Article
Environmental Sciences
Zehu Hong, Weiheng Xu, Yun Liu, Leiguang Wang, Guanglong Ou, Ning Lu, Qinling Dai
Summary: In this study, a parametric estimation model combining Sentinel-1 and Sentinel-2 images was developed to accurately estimate the three-dimensional green volume (3DGV) of urban green space (UGS). The results demonstrated the potential of combining Sentinel-1 and Sentinel-2 images for 3DGV retrieval in UGS.
Article
Remote Sensing
Wenbo Yu, Zhenfeng Shao, Xiao Huang, Deren Li, Yewen Fan, Xiaodi Xu
Summary: This study introduces a novel framework to