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

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.

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

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.

The Relationship between Landscape Metrics and Facial Expressions in 18 Urban Forest Parks of Northern China

Urban forests are an important green infrastructure that positively impacts human well-being by improving emotions and reducing psychological stress. Questionnaires have been used frequently to study the influence of forest experiences on mental health; however, they have poor controllability and low accuracy for detecting immediate emotions. This study used the alternative approach of facial reading, detecting the facial expressions of urban forest visitors and their relationships with the landscape metrics. Using the microblogging site, Sina Weibo, we collected facial photos of 2031 people visiting 18 different forest parks across Northern China in 2020. We used satellite imagery analysis to assess the elevation and pattern sizes of green space and blue space areas. Age and location were taken as independent variables affecting facial expressions, which were categorized as happy or sad. With increases in green space and intact park areas, people showed a higher frequency of expressing happy scores. The results showed that the forest experience frequently elicited positive emotions, suggesting that creating and maintaining urban green spaces enhance people’s quality of life.

Long-Term Land Use and Landscape Pattern Changes in a Marshland of Hungary

This paper presents the trends of landscape change in the marshes on the southern shore of Lake Balaton, a wetland profoundly transformed by human activities. The study does not only deal with alterations in the areal proportions of land use classes but also quantitatively analyses landscape pattern, comparing landscape metrics on different dates. Based on the findings, proposals for rehabilitation are made. Through the restoration of wetland habitats, the provision level of ecosystem services can be raised. Landscape change was investigated from 1783 to 2020. For this purpose, archive maps were digitized, CORINE land cover datasets corrected by Sentinel-2 imagery were employed and from the vector data, the proportions of land use classes were calculated. For landscape pattern perimeter, area, neighbourhood and diversity metrics were used, calculated by ArcGIS vLATE plugin. It was pointed out that in land cover, the share of wetlands considerably declined over the centuries but in recent decades somewhat expanded. In the 20th century, grasslands were the predominant land use class, but with the spread of other categories, land use has become more complex. Landscape metrics show an increased fragmentation of natural habitats, a higher number of patches and edge density, leading to higher landscape diversity. Rehabilitation proposals include the establishment of rainwater retention reservoirs, the conversion of arable land which cannot be cultivated profitably to close-to-natural classes (first of all, grasslands) and the plantation of gallery forests of native tree species along canals. In comparison with other regions, similar temporal trends and spatial distributions are observed. For instance, the internationally well-known transformation of the Doñana wetland started later but was more intensive than in Hungary.

Landscape Characteristics Influence Ranging Behavior of Asian Elephants at The Human-Wildlands Interface in Myanmar

ContextAsian elephant numbers are declining across much of their range driven largely by serious threats from land use change resulting in habitat loss and fragmentation. Myanmar, holding critical range for the species, is undergoing major developments due to recent sociopolitical changes. To effectively manage and conserve the remaining populations of endangered elephants in the country, it is crucial to understand their ranging behavior.ObjectivesOur objectives were to (1) estimate the sizes of dry, wet and annual ranges of free ranging elephants in Myanmar; and quantify the relationship between dry season (the period when human-elephant interactions are the most likely to occur) range size and configurations of agriculture and natural vegetation within the range, and 2) evaluate how percentage of agriculture within dry core range (50% AKDE range) of elephants relates to their daily distance traveled.MethodsWe used autocorrelated kernel density estimator (AKDE) based on a continuous-time movement modeling (ctmm) framework to estimate dry season (26 ranges from 22 different individuals), wet season (12 ranges from 10 different individuals), and annual range sizes (8 individuals), and reported the 95%, 50% AKDE, and 95% Minimum Convex Polygon (MCP) range sizes. We assessed how landscape characteristics influenced range size based on a broad array of 48 landscape metrics characterizing aspects of vegetation, water, and human features and their juxtaposition in the study areas. To identify the most relevant landscape metrics and simplify our candidate set of informative metrics, we relied on exploratory factor analysis and Spearman’s rank correlation coefficient. Based on this analysis we adopted a final set of metrics into our regression analysis. In a multiple regression framework, we developed candidate models to explain the variation in AKDE dry season range sizes based on the previously identified, salient metrics of landscape composition. ResultsElephant dry season ranges were highly variable averaging 792.0 km2 and 184.2 km2 for the 95% and 50% AKDE home ranges, respectively. We found both the shape and spatial configuration of agriculture and natural vegetation patches within an individual elephant’s range play a significant role in determining the size of its range. We also found that elephants are moving more (larger energy expenditure) in ranges with higher percentages of agricultural area.ConclusionOur results provide baseline information on elephant spatial requirements and the factors affecting them in Myanmar. This information is important for advancing future land use planning that takes into account space-use requirements for elephants. Failing to do so may further endanger already declining elephant populations in Myanmar and across the species’ range.

Quantification of Urban Patterns and Processes through Space and Time Using Remote Sensing Data: A Comparative Study between Three Saudi Arabian Cities

Saudi Arabia has developed rapidly over the last five decades in the wake of an extensive development programme implemented by the government throughout the entire country. Several previous studies have measured the extent and rate of urbanization in Saudi Arabian cities, but most of this research used only remote sensing data or a single index to explain urban growth patterns. This study used satellite data and a set of landscape metrics to quantify the spatiotemporal urban growth patterns and processes in three Saudi Arabian cities–Riyadh, Jeddah and Makkah. First, Landsat images were collected and classified for the years 1985, 1990, 2000, 2007, 2014 and 2020. Classification was carried out through an object-based image analysis (OBIA) to map the extent of urbanization. The classified maps were then used to compute seven landscape metrics to determine the spatial configuration of urban areas. The spatial metrics were calculated for the entire landscape and across buffer zones that were delineated from the urban core centre of each city. The overall accuracies were >94% for all the classified maps. The spatiotemporal results indicated that all three cities have experienced significant urban growth during the last four decades. Urban patterns in Jeddah were more dispersed than in Riyadh, which showed aggregated patterns (especially in recent years), while urban growth in Makkah tended to be more fragmented. The urban form in Riyadh was relatively simple, while a complex form was associated with Makkah and Jeddah. Understanding the rates, patterns, processes and trajectories of changes to urban land use is essential for various decision-making processes.

Quantifying how urban landscape heterogeneity affects land surface temperature at multiple scales

Background Landscape metrics have been widely applied to quantifying the relationship between land surface temperature and urban spatial patterns and have received acceptable verification from landscape ecologists but some studies have shown their inaccurate results. The objective of the study is to compare landscape metrics and texture-based measures as alternative indices in measuring urban heterogeneity effects on LST at multiple scales. Results The statistical results showed that the correlation between urban landscape heterogeneity and LST increased as the spatial extent (scale) of under-study landscapes increased. Overall, landscape metrics showed that the less fragmented, the more complex, larger, and the higher number of patches, the lower LST. The most significant relationship was seen between edge density (ED) and LST (r = − 0.47) at the sub-region scale. Texture measures showed a stronger relationship (R2 = 34.84% on average) with LST than landscape metrics (R2 = 15.33% on average) at all spatial scales, meaning that these measures had a greater ability to describe landscape heterogeneity than the landscape metrics. Conclusion This study suggests alternative measures for overcoming landscape metrics shortcomings in estimating the effects of landscape heterogeneity on LST variations and gives land managers and urban planners new insights into urban design.