scholarly journals Perceptions of landscape patterns: Do the numbers count?

2000 ◽  
Vol 76 (3) ◽  
pp. 475-480 ◽  
Author(s):  
Robert G. D'Eon ◽  
Susan M. Glenn
Keyword(s):  
Undergraduate Students ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Human Perception ◽  
Landscape Fragmentation ◽  
Landscape Patterns ◽  
Relative Efficacy ◽  
Patch Shape ◽  
Before And After ◽  
Patch Density

Human perception and intuition can powerfully influence how we measure and interpret landscape pattern. We compared human perception with more quantitative measures to determine their relative efficacy in arriving at conclusions about landscape pattern. We surveyed 30 professional workshop participants and 38 undergraduate students for their perception of landscape fragmentation before and after calculating a suite of landscape metrics. Participants' perception of fragmentation was most correlated with number of patches, patch density, and patch shape. Most participants retained their original intuitive response after calculating indices. We suggest that a lack of meaningful quantitative expressions for absolute landscape structure will continue to result in a dependence on intuitive human perception for management of landscape pattern. Key words: landscape pattern, forest fragmentation, perception, landscape metrics, forest management

scholarly journals On the Scale Effect of Relationship Identification between Land Surface Temperature and 3D Landscape Pattern: The Application of Random Forest

2022 ◽  
Vol 14 (2) ◽  
pp. 279
Author(s):  
Qiong Wu ◽  
Zhaoyi Li ◽  
Changbao Yang ◽  
Hongqing Li ◽  
Liwei Gong ◽  
...  
Keyword(s):  
Random Forest ◽  
Linear Regression ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Land Surface ◽  
Landscape Patterns ◽  
Impervious Surfaces ◽  
Multi Scale

Urbanization processes greatly change urban landscape patterns and the urban thermal environment. Significant multi-scale correlation exists between the land surface temperature (LST) and landscape pattern. Compared with traditional linear regression methods, the regression model based on random forest has the advantages of higher accuracy and better learning ability, and can remove the linear correlation between regression features. Taking Beijing’s metropolitan area as an example, this paper conducted multi-scale relationship analysis between 3D landscape patterns and LST using Pearson Correlation Coefficient (PCC), Multiple Linear Regression and Random Forest Regression (RFR). The results indicated that LST was relatively high in the central area of Beijing, and decreased from the center to the surrounding areas. The interpretation effect of 3D landscape metrics on LST was more obvious than that of the 2D landscape metrics, and 3D landscape diversity and evenness played more important roles than the other metrics in the change of LST. The multi-scale relationship between LST and the landscape pattern was discovered in the fourth ring road of Beijing, the effect of the extent of change on the landscape pattern is greater than that of the grain size change, and the interpretation effect and correlation of landscape metrics on LST increase with the increase in the rectangle size. Impervious surfaces significantly increased the LST, while the impervious surfaces located at low building areas were more likely to increase LST than those located at tall building areas. It seems that increasing the distance between buildings to improve the rate of energy exchange between urban and rural areas can effectively decrease LST. Vegetation and water can effectively reduce LST, but large, clustered and irregularly shaped patches have a better effect on land surface cooling than small and discrete patches. The Coefficients of Rectangle Variation (CORV) power function fitting results of landscape metrics showed that the optimal rectangle size for studying the relationship between the 3D landscape pattern and LST is about 700 m. Our study is useful for future urban planning and provides references to mitigate the daytime urban heat island (UHI) effect.

scholarly journals A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 990
Author(s):  
Yongfen Zhang ◽  
Nong Wang ◽  
Chongjun Tang ◽  
Shiqiang Zhang ◽  
Yuejun Song ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
River Basin ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Sediment Yield ◽  
River Basins ◽  
Landscape Patterns ◽  
Soil Erodibility ◽  
Land Use Pattern

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

scholarly journals A study on the evolution mechanism of agricultural landscape pattern of Dadu River Valley in Danba Region

2021 ◽  
Vol 300 ◽  
pp. 02015
Author(s):  
Linlu Tian ◽  
Jiajin Wu ◽  
Minqing Li ◽  
Chunwei Xia ◽  
Jianpeng Cao ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Landscape Pattern ◽  
Agricultural Landscape ◽  
Landscape Fragmentation ◽  
Research Area ◽  
Landscape Patterns ◽  
Agricultural Policies ◽  
Dry Valley ◽  
Moderate Drought ◽  
Dadu River

