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Sky view factor calculation in complex urban geometry with terrestrial LiDAR

PHYSICAL GEOGRAPHY 2021年第4期42卷 374-394页

作者： Heo, Han Kyul Lee, Dong Kun Park, Chae Yeon Kim, Ho Gul Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Coll Agr Life Sci Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Cheongju Univ Dept Human Environm Design Major Landscape Urban Planning Cheongju South Korea

The sky view factor (SVF) is a key indicator in urban structures and is used in research in various fields. Recently, a method was developed to compute SVF in complex urban areas using airborne light detection and ranging (LiDAR). However, it displays low accuracy in areas with trees and buildings, owing to the limited resolution of airborne LiDAR data. In this study, the accuracy of the SVF calculation using terrestrial LiDAR was verified by comparing the reference data calculated from fisheye photographs at the same positions. Our results indicate that the SVF derived using terrestrial LiDAR has higher accuracy. We also tested whether a higher accuracy could be obtained by increasing the spatial resolution of the LiDAR data. The SVF estimation is more accurate when using terrestrial LiDAR, displaying a 60% reduction in the maximum error compared with the SVF estimated using airborne LiDAR. In addition, according to this research, a voxel size of 2.5 cm is sufficient for estimating SVF in a complex urban area. This resolution can be achieved through mobile LiDAR. Therefore, it is anticipated that the SVF calculation technique used in this study will be more practical when used with mobile LiDAR.

关键词： Urban structure voxel 3D Point Cloud tree effect sensitivity analysis

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Multi-hazard mapping of droughts and forest fires using a multi-layer hazards approach with machine learning algorithms

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GEOMATICS NATURAL HAZARDS & RISK 2022年第1期13卷 2649-2673页

作者： Piao, Yong Lee, Dongkun Park, Sangjin Kim, Ho Gul Jin, Yihua Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Res Inst Agr Life Sci Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Cheongju Univ Dept Human Environm Design Cheongju South Korea Yanbian Univ Agr Coll Dept Landscape Architecture Yanji South Korea

The frequency of forest fires in Gangwon-do has increased in recent years due to advanced climate change and dry weather. The Gangwon-do area, the largest forest area in South Korea, has rich forest resources and ecological diversity, therefore there is an urgent need for more effective monitoring and prevention of forest fires. This study proposed a method to establish a multi-hazard probability map (MHPM) for two related hazards (forest fires and droughts) based on a multi-layer hazards approach and machine learning algorithms for monitoring forest fire susceptibility areas. First, extreme drought years were selected using the standardized precipitation index (SPI). An inventory drought map was constructed using the enhanced vegetation index (EVI) based on satellite image data. Then, 70% of the inventory maps based on forest fires and droughts were used to construct hazard susceptibility maps and 30% of these were used to validate three machine learning models: Classification and Regression Trees (CART), Random Forest (RF) and boosted Regression Trees (BRT). Eleven conditioning factors related to climate, topography, hydrology, and human activities were considered for the analysis. The results of the three models were then validated using the area under the receiver operating characteristic (ROC) curve (AUC), and the best performing model was selected (BRT;forest fire: 85%, drought: 80%). Finally, the susceptibility maps of forest fires and droughts were combined to construct the MHPM for the Gangwon Province, South Korea. The results show that the MHPM of forest fires and droughts constructed in this study is valid and reliable. This multi-hazard map can provide key information for planners and decision-makers to develop forest fire prevention and management plans and to more effectively prevent and reduce the frequency of forest fires.

关键词： Multi-hazard natural hazard forest fire drought remote sensing

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Exploring Google Street View with deep learning for crop type mapping

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2021年 171卷 278-296页

作者： Yan, Yulin Ryu, Youngryel Seoul Natl Univ Interdisciplinary Program Agr & Forest Meteorol Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul 151921 South Korea

