A Workflow to Extract the Geometry and Type of Vegetated Landscape Elements from Airborne LiDAR Point Clouds

Rural European landscapes are characterized by a variety of vegetated landscape elements. Although it is often not their main function, they have the potential to affect river discharge and the frequency, extent, depth and duration of floods downstream by creating both hydrological discontinuities and connections across the landscape. Information about the extent to which individual landscape elements and their spatial location affect peak river discharge and flood frequency and severity in agricultural catchments under specific meteorological conditions is limited. This knowledge gap can partly be explained by the lack of exhaustive inventories of the presence, geometry, and hydrological traits of vegetated landscape elements (vLEs), which in turn is due to the lack of appropriate techniques and source data to produce such inventories and keep them up to date. In this paper, a multi-step methodology is proposed to delineate and classify vLEs based on LiDAR point cloud data in three study areas in Flanders, Belgium. We classified the LiDAR point cloud data into the classes ‘vegetated landscape element point’ and ‘other’ using a Random Forest model with an accuracy classification score ranging between 0.92 and 0.97. The landscape element objects were further classified into the classes ‘tree object’ and ‘shrub object’ using a Logistic Regression model with an area-based accuracy ranging between 0.34 and 0.95.

Spatial Grain Effects of Urban Green Space Cover Maps on Assessing Habitat Fragmentation and Connectivity

The scientific evaluation of landscape fragmentation and connectivity is important for habitat conservation. It is strongly influenced by the spatial resolution of source maps, particularly in urban environments. However, there is limited comprehensive investigation of the spatial grain effect on urban habitat and few in-depth analysis across different urban gradients. In this paper, we scrutinize the spatial grain effects of urban green space (UGS) cover maps (derived from remote sensing imagery and survey data) with respect to evaluating habitat fragmentation and connectivity, comparing among different urban gradient scenarios (downtown, urban periphery, and suburban area) in Hangzhou, a megacity in China. The fragmentation was detected from three indices, including Entropy, Contagion, and Hypsometry. Then morphological spatial pattern analysis (MSPA) was applied for the landscape element identification. The possibility of connectivity (PC) and patch importance (dPC) were proposed for measuring the landscape connectivity based on Cores and Bridges from MSPA results. The results indicate that the farther the location is from downtown, the less sensitive the landscape element proportion to the spatial resolution. Among the three fragmentation indices, the overall hypsometry index has the lowest sensitivity to the spatial resolution, which implies this index’s broader application value. Considering connectivity, high spatial resolution maps are appropriate for analyzing highly heterogeneous urban areas, while medium spatial resolution maps are more applicable to urban periphery and suburban area with larger UGS patches and less fragmentation. This study suggests that the spatial resolution of UGS maps substantially influence habitat fragmentation and connectivity, which is critical for decision making in urban planning and management.

Bio-Tile: An Intelligent Hybrid-Infrastructure

Bio-tile is a multipurpose artifact designed for protecting the coastline from erosion while creating a landscape element and an architectural experience for visitors. Bio-tile performs as a mitigation strategy to slow down erosion while promoting biodiversity. This paper describes the methodology used to develop the bio-tile as the nexus between digital and environmental for resolving coastline challenges through material tectonics. A non-linear algorithm and nature’s inherent code are used to develop the Bio-tile, a nature-based hybrid infrastructure. This approach aims to generate a performance-oriented design by using emergence theory to construct shoreline elements adaptive to climatic conditions.

Rationality in pier geometry of Kintaikyo Bridge from viewpoint of river engineering

The Kintaikyo Bridge, with its elegant wooden arches, has a unique pier shape and continues to be loved by residents and visitors alike. Although this bridge is an active footbridge and an important landscape element along with the Nishikigawa River and its river beach, the rationality or irrationality of the shape of its piers remains unknown. This paper is intended to clarify the river engineering characteristics of the piers for the first time by conducting 1/129 scale hydraulic model experiments. The shapes tested were a perfect spindle shape (which has been adopted as a common theory for many years) and a reconstructed current shape based on the spindle shape, and for comparison, an oval and a non-regular hexagon shape with the same width and area. The current shape, along with the spindle shape, suppressed the water level rise around the pier more than the others. As for the riverbed fluctuation, the current shape slightly increased the scour more than the others, but it also maximized the sedimentation around the scoured part. In other words, the current shape has the potential to facilitate the procurement of sediment for post-flood restoration. In addition, the current shape overwhelmingly reduced the statistical dispersion associated with the experiment, suggesting that it stabilizes the trend of riverbed fluctuation even during actual floods. Based on the results, the future conservation of the Kintaikyo Bridge was also discussed.

Deep Learning Image Feature Recognition Algorithm for Judgment on the Rationality of Landscape Planning and Design

This paper uses an improved deep learning algorithm to judge the rationality of the design of landscape image feature recognition. The preprocessing of the image is proposed to enhance the data. The deficiencies in landscape feature extraction are further addressed based on the new model. Then, the two-stage training method of the model is used to solve the problems of long training time and convergence difficulties in deep learning. Innovative methods for zoning and segmentation training of landscape pattern features are proposed, which makes model training faster and generates more creative landscape patterns. Because of the impact of too many types of landscape elements in landscape images, traditional convolutional neural networks can no longer effectively solve this problem. On this basis, a fully convolutional neural network model is designed to perform semantic segmentation of landscape elements in landscape images. Through the method of deconvolution, the pixel-level semantic segmentation is realized. Compared with the 65% accuracy rate of the convolutional neural network, the fully convolutional neural network has an accuracy rate of 90.3% for the recognition of landscape elements. The method is effective, accurate, and intelligent for the classification of landscape element design, which better improves the accuracy of classification, greatly reduces the cost of landscape element design classification, and ensures that the technical method is feasible. This paper classifies landscape behavior based on this model for full convolutional neural network landscape images and demonstrates the effectiveness of using the model. In terms of landscape image processing, the image evaluation provides a certain basis.

The Visual Effect of Signboards on the Vitality of the Streetscapes Using Eye-Tracking

This study focuses on whether signboards attract people’s visual concentration as a foreground element of the streetscape and check the difference in streetscape image according to the area of the signboard. For this purpose, 133 street-view photographs were taken at five major commercial districts in Seoul and 17 photos were selected for this study. The photos were then classified into the High Signboard Group (HSG) and Low Signboard Group (LSG) according to the area of the signboards and conducted eye-tracking experiments and surveys. Finally, data from 33 people were collected and a t-test was conducted to identify differences between the two groups. As a result, the number of fixations, the fixation time, and the revisits of fixation on signboards were measured higher in HSG, and the distance of gaze movement (saccade) was lower. The results of the image survey analysis showed that HSG groups had low streetscape satisfaction, signboard satisfaction, and streetscape aesthetic quality. However, Dynamic and Interesting factors were high. Taken together, the signboard can be seen as a landscape element that focuses attention by giving people an active and interesting image, which shows the importance and possibility of using signboards in future streetscape design.

Gradient analysis of landscape variation in Norway

SUMMARYA multitude of landscape characterisation and mapping methods exist, but few methods take into account that landscapes properties vary in a gradual, continuous manner along multiple directions of variation. In this study, we used gradient analytic methods, rooted in ecological continuum theory, to analyse landscape variation throughout Norway. The aim is to explain differences in landscape properties in the simplest possible way, by identifying ‘complex landscape gradients’ (CLGs), i.e. composite gradients of co-occurring landscape elements and properties.We collected data by stratified sampling of 100 test areas (20×20 km), in which we delineated a total of 3966 observation units (landscape polygons 4–30 km²) based on geomorphological criteria. For each observation unit, 85 landscape variables were recorded. We identified patterns of variation in landscape element composition by parallel use of two multivariate statistical methods, detrended correspondence analysis (DCA) and global nonmetric multidimensional scaling (GNMDS).The analyses revealed that the most important properties explaining differences in total landscape elements composition was location of the landscape relative to the coastline and coarse-scale landform variation. Most landscape elements had distinct optima within specific segments along broad-scale complex-gradients in landscape properties. A tentative landscape-type hierarchy was built by an iterative procedure by which the amount of compositional turnover in landscape-element composition between adjacent types was standardised. Six ‘major landscape types’ were identified based on geomorphological criteria. Within each major type, we identified a unique set of 2–5 important CLGs, representing geo-ecological, bio-ecological, and land use-related landscape variation. Minor landscape types were obtained by combining segments along two or more CLGs.The study shows that geological diversity, biological diversity and human land-use are tightly intertwined at the landscape level of ecological complexity, and that predominantly abiotic processes control and constrain both biotic processes and human land use.

Identifikasi kesesuaian tata letak tanaman berdasarkan konsep Tri Mandala (studi kasus Pura Puseh lan Desa, Desa Pakraman Batuan dan Desa Pakraman Kebon Singapadu)

Temple is a shrine of Hindu religion and is one of the places for the application of traditional Balinese garden. Temples’s garden should use upakara plant that not only serves as a landscape element but also can be used as a means offering (upakara). The concept of plant placement in the temple’s garden should also characterize the local philosophy, including Tri Mandala. The purpose of this study is to identify plants type and conformity of plants placement in Pura Puseh lan Desa, Desa Pakraman Batuan and in Pura Puseh Lan Desa, Desa Pakraman Kebon Singapadu based on Tri Mandala concept. The study uses survey methods with data collection techniques, through field observations, interviews, and library studies. The results showed that the two temples used upakara plants and ornamental plants as soft elements. The concept of plants placement is largely in accordance with the concept of Tri Mandala.

Water in Descriptions of Global Geoparks: Not Less Important than Geology?

Water is an important landscape element of protected areas, but its significance to geoparks (parks representing geological heritage) is still unclear. The content of the official, standardized descriptions of the UNESCO global geoparks (144 in total) was analyzed in order to understand the consideration of water by geopark creators/managers. It was found that water objects (seas/oceans, rivers, and lakes are most common) are mentioned in 55% of these descriptions, and 47% of the latter bear photos of water objects. Moreover, water is generally strongly related to geological heritage (in 80% of cases). These findings imply a significant attention to hydrodiversity in geoparks (apparently, official descriptions reflect global geopark practice and intentions). This attention does not differ between Europe, Southeast Asia, and Latin America. It has increased in the 2010s relatively to the 2000s. The registered consideration of water in geoparks can be explained differently, and one plausible hypothesis links it to an increasing willingness of geopark creators/managers to demonstrate the natural integrity of geological heritage landscapes. Such attention to water is suitable to deliver the knowledge of this integrity to tourists, but it increases the risks of visitor distraction from geological heritage, shifting to easy-to-understand and beautiful water objects.