Tug-of-war lacunarity—A novel approach for estimating lacunarity

Reiss, Martin A.; Lemmerer, Birgit; Hanslmeier, A.; Ahammer, Helmut

doi:10.1063/1.4966539

Cited by 12 publications

(14 citation statements)

References 25 publications

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“…While FFI quantifies how much compact or fragmented the space occupied by the forest is, the lacunarity quantifies how space is occupied. In order to assess the degree of heterogeneity of forest loss areas compared to gain areas and their effects on forest, the Tug-of-War lacunarities ( Λ T-o-W ) 55 were used. Λ T-o-W indicates mainly the manner of forest loss areas where increasing values indicate a chaotic distribution of the forest loss areas and vice versa.…”

Section: Methodsmentioning

confidence: 99%

Dynamics of Forest Fragmentation and Connectivity Using Particle and Fractal Analysis

Andronache

Marin

Fischer

et al. 2019

Sci Rep

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The ever decreasing area of forests has lead to environmental and economical challenges and has brought with it a renewed interest in developing methodologies that quantify the extent of deforestation and reforestation. In this study we analyzed the deforested areas of the Apuseni Mountains, which has been under economic pressure in recent years and resulted in widespread deforestation as a means of income. Deforested surface dynamics modeling was based on images contained in the Global Forest Database, provided by the Department of Geographical Sciences at Maryland University between 2000 and 2014. The results of the image particle analysis and modelling were based on Total Area (ha), Count of patches and Average Size whereas deforested area distribution was based on the Local Connected Fractal Dimension, Fractal Fragmentation Index and Tug-of-War Lacunarity as indicators of forest fragmentation or heterogeneity. The major findings of the study indicated a reduction of the tree cover area by 3.8%, an increase in fragmentation of 17.7% and an increase in heterogeneity by 29%, while fractal connectivity decreased only by 0.1%. The fractal and particle analysis showed a clustering of forest loss areas with an average increase from 1.1 to 3.0 ha per loss site per year. In conclusion, the fractal and particle analysis provide a relevant methodological framework to further our understanding of the spatial effects of economic pressure on forestry.

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Section: Methodsmentioning

confidence: 99%

Dynamics of Forest Fragmentation and Connectivity Using Particle and Fractal Analysis

Andronache

Marin

Fischer

et al. 2019

Sci Rep

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“…For the analysis of fractal indices as FFI and Λ T−o−W , were used FFI plugin [45] and Frac2D plugin [46] in the IQM 3.5 software [47].…”

Section: Glcm and Fractal Analysismentioning

confidence: 99%

“…Moreover, lacunarity discriminates the spatial distribution of gaps in texture at multiple scales, and is not sensitive to the edges of the images. In this paper, the Tug-of-War algorithm lacunarity [46] was calculated based on the equation:…”

Section: Glcm and Fractal Analysismentioning

confidence: 99%

Recent Deforestation Pattern Changes (2000–2017) in the Central Carpathians: A Gray-Level Co-Occurrence Matrix and Fractal Analysis Approach

Ciobotaru

Andronache

Ahammer

et al. 2019

Forests

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The paper explores the distribution of tree cover and deforested areas in the Central Carpathians in the central-east part of Romania, in the context of the anthropogenic forest disturbances and sustainable forest management. The study aims to evaluate the spatiotemporal changes in deforested areas due to human pressure in the Carpathian Mountains, a sensitive biodiverse European ecosystem. We used an analysis of satellite imagery with Landsat-7 Enhanced Thematic Mapper Plus (Landsat-7 ETM+) from the University of Maryland (UMD) Global Forest Change (GFC) dataset. The workflow started with the determination of tree cover and deforested areas from 2000-2017, with an overall accuracy of 97%. For the monitoring of forest dynamics, a Gray-Level Co-occurrence Matrix analysis (Entropy) and fractal analysis (Fractal Fragmentation-Compaction Index and Tug-of-War Lacunarity) were utilized. The increased fragmentation of tree cover (annually 2000-2017) was demonstrated by the highest values of the Fractal Fragmentation-Compaction Index, a measure of the degree of disorder (Entropy) and heterogeneity (Lacunarity). The principal outcome of the research reveals the dynamics of disturbance of tree cover and deforested areas expressed by the textural and fractal analysis. The results obtained can be used in the future development and adaptation of forestry management policies to ensure sustainable management of exploited forest areas.

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“…Fractal analysis is applied by using the Fractal Fragmentation Index (FFI) plugin [40], and the Tug-of-War Lacunarity analysis was conducted using the Frac2D plugin [41] in the IQM 3.2 software [42].…”

Section: Of 18mentioning

confidence: 99%

“…Tug-of-War lacunarity is useful in determining the way the deforestation and reforestation are done: homogenous -organized or heterogonous-disorganized, and their effect on forest areas. Tug-of-War lacunarity [41] was calculated based on the equation:…”

Section: Of 18mentioning

confidence: 99%

Using Multitemporal Landsat ETM+ Imagery to Determine a Sustainable Exploitation Patterns of the Forest Resources in the Moldo-Transylvanian Carpathians - Romania

Ciobotaru¹,

Andronache²,

Ahammer³

et al. 2018

Preprint

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Monitoring the ratio of forested and deforested areas plays a key role in studying the dynamics of forest areas. Appropriate mapping of anthropogenic forest disturbances is particularly important in the context of sustainable forest management. It provides ecological, social and economic information which is crucial for forest policymakers. In the last two decades, the forest areas of the Moldo-Transylvanian Carpathians have been subject to a high rate of deforestation which at present state lacks proper quantification. We present a novel methodology for monitoring the forest disturbance dynamics in Moldo-Transylvanian Carpathians by use of fractal analysis including entropy, Fractal Fragmentation Index (FFI) and Tug-of-War lacunarity ( ). This was necessary to quantify and identify the disorder (entropy), the fragmentation (FFI) and heterogeneity of the spatial distribution ( ) patterns. Based on satellite images of the forest areas (annually 2000-2014), increased fragmentation was demonstrated by FFI increase, a measure of the degree of disorder (entropy) and heterogeneity (lacunarity). Our results revealed that textural and fractal analysis can be an effective tool for the extraction of quantitative information about the spatiotemporal dynamics of forest disturbance. The methods developed, and results obtained are a complementary approach to forest disturbance mapping (based on traditional image Preprints (www.preprints.org) | NOT PEER-REVIEWED |

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Tug-of-war lacunarity—A novel approach for estimating lacunarity

Cited by 12 publications

References 25 publications

Dynamics of Forest Fragmentation and Connectivity Using Particle and Fractal Analysis

Dynamics of Forest Fragmentation and Connectivity Using Particle and Fractal Analysis

Recent Deforestation Pattern Changes (2000–2017) in the Central Carpathians: A Gray-Level Co-Occurrence Matrix and Fractal Analysis Approach

Using Multitemporal Landsat ETM+ Imagery to Determine a Sustainable Exploitation Patterns of the Forest Resources in the Moldo-Transylvanian Carpathians - Romania

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