Fuzzy Logic and Geostatistical Techniques for Spatialization of Soil Texture in Region with Rough Terrains

Camarinha, Pedro Ivo Mioni; Trannin, Isabel Cristina de Barros; Simões, Silvio Jorge Coelho; Bernardes, George de Paula

doi:10.1016/j.proenv.2011.07.060

Cited by 9 publications

(7 citation statements)

References 3 publications

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“…Fuzzy logic often uses linguistic and verbal information (Marimin, Djatna, Suharjito, Hidayat, Utama, Astuti and Martini, 2013). Fuzzy systems, including fuzzy set theory and fuzzy logic, provide a rich and meaningful improvement, or extension of conventional logic (Camarinha et al , 2011). Several researchers have been carried out by integrated GIS and fuzzy logic approach in their studies, namely, Ghayoumian et al (2007), Camarinha et al (2011), and Londoño et al (2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial intelligent decision support system for increasing productivity on natural rubber agroindustry by green productivity approach

Teniwut

Marimin

Indrasti

2017

IJPPM

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Purpose The purpose of this paper is to develop a spatial intelligent decision support system (SIDSS) for increasing productivity in the rubber agroindustry by green productivity (GP) approach. The SIDSS was used to measure the productivity of rubber plantation and rubber agroindustry by GP approach, and select the best strategies for increasing the productivity of rubber agroindustry. Design/methodology/approach This system was developed by combining spatial analysis, GP, and fuzzy analytic network process (ANP) with the model-based management system, which is able to provide comprehensive and meaningful decision alternatives for the development of natural rubber agroindustry. Rubber plantation productivity measurement model was used to find the productivity level of rubber plantation with fuzzy logic, and also to provide information and decision alternatives to all stakeholders regarding spatial condition of rubber agroindustry, production process flow, and analysis of the seven green wastes at each production process flow using the geographic information system. GP measurement model was used to determine the productivity performance of the rubber agroindustry with the green productivity index (GPI). The best strategy for increasing the productivity was determined with fuzzy ANP. Findings Rubber plantation measurement model showed that the average of plantation productivity was 6.25 kg/ha/day. GP measurement model showed that the GPI value of ribbed smoked sheet (RSS) was 0.730, whereas of crumb rubber (CR) was 0.126. The best strategy for increasing the productivity of rubber agroindustry was raw material characteristics control. Based on the best strategy, the GPI value of RSS was 1.340, whereas of CR was 0.228. Research limitations/implications This decision support system is still limited as it is based on static data; it needs further development so that it can be more dynamically based on developments in the rubber agroindustry related levels of productivity and environmental impact. In addition, details regarding the decision to increase the productivity of the rubber section by benchmarking efforts should be studied further, both among plantation as well as among countries such as Thailand so that the productivity of rubber plantation and agroindustry can be integrated. Practical implications This research can help the planters to select superior clones for rubber trees, to improve the technique of tapping latex, and to use a better coagulant. The good quality and quantity of raw material is a key factor in increasing the productivity of rubber agroindustry; if the quality of latex is good then the resulting product will also have a good quality and production cost can be reduced. In addition, the application of GP through the calculation of GPI value using improvement scenarios can be used as a reference and comparison for evaluating the performance of rubber agroindustry to reduce the waste generated by the activities of rubber processing plant. Social implications Reduction of waste generated by production activities can improve the quality of life of the workforce and the environment. The calculation of GPI value can also be used as a basis to use raw materials, water, and electricity more efficiently. Originality/value This system was developed by combining spatial analysis, GP, and fuzzy ANP with the model-based management system, which is able to provide comprehensive and meaningful decision alternatives for the development of natural rubber agroindustry.

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Section: Literature Reviewmentioning

confidence: 99%

Spatial intelligent decision support system for increasing productivity on natural rubber agroindustry by green productivity approach

Teniwut

Marimin

Indrasti

2017

IJPPM

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“…The spatial variability of soil physical properties (Russo & Bresler, 1981;Camarinha et al, 2011), especially soil pore size distribution, are major factors in spatial variation of the final infiltration rate, Philip sorptivity and transmissivity (Sharma et al, 1980;Machiwal et al, 2006;Haghighi et al, 2010) in the flood plain and control areas of the studied region. Hallett et al (2004) stated that macro-pores and repellency is the likely cause of severe spatial variability.…”

Section: Geostatistical Analysismentioning

confidence: 99%

“…Scaling is one approach that has been used to describe the spatial variability of soil properties (Peck et al, 1977;Machiwal et al, 2006). The geostatistical technique was applied to analyze the spatial variability of soil sorptivity (Sepaskhah et al, 2005) and soil texture (Camarinha et al, 2011). In geostatistic analysis, a variogram or semi-variogram is employed to determine spatial variability of a variable, and provide the input parameters for the spatial interpolation of kriging (Webster & Oliver, 2007).…”

mentioning

confidence: 99%

Modelling infiltration and geostatistical analysis of spatial variability of sorptivity and transmissivity in a flood spreading area

Fashi

Sharifi

Kamali

2014

Span. j. agric. res.

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Knowledge of infiltration characteristics is useful in hydrological studies of agricultural soils. Soil hydraulic parameters such as steady infiltration rate, sorptivity, and transmissivity can exhibit appreciable spatial variability. The main objectives of this study were to examine several mathematical models of infiltration and to analyze the spatial variability of observed final infiltration rate, estimated sorptivity and estimated transmissivity in flood spreading and control areas in Ilam province, Iran. The suitability of geostatistics to describe such spatial variability was assessed using data from 30 infiltration measurements sampled along three lines. The Horton model provided the most accurate simulation of infiltration considering all measurements and the Philip's two-term model provided less accurate simulation. A comparison of the measured values and the estimated final infiltration rates showed that the KostiakovLewis, Kostiakov, and SCS models could not estimate the final infiltration rate as well as Horton model. Estimated sorptivity and transmissivity parameters of the Philip's two-term model and final infiltration rate had spatial structure, and were considered to be structural variables over the transect pattern. The Gaussian model provided the best-fit theoretical variogram for these three parameters. Variogram values ranged from 99 and 88 m for sorptivity and final infiltration rate to 686 (spherical) and 384 m (Gaussian) for transmissivity. Sorptivity, transmissivity and final infiltration attributes showed a high degree of spatial dependence, being 0.99, 0.81 and 1, respectively. Results showed that kriging could be used to predict the studied parameters in the study area.

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“…The application of fuzzy logic to natural resource science and management is still relatively new, but growing rapidly. This application has been used among other things in the identification of preferred artificial recharge sites, the convertion of soil texture classes in numerical values and the prediction of daily runoff rates by using moisture and rainfall as input variables (Ghayoumian et al, 2007;Camarinha et al, 2011;Tayfur and Brocca, 2015) Related to the objective of this study, fuzzy logic has been applied in infiltration studies analyzing only conventional tests. Two fuzzy rule base models for calculating the infiltration and movement of soil moisture in a heterogeneous soil column were developed by Bárdossy and Disse (1993).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic-based assessment for mapping potential infiltration areas in low-gradient watersheds

Londoño

Romanelli

Lima

et al. 2016

Journal of Environmental Management

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This paper gives an account of the design a logic-based approach for identifying potential infiltration areas in low-gradient watersheds based on remote sensing data. This methodological framework is applied in a sector of the Pampa Plain, Argentina, which has high level of agricultural activities and large demands for groundwater supplies. Potential infiltration sites are assessed as a function of two primary topics: hydrologic and soil conditions. This model shows the state of each evaluated subwatershed respecting to its potential contribution to infiltration mainly based on easily measurable and commonly used parameters: drainage density, geomorphologic units, soil media, land-cover, slope and aspect (slope orientation). Mapped outputs from the logic model displayed 42% very low-low, 16% moderate, 41% high-very high contribution to potential infiltration in the whole watershed. Subwatersheds in the upper and lower section were identified as areas with high to very high potential infiltration according to the following media features: low drainage density (<1.5 km/km(2)), arable land and pastures as the main land-cover categories, sandy clay loam to loam - clay loam soils and with the geomorphological units named poorly drained plain, channelized drainage plain and, dunes and beaches.

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Fuzzy Logic and Geostatistical Techniques for Spatialization of Soil Texture in Region with Rough Terrains

Cited by 9 publications

References 3 publications

Spatial intelligent decision support system for increasing productivity on natural rubber agroindustry by green productivity approach

Spatial intelligent decision support system for increasing productivity on natural rubber agroindustry by green productivity approach

Modelling infiltration and geostatistical analysis of spatial variability of sorptivity and transmissivity in a flood spreading area

Fuzzy logic-based assessment for mapping potential infiltration areas in low-gradient watersheds

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