Using GIS and Fractal Theory to Evaluate Degree of Fault Complexity and Water Yield

Yang, Binbin; Yuan, Junhong; Duan, Lihong; Liu, Qin

doi:10.1007/s10230-018-0563-8

Cited by 8 publications

(1 citation statement)

References 34 publications

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“…The rapid developments in GIS have enabled spatial data to be examined with more innovative perspectives. In this context, fractal analysis, an effective tool for identifying and analyzing the irregularities of objects, events, and phenomena, has recently been integrated into GIS to study the spatial pattern of objects in many subjects such as urbanization (Li et al 2011;Tannier et al 2011;Terzi and Kaya 2011;Ozturk 2017;Purevtseren et al 2018;Man and Chen 2020), transportation (Lu and Tang 2004;Sun et al 2007;Dasari and Gupta 2020;Karpinski et al 2020;Sahitya and Prasad 2020), and geology (Wang et al 2012;Pourghasemi et al 2014;Ni et al 2017;Sun et al 2017;Yang et al 2019). Although fractal analysis has the potential to improve the accuracy of measurement and identification of forest areas (Lorimer et al 1994), very few studies have been conducted on the use of fractal analysis in forest areas.…”

Section: Introductionmentioning

confidence: 99%

Fractal analysis of spatio-temporal changes of forest cover in Istanbul, Turkey

Öztürk

2022

AGS

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In this study, the spatio-temporal changes in forest cover in Istanbul, one of the provinces with the most changes in forest areas in Turkey due to the pressure of urbanization and industrialization, were investigated using fractal analysis. The areal changes and changes in spatial patterns were determined to assess the spatio-temporal changes in the period 2000–2017. Fragmentation/compactness and heterogeneity/homogeneity of forest cover were determined by fractal dimension and lacunarity index, respectively. The results show that the forest areas have significantly decreased and become more fragmented and heterogeneous. In conclusion, this study reveals that fractal analysis can provide considerable information in the examination and interpretation of spatial changes in forest areas.

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