS), which is an area informatics approach to area studies, and the research network complex based on DSS's application in Thailand. In particular, the paper presents and discusses cur-rent activities of the DSS research network at the national level in Thailand rather than being a theoretical and analytical study of the DSS mechanism or its cases. DSS has wide applications in Thailand, extending to various fields such as agri-cultural and natural resource management, economic and social management, historical and cultural preservation, and so on. DSS generally refers to a support system embedded into a computer system for providing intellectual resources with the appropriate numerical model necessary for decision making in production activities. Agricultural and natural resources have been the foundation of social and economic development in Thailand since the country's first national plan in the 1960s. Decision making to maintain agricultural productivity as well as to protect natural resources requires well-integrated data sets. The Thailand Research Fund (TRF) established a DSS research and development network (TRF-DSS) in 2002 to help various research teams in Thailand develop DSS tools and components for addressing agricultural and natural resource management issues. Using a "systems" approach, the DSS framework allows researchers and users to identify and inte-grate key components as well as to define databases and model-base management systems. This paper focuses on the TRF-DSS research and development network, which consists of 12 universities, two line agencies in Thailand, and a line agency in Cam-bodia. During 2002-10, a total of 59 research projects were granted a budget alloca-tion of 140.1 million baht, and a budget of 15.4 million baht was allocated to support activities of the network. In addition, 10 projects were funded to carry out post-project activities, with a total budget of 1.5 million baht. More than 20 DSS tools were developed and implemented by various users, ranging from policy makers to provincial and local government agencies engaged in short- and long-term planning and management. Most DSS tools were designed to allow the integration of bio-physical and socioeconomic data as well as the decision support modules for alterna-tives evaluation and analysis. These approaches support the choices of dynamic simulation models as well as multi-criteria analyses for modelbase software develop-ment. They also allow users to evaluate various alternatives in agricultural and natural resource management. Networking is a powerful platform for DSS research and development and may be applied to other types of research and development agenda in Thailand, such as area study projects. DSS tools contribute to an understanding of sustainability of production systems against a background of climate change, poverty reduction, and food security. [ABSTRACT FROM AUTHOR]