Ground reference data are an essential prerequisite for supervised crop mapping. The lack of a low-cost and efficient ground referencing method results in pervasively limited reference data and hinders crop classification. In this study, we apply a convolutional neural network (CNN) model to explore the efficacy of automatic ground truthing via Google Street View (GSV) images in two distinct farming regions: Illinois and the Central Valley in California. We demonstrate the feasibility and reliability of our new ground referencing technique by performing pixel-based crop mapping at the state level using the cloud-based Google Earth Engine platform. The mapping results are evaluated using the United States Department of Agriculture (USDA) crop data layer (CDL) products. From similar to 130,000 GSV images, the CNN model identified similar to 9,400 target crop images. These images are well classified into crop types, including alfalfa, almond, corn, cotton, grape, rice, soybean, and pistachio. The overall GSV image classification accuracy is 92% for the Central Valley and 97% for Illinois. Subsequently, we shifted the image geographical coordinates 2-3 times in a certain direction to produce 31,829 crop reference points: 17,358 in Illinois, and 14,471 in the Central Valley. Evaluation of the mapping results with CDL products revealed satisfactory coherence. GSV-derived mapping results capture the general pattern of crop type distributions for 2011-2019. The overall agreement between CDL products and our mapping results is indicated by R-2 values of 0.44-0.99 for the Central Valley and 0.81-0.98 for Illinois. To show the applicational value of the proposed method in other countries, we further mapped rice paddy (2014-2018) in South Korea which yielded fairly well outcomes (R-2 = 0.91). These results indicate that GSV images used with a deep learning model offer an efficient and cost-effective alternative method for ground referencing, in many regions of the world.

关键词： Crop type mapping Deep learning Google Earth Engine Google Street View Ground referencing

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Mapping riparian habitat using a combination of remote-sensing techniques

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2016年第5期37卷 1069-1088页

作者： Jeong, Seung Gyu Mo, Yongwon Kim, Ho Gul Park, Chong Hwa Lee, Dong Kun Seoul Natl Univ Res Inst Agr & Life Sci Seoul South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Grad Sch Environm Studies Dept Landscape Architecture Seoul South Korea Seoul Natl Univ Coll Agr Life Sci Dept Landscape Architecture & Rural Syst Engn Seoul South Korea

Light detection and ranging (lidar) and object-oriented classification (OOC) can be used to overcome the shortcomings of the traditional pixel-based classification (PBC) of coarse spatial resolution data, such as Landsat data, for habitat mapping in riparian zones. The purposes of this study were to investigate methods to classify multispectral data and lidar for riparian habitat mapping, and to identify major habitat components for two target species. The mapping of riparian habitat based on OOC and Decision Tree Classification (DTC) was carried out by merging vertical data from lidar and spectral data of high-resolution imagery. Our results showed an overall classification accuracy of 88.2%. In particular, small and continuous habitat types, such as short and tall grasses, rock outcrop and gravel, and riffles, improved the classification accuracy compared with the pixel-based methods. The habitat patches and paths for each target species were identified by incorporating the point data from the field survey and the outcomes of image classification. Our study demonstrated that the proposed methodology can be successfully used for the identification and restoration of fragmented riparian habitats, and can offer an opportunity to obtain high classification accuracies for micro-habitat components in dynamic riverine areas.

关键词： Biological surveys Classification Habitat improvement Ecological distribution Microhabitats Mapping Habitat LIDAR Methodology Lidar applications Remote sensing LANDSAT Remote Sensing Habitats Gravel Grasses Trees Aquatic Habitats Riffles

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landscape design methodology as perceived through memory schema with user experience

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International Journal of Urban Sciences 2020年第2期24卷 282-296页

作者： Park, Suji Kim, Hanbai Han, Soyoung Kwon, Yoonku The Institute of Urban Science University of Seoul Seoul South Korea Dept. of Landscape Architecture University of Seoul Seoul South Korea Landscape Architecture Program Virginia Tech Blacksburg United States Dept. of Landscape Architecture Korea National College of Agriculture and Fisheries Jeonju South Korea

This study examined interrelationships between memory schema incised into landscapes pursued by designers and user’s responses by using multiple case study methods. We selected three cases according to three dimensions of landscape design method related to memory schema to examine each concept thoroughly;(1) Vietnam Veterans Memorial in USA as a context design, (2) Diana, Princess of Wales Memorial Fountain in England as a transformation design and, (3) Sutton Place which is imaginary design of Geoffery Jellicoe as an imagination design. Seonyudo Park in Korea has been selected to review with all the aspects of three type of memory schema. Our findings highlight that memory schema as a landscape design metaphor has been emphasizing the five human senses and internal experiences. Memories could be transformed into various forms and meanings in landscapes according to designers’ intentions. Furthermore, when one’s recalled experience is expressed through landscape, which is expressed through a schema, and the user who uses the landscape correlates to the memory. This study suggests that landscape design with a memory schema can serve as a creative design medium that applies the positive effects of design experience to landscapes with humans. © 2019, © 2019 The Institute of Urban Sciences.

关键词： design methodology Experience landscape design memory schema

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The effects of tree characteristics on rainfall interception in urban areas

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landscape AND ECOLOGICAL ENGINEERING 2019年第3期15卷 289-296页

作者： Yang, Byungsun Lee, Dong Kun Heo, Han Kyul Biging, Gregory Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 08826 South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul 08826 South Korea Univ Calif Berkeley Dept Environm Sci Policy & Management Berkeley CA 94720 USA

Trees in urban areas have significant effects on the urban ecosystem. They can be used to improve the water cycle in urban areas by increasing evaporation and reducing runoff through rainfall interception. Street trees placed in planters on impervious areas reduce runoff by intercepting rainfall and by temporarily storing raindrops on leaves. Therefore, understanding tree canopy geometry and the effect of rainfall interception is important in urban hydrology. In this study, we assessed the effect of tree canopy morphology on rainfall interception using four major street tree species, Sophora japonica L., Ginkgo biloba L., Zelkova serrata (Thunb.) Makino, and Aesculus turbinata Blume, in Seoul, South Korea. We measured throughfall for each tree and also derived three-dimensional data of tree canopy morphology with a terrestrial laser scanner. Tree height, canopy crown width, leaf area index (LAI), leaf area density, mean leaf area, and mean leaf angle were used to determine canopy morphology. The interception rate was mostly affected by the LAI;a higher LAI tended to result in a higher interception rate. Leaf area affected the rainfall interception rate when trees had similar LAIs. These findings on individual tree canopy rainfall interception can help us to understand the importance of rainfall interception in hydrology and for ecological restoration when planning urban green spaces.

关键词： Terrestrial laser scanner Urban water cycle Leaf area index Runoff Tree species

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The effect of load reduction on underground concrete arch structures in embedded trench installations

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2020年第0期98卷 103240-000页

作者： Kang, Junsuk Im, Hwangi Park, Jong Sup Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul 08826 South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 08826 South Korea Seoul Natl Univ Interdisciplinary Program Urban Planning Seoul 08826 South Korea Seoul Natl Univ Res Inst Agr & Life Sci Seoul 08826 South Korea Sangmyung Univ Dept Civil Engn Cheonan 31066 South Korea

This analytical and experimental study examined the effects of using EPS Geofoam to reduce the earth pressure on underground arch structures. The finite element models developed using 2-D and 3-D approaches and nonlinear soil models were calibrated using field testing data. The behavior of the structure was investigated for varying thicknesses of the geofoam layer to determine the optimum level. The results of the finite element analysis revealed a load reduction of more than 80% when using the embedded trench installation (ETI) method. These results were within 10% of the experimentally measured values, demonstrating that the ETI method is an effective way to reduce earth pressure on underground arch structures.

关键词： Underground arch structures EPS geofoam Earth pressure ETI

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Continuous observation of vegetation canopy dynamics using an integrated low-cost, near-surface remote sensing system

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AGRICULTURAL AND FOREST METEOROLOGY 2019年 264卷 164-177页

作者： Kim, Jongmin Ryu, Youngryel Jiang, Chongya Hwang, Yorum Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Dept Landscape Architecture Seoul South Korea Seoul Natl Univ Dept Rural Syst Engn Seoul South Korea Seoul Natl Univ Interdisciplinary Program Agr & Forest Meteorol Seoul South Korea Seoul Natl Univ Brain Korea Plus Team 21 Seoul South Korea

Continuous monitoring of vegetation indices (VIs) the fraction of absorbed photosynthetically active radiation (fPAR) and leaf area index (LAI) through satellite remote sensing has advanced our understanding of biosphere-atmosphere interactions. Substantial efforts have been put into monitoring individual variables in the field, but options to concurrently monitor VIs, fPAR, and LAI in-situ have been lacking. In this paper, we present the Smart Surface Sensing System (4S), which automatically collects, transfers and processes VIs, fPAR and LAI data streams. The 4S consists of a microcomputer, controller and camera, a multi-spectral spectrometer built in with a light-emitting diode (LED) and an Internet connection. Lab testing and field observations in a rice paddy site that experiences wet summer monsoon seasons confirmed the linear response of 4S to light intensities in the blue, green, red and near-infrared spectral channels, with wide ranging temperatures and humidity having only a minor impact on 4S throughout the growing season. Applied over an entire rice growing season (day of year [DOY] 120 - 248), VIs and (PAR from 4S were linearly related to corresponding VIs from a reference spectrometer (R-2 = 0.98;NDVI, R-2 = 0.96;EVI) and the LAI-2200 instrument (R-2 = 0.76), respectively. Integration of gap fraction-based LAI from LED sensors and a green index from the micro-camera allowed tracking of the seasonality of green LAI. The continuous and diverse nature of 4S observations highlights its potential for evaluating satellite remote sensing products. We believe that 4S will be useful for the expansion of ecological sensing networks across multiple spatial and temporal scales.

关键词： Leaf area index NDVI EVI fPAR LED Camera

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Seasonal variations in photosynthetic parameters and leaf area index in an urban park

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URBAN FORESTRY & URBAN GREENING 2015年第4期14卷 1059-1067页

作者： Kimm, Hyungsuk Ryu, Youngryel Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul 151921 South Korea Seoul Natl Univ Interdisciplinary Program Agr & Forest Meteorol Seoul 151921 South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 151921 South Korea Seoul Natl Univ Res Inst Agr & Life Sci Seoul 151921 South Korea

Parks account for a large proportion of green spaces in urban regions, but most previous studies have focused on the values of recreational services in urban parks-carbon uptake by plants in urban parks has been studied less extensively. Urban parks typically form complex landscapes in space and time by integrating multiple species with open canopies. Thus, to better understand canopy photosynthesis in urban park, measuring spatial and temporal variations in photosynthetic parameters and canopy structural variables is essential. Here, we report seasonal and spatial variations in two key photosynthetic parameters (V-cmax and J(max) which are the maximum rates of carboxylation and electron transport, respectively) and leaf area index (LAI) in Seoul Forest Park. During the peak growing season, we found an eightfold difference (20 to 149 mu mol m(-2) s(-1)) and fourfold difference (38 to 141 mu mol m(-2) s(-1)) in V-cmax and J(max), respectively, across 10 species. Over the seasons, two woody species (Zelkova serrata (Thunb.) Makino and Prunus yedoensis Matsum), respectively showed three- to fivefold differences in V-cmax and two- to fivefold differences in Jmax. We evaluated whether leaf nitrogen contents could predict V-cmax and J(max), and found significant correlations among the three variables during the peak growing season across 10 species, but no significant correlations among them over the seasons in the two woody species. LAI computed using in- situ observations and satellite remote-sensing imagery showed a high spatial heterogeneity during the growing season. These results highlight the considerable spatial and temporal variability in photosynthetic parameters and LAI, which implies that individual tree-based three-dimensional canopy modeling will be essential for accurate estimation of canopy photosynthesis in urban parks. (C) 2015 Elsevier GmbH. All rights reserved.

关键词： Leaf area index Leaf nitrogen Maximum rate of carboxylation Maximum rate of electron transport Photosynthesis Urban park

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Comprehensive assessments of carbon dynamics in an intermittently-irrigated rice paddy

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AGRICULTURAL AND FOREST METEOROLOGY 2020年第0期285卷 107933-000页

作者： Hwang, Yorum Ryu, Youngryel Huang, Yan Kim, Jongho Iwata, Hiroki Kang, Minseok Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Natl Ctr AgroMeteorol Seoul South Korea Shinshu Univ Fac Sci Dept Environm Sci Matsumoto Nagano Japan

Rice is a major crop that feeds more than half of the global population. Rice paddies play a complex role in the carbon cycle by emitting CH4 to the atmosphere while either sequestering or releasing CO2 to the atmosphere. Here, we present 3.5 years of eddy covariance measurements of CO2 and CH4 fluxes over an intermittently irrigated, single crop rice paddy in South Korea in tandem with carbon stock measurements for leaves, stems, grains, and roots. The rice paddy acted as a slight sink or neutral in CO2 (-47 +/- 51 g C m(-2) y(-1);mean +/- 95% confidence interval) with 941 +/- 130 g C m(-2) y(-1) and 894 +/- 108 g C m(-2) y(-1) as the gross primary production (GPP) and ecosystem respiration (Reco), respectively. The mean annual net primary productivity (NPP) was 666 +/- 31 g C m(-2) y(-1), which was partitioned to leaves (9%), stems (30%), grains (51%), and roots (10%), for a harvest index of 57%. The paddy emitted 20.6 +/- 1.5 g C m(-2) y(-1) in the form of CH4, of which between 82 and 96% was emitted during the cultivation period (similar to 132 days). The CH4 flux showed a mid-season decline caused by mid-season drainage, which produced aerobic soil conditions that inhibited CH4 emissions. The proportion of estimated ebullitive flux to total CH4 flux ranged from 10 to 17% during the cultivation period. GPP, Reco, and CH4 fluxes varied by 12%, 11%, and 7%, respectively, over the 3-year period. When considering the harvest and the global warming potential of CH4, the paddy shifted from a greenhouse gas sink to a strong source (2,741 +/- 468 g CO2 eq m(-2) y(-1)). These findings will improve our understanding of carbon budgets and cycles, and help develop greenhouse gas and water management strategies for rice paddies.

关键词： Rice paddy CO2 flux CH4 flux Carbon allocation Drainage Harvest index

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