Taking the Dadu River Basin in the Danba area of Ganzi Prefecture, Sichuan Province as the research area, based on the 2013 and 2016 Landsat8 remote sensing images, the temperature vegetation drought index (TVDI) method is used to divide the Dadu River dry valley into 6 arid gradient regions. Using ArcGIS10.5 software and Fragstats4.2 software to calculate the landscape pattern index of different arid gradient areas in different years, combined with the survey results of agricultural policies, development models, and agricultural landscape patterns in key regions, analyze the evolution of agricultural landscape patterns under different drought gradients. The results show that, except for other forestlands, the degree of landscape fragmentation is decreasing year by year on the gradient of light and moderate drought, and the degree of spatial heterogeneity is higher. On the gradient of extreme drought, the degree of landscape fragmentation is higher, and the degree of spatial heterogeneity is lower.

Analysis on Evolution of Landscape Pattern in Dianchi Basin Based on RS and GIS

2011 ◽  
Vol 291-294 ◽  
pp. 3419-3423 ◽  
Author(s):  
Zhao Qin Han ◽  
Jing Ye ◽  
Zhen Wang ◽  
Jie Liu ◽  
Shu Xia Yu
Keyword(s):  
Remote Sensing ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Principal Component ◽  
Landscape Fragmentation ◽  
Remote Sensing Images ◽  
Rs And Gis ◽  
Land Use Types ◽  
Landscape Patches ◽  
Landscape Level

With the support of RS, GIS and FRAGSTATS techniques, the landscape pattern has been analyzed quantitatively in Dianchi basin by 16 commonly used landscape metrics, based on remote sensing images of 1988, 1990, 1994, 1999, 2002 and 2008. After performance of principal component analysis (PCA) on the 16 landscape metrics, three principal components (PCs) were generalized: spatial aggregation of landscape patches, landscape fragmentation and landscape diversity. Then, the characteristics and evolution of landscape pattern in Dianchi basin have been explored at the landscape level. The results showed, that, from 1988 to 1994, the landscape fragmentation was serious and the level of diversity was fluctuant. And for some kinds of landscape patches, the integrity was much undermined, the spatial distribution was scattered and the degree of aggregation was fallen. From 1994 to 2008, the degree of aggregation between patches increased gradually. The situation of landscape fragmentation was under control. And, the land use types had a tendency towards diversification and homogenization.

scholarly journals Landscape Pattern Changes in the Xingkai Lake Area, Northeast China

2019 ◽  
Vol 16 (20) ◽  
pp. 3820 ◽  
Author(s):  
Xiaohui Liu ◽  
Yuan Zhang ◽  
Guihua Dong ◽  
Guanglei Hou ◽  
Ming Jiang
Keyword(s):  
Landscape Pattern ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Landscape Fragmentation ◽  
Landscape Patterns ◽  
Paddy Fields ◽  
Lake Area ◽  
Landscape Types ◽  
The Difference ◽  
Relative Change

Understanding landscape change is important for ecologically sustainable development. In this paper, we assessed the spatiotemporal variations of landscape pattern in the Xingkai Lake area using remote sensing data from 1982, 1995, 2000, 2005, 2010, and 2015. Landscape patterns of marshlands, paddy fields, dry farmlands, and their combinations were analyzed at class and landscape levels. We examined the stability of landscape types through principal component analysis based on class level indices for landscape types. The results indicated that marshland areas decreased significantly by 33.87% but paddy fields increased by 1.84 times from 1982 to 2015. The largest conversion of dry farmlands to paddy fields was 90.88 km2 during the period 2010–2015. In contrast, the largest conversion of paddy fields to dry farmlands was 86.03 km2 during the period 2000–2005. The difference in relative change revealed that dry farmlands had experienced a greater relative change than paddy fields since 2000. The interspersion and juxtaposition index decreased, while the number of patches grew. This showed that landscape fragmentation was increasing and the landscape pattern was becoming dispersed. Marshlands were more stable than paddy fields and dry farmlands across all time periods, except for the year 2005.

scholarly journals The Ecosystem Services Value Change and Its Driving Forces Responding to Spatio-Temporal Process of Landscape Pattern in the Co-Urbanized Area

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1043
Author(s):  
Xinyu Zhang ◽  
Huawei Li ◽  
Hua Xia ◽  
Guohang Tian ◽  
Yuxing Yin ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Landscape Pattern ◽  
Driving Forces ◽  
Yellow River ◽  
Landscape Patterns ◽  
Rapid Expansion ◽  
Edge Density ◽  
Cultivated Land ◽  
Construction Land ◽  
Patch Density

The development of urbanization is still expanding on the earth, and the rapid expansion of cities has changed the regional landscape pattern and significantly affected the value of regional ecosystem services in developing countries such as China. Zhongmu County, as the core area of Zhengzhou-Kaifeng integration, studying the temporal and spatial transformations of its landscape pattern and ecosystem service value (ESV) is of great significance to the region’s sustainable development. Based on remote sensing images and socioeconomic data, this study aims to explore the landscape pattern of Zhongmu County from 2005 to 2018 and its impact on ESV. Research methods include an ESV equivalent factor method, landscape pattern index, spatial autocorrelation, and other methods. The results showed that: (1) During the study period, the patch density and shape complexity, landscape diversity, and fragmentation of the overall landscape in the study area continued to increase while landscape connectivity decreased. (2) The total amount of ESV increased by 10.05 million USD; ESV had certain differences in spatial distribution: high-value clusters were mainly located at the boundary of the Yellow River in the north, while low-value clusters had a significant eastward expansion trend. (3) ESV increased significantly in areas where cultivated land was transferred to waters and forests, and ESV in areas where waters transferred to construction land and cultivated land was significantly reduced. (4) ESV had a significant positive spatial correlation with patch density, edge density, mean patch fractal dimension, mean patch size, and the landscape shape index, and a spatially negative correlation with the contagion index and cohesion index. The spatial and temporal changes in landscape patterns and ESV were all mainly driven by the regional development “Zhengzhou-Kaifeng integration” policy. Therefore, the ESV can be improved, and the ecological security of the urban integration area can be guaranteed through policy measures such as optimizing the layout of construction land and adjusting the uniform distribution of green areas by the land-use policy.

scholarly journals EFFECTS OF CHANGING SCALES ON LANDSCAPE PATTERNS AND SPATIAL MODELING UNDER URBANIZATION

2020 ◽  
Vol 28 (2) ◽  
pp. 62-73
Author(s):  
Jinming Yang ◽  
Shimei Li ◽  
Jingwei Xu ◽  
Xiaojie Wang ◽  
Xiaoguang Zhang
Keyword(s):  
Spatial Scale ◽  
Landscape Pattern ◽  
Spatial Modeling ◽  
Regression Models ◽  
Block Size ◽  
Landscape Patterns ◽  
The Mean ◽  
Patch Density ◽  
Variation Trends ◽  
Better Than

Spatial scale is an eternal topic in landscape pattern related analysis. This paper examined the spatial scale effect of landscape pattern changes and their relationships with urbanization indicators in Qingdao using a series of sampling blocks. The results indicated that, with the increasing block scale, the mean patch density and aggregation within a block decreased, whereas the diversity increased. Furthermore, the expanding scale amplified the mean change ratio of landscape metrics and eliminated local drastic changes and regional variation trends along an urban-to-rural gradient, which would be obvious at a finer block scale. Meanwhile, the adjusted R2 of GWR (Geographically Weighted Regression) models increased with an increasing block size, especially when the block scale changed from 1 km to 5 km. Odd-numbered block scales performed better than even-numbered block scales.

scholarly journals Analysis of the spatial differentiation and scale effects of the three-dimensional architectural landscape in Xi’an, China

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261846
Author(s):  
Wenjing Ren ◽  
Jingyuan Zhao ◽  
Xina Ma ◽  
Xiao Wang
Keyword(s):  
Spatial Autocorrelation ◽  
Urban Renewal ◽  
Urban Area ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Scale Effects ◽  
Effective Means ◽  
Three Dimensional ◽  
Landscape Patterns ◽  
Weighting Method

Three-dimensional landscape patterns are an effective means to study the relationship between landscape pattern evolution and eco-environmental effects. This paper selects six districts in Xi’an as the study area to examine the spatial distribution characteristics of the three-dimensional architectural landscape in the city’s main urban area using three-dimensional information on the buildings in 2020 with the support of GIS. In this study, two new architectural landscape indices—landscape height variable coefficient and building rugosity index—were employed in landscape pattern analysis, whilst a system of rigorous and comprehensive three-dimensional architectural landscape metrics was established using principal component analysis. A mathematical model of weighted change of landscape metrics based on the objective weighting method was applied to carry out scale analysis of the landscape patterns. Spatial statistical analysis and spatial autocorrelation analysis were conducted to comprehensively study the differentiation of three-dimensional architectural landscape spatial patterns. The results show that the characteristic scale of the three-dimensional landscape pattern in Xi’an’s main urban area is around 8 km. Moreover, the three-dimensional landscape of the buildings in this area is spatially positively correlated, exhibiting a high degree of spatial autocorrelation whilst only showing small spatial differences. The layout of the architectural landscape pattern is disorderly and chaotic within the second ring, whilst the clustering of patch types occurs near the third ring. Moreover, the building density in the Beilin, Lianhu, and Xincheng districts is large, the building height types are rich, and the roughness of the underlying surface is high, such that these are key areas to be improved through urban renewal. The height, volume, density, morphological heterogeneity, and vertical roughness of the architectural landscape vary amongst functional areas within the study area. This paper is the first to apply the study of spatial heterogeneity of three-dimensional landscape patterns to Xi’an. It does so in order to provide a quantitative basis for urban landscape ecological design for urban renewal and the rational planning of built-up areas, which will promote the sustainable development of the city’s urban environment.

scholarly journals Geographic context affects the landscape change and fragmentation caused by wind energy facilities

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7129 ◽  
Author(s):  
Jay E. Diffendorfer ◽  
Monica A. Dorning ◽  
Jolene R. Keen ◽  
Louisa A. Kramer ◽  
Robert V. Taylor
Keyword(s):  
Wind Energy ◽  
Landscape Pattern ◽  
Landscape Change ◽  
Road Networks ◽  
Landscape Fragmentation ◽  
Landscape Patterns ◽  
Core Area ◽  
Area Index ◽  
Geographic Context ◽  
The Impact

Wind energy generation affects landscapes as new roads, pads, and transmission lines are constructed. Limiting the landscape change from these facilities likely minimizes impacts to biodiversity and sensitive wildlife species. We examined the effects of wind energy facilities’ geographic context on changes in landscape patterns using three metrics: portion of undeveloped land, core area index, and connectance index. We digitized 39 wind facilities and the surrounding land cover and measured landscape pattern before and after facility construction using the amount, core area, and connectivity of undeveloped land within one km around newly constructed turbines and roads. New facilities decreased the amount of undeveloped land by 1.8% while changes in metrics of landscape pattern ranged from 50 to 140%. Statistical models indicated pre-construction development was a key factor explaining the impact of new wind facilities on landscape metrics, with pre-construction road networks, turbine spacing, and topography having smaller influences. As the proportion of developed land around facilities increased, a higher proportion of the facility utilized pre-construction developed land and a lower density of new roads were built, resulting in smaller impacts to undeveloped landscapes. Building of new road networks was also a predictor of landscape fragmentation. Utilizing existing development and carefully placing turbines may provide opportunities to minimize the impacts of new wind energy facilities.

Land Consolidation-Induced Effects on Local Landscape Patterns in Hilly and Mountainous Southwestern China

2011 ◽  
Vol 356-360 ◽  
pp. 2980-2990
Author(s):  
Fang Ling Fan ◽  
Chao Fu Wei ◽  
Shuai Yin
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Large Scale ◽  
Arable Land ◽  
Landscape Patterns ◽  
Land Consolidation ◽  
Southwestern China ◽  
Mountainous Area ◽  
Before And After ◽  
Land Consolidation Project

Land Consolidation Project (LCP), as a kind of drastic disturbance by human intentional activities, significantly changes landscape pattern. The information of landscape pattern from land-use map and planning map (scale: 1:2000) were extracted by taking the land consolidation project in hilly and mountainous area of Bashan Town, Zhong County, Chongqing, Southwestern China as an example. The whole landscape structure and each land use type class level metrics of landscape pattern were calculated. Then their effects on local landscape patterns were estimated by Fragstats for Arcview. Sixteen metrics had been chosen to describe the changes before and after LCP. The total area of the research region was 1037.45 hm2, and arable land area accounted for 80.95%, therefore heterogeneous map was mosaic. Land Leveling Project (LLP) got each patch of arable land expanded. The fragmentation was sharply reduced .The complex of patches edge was decreased. The shape of each field was ruled. And all above were beneficial for the growth of crop and plantation, especially in a large scale. LCP could reallocate fragment parcels and improve agricultural conditions.

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