Land Suitability for Short Rotation Coppices Assessed through Fuzzy Membership Functions

Corona, Piermaria; Salvati, Riccardo; Barbati, Anna; Chirici, Gherardo

doi:10.1007/978-1-4020-8504-8_12

Cited by 12 publications

(7 citation statements)

References 53 publications

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“…They compared the land indices with observed yield of the crop and obtained a correlation coefficient of 0.14 and 0.35 for parametric and fuzzy methods respectively. Corona et al (2008) explained some benefits of fuzzy set application in land suitability assessment and performed a case study on land suitability by using fuzzy sets. They concluded that this methodology is quite useful in such projects.…”

Section: Discussionmentioning

confidence: 99%

Soil suitability evaluation for crop selection using fuzzy sets methodology

Sharififar

Ghorbani

Sarmadian

2016

AAS

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In this study appraisal of four different agricultural land evaluation methods including the so-called Storie method, square root method, maximum limitation method and fuzzy sets method, was done. The study was performed in Bastam region, located in Semnan province at the north east of Iran. Three crops including tomato, wheat and potato were assessed for the purpose of this research. Soil characteristics assessed were rooting depth, CaCo 3, organic carbon content, clay content, pH and slope gradient. Statistical analyses were done at significance levels of α = 0.1 and α = 0.05. Results of regression between land indices, calculated through the four methods, with observed yields of the crops, showed that the regression were significant in fuzzy sets method for all of the assessed crops at p = 0.05 but not significant in maximum limitation method for any of the crops. The Storie and square root methods also showed a significant correlation with wheat yield at p = 0.1. This study was a demonstrative test of fuzzy sets theory in land suitability evaluation for agricultural uses, which revealed that this methodology is the most correct method in given circumstances.Key words: fuzzy sets, land evaluation, land use, soil classification, crop growth conditions, soil suitability, crop selection IZVLEČEK UPORABA METODOLOGIJE MEHKIH MNOŽIC PRI OCENI PRIMERNOSTI TAL ZA RAZLIČNE POLJŠČINEV raziskavi so bile ocenjene štiri metode vrednotenja kmetijskih zemljišč vključujoč Storijevo metodo, metodo kvadratnega korena, metodo maksimalne omejitve in metodo mehkih množic. Raziskava je potekala na območju Bastama, v provinci Semnan, v severovzhodnem delu Irana. Primernost zemljišč je bila ovrednotena za tri poljščine, paradižnik, pšenico in krompir. Ocenjene so bile naslednje lastnosti tal: globina koreninjenja, vsebnosti CaCO 3, organskega ogljika in gline, pH in naklon zemljišča. Statistične analize so bile narejene pri stopnji značilnosti α = 0,1 in α = 0.05. Rezultati regresijske analize za odvisnost pridelkov izbranih polščin od indeksov primernosti zemljišč, izračunanih po zgoraj omenjenih metodah je pokazala, da je statistično značilna samo odvisnost pridelka od indeksa primernosti zemljišč dobljenega z metodo mehkih množic" Storijeva metoda in metoda kvadratnega korena sta pokazali značilno odvisnost prideleka pšenice od indeksa primernosti zemljišč pri α = 0,1. Raziskava je bila demonstracijski preskus primernosti uporabe metode mehkih množic pri vrednotenju zemljišč v kmetijski rabi. Ugotovljeno je bilo, da je bila ta metodologija v danih okoliščinah najprimernejša.Ključne besede: mehke množice, vrednotenje zemljišč, raba tal, klasifikacija tal, razmere za rast poljščin, primernost tal, izbira poljščin

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Section: Discussionmentioning

confidence: 99%

Soil suitability evaluation for crop selection using fuzzy sets methodology

Sharififar

Ghorbani

Sarmadian

2016

AAS

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“…The advantages of the multi-criteria analysis, GIS-based decision support system, including WLC or OWA in spatial and terrestrial planning, were discussed in several studies (Aydi et al 2016;Corona et al 2008;Jamil et al 2018;Kumar and Kumar 2014;Masoodi et al 2016b;Raza et al 2018Romano et al 2015Shuaibu and Kara 2019;Zolekar et al 2015;Zabihi et al 2019).…”

Section: Discussionmentioning

confidence: 99%

GIS-Based Multi-Criteria and Multi-Objective Evaluation for Sustainable Land-Use Planning (Case Study: Qaleh Ganj County, Iran) “Landuse Planning Using MCE and Mola”

et al. 2021

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Land evaluation is a key factor in land-use spatial planning, affecting both success and sustainability. This study showcases the value of using the multi-criteria evaluation (MCE) and multi-objective land allocation (MOLA) GIS decision-making tools determine the most favorable spatial development of various land-use types, for Qaleh Ganj County in Iran. Weighted linear combination (WLC) and ordered weighted averaging (OWA) were used to assess the potential of seven land uses based on predefined criteria. MOLA was also used for land-use zoning based on suitability. The results derived from these techniques indicate that the rangeland zone with 30.80% and the ecotourism zone with 22.9% have the highest suitability potential, and aquaculture with 0.26% and tourism with 0.24% have the lowest potential in Qaleh Ganj. Considering the 7 land uses and a lot of defined criteria, MCE and MOLA provided an automatic and flexible way of dealing with qualitative multi-dimensional environmental effects, factors, constraints and objectives. The combination of WLC and OWA helped to manage selection factors differently, as their level of risk and trade-off is different. The result can be considered as optimal suitability maps with an environmental preservation goal which can help to protect the natural environment of this area, and will also allow for continued economic development. The approach described in this study can help developing countries and the sensitive area facing environmental challenges due to rapid development. This approach and its application procedures can be applied to similar territorial contexts, where several territorial factors should be considered and taken into account.

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“…Fuzzy sets are usually combined with MCDM in the field of suitable analysis. Corona et al (2008) combined fuzzy sets and the weight linear combination in multiple criteria methods to conduct the land suitability assessment in south Italy, the result applied rational number 0 and 1 to represent the suitability grades, 0 as not suitable, 1 as very suitable. However, problem exists as how to accurately determine the membership function in fuzzy logic method.…”

Section: The Uncertainty On the Discretization Of Continuous Raster Datamentioning

confidence: 99%

“…As to the land suitability assessment in planning, there is no uniform standard for the numbers of class. The current existing class numbers including 3 classes (Corona, 2008;Liu et al, 2012;, 4 classes (Chen et al, 1999;Chen et al, 2010) and 5 classes (Zhou et al, 2007;Zhuo, 2012). Research indicates that the number of breaks should be an odd value as even number of classes misses a central class.…”

Section: The Applicability Of the Natural Breaks (Jenks)mentioning

confidence: 99%

The Uncertainties on the Gis Based Land Suitability Assessment For Urban and Rural Planning

Liu

Zhan

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VI/4 KEY WORDS: Uncertainty, Land suitability assessment, GIS, Planning ABSTRACT:The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS) based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the "Nature Breaks" method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making.

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Land Suitability for Short Rotation Coppices Assessed through Fuzzy Membership Functions

Cited by 12 publications

References 53 publications

Soil suitability evaluation for crop selection using fuzzy sets methodology

Soil suitability evaluation for crop selection using fuzzy sets methodology

GIS-Based Multi-Criteria and Multi-Objective Evaluation for Sustainable Land-Use Planning (Case Study: Qaleh Ganj County, Iran) “Landuse Planning Using MCE and Mola”

The Uncertainties on the Gis Based Land Suitability Assessment For Urban and Rural Planning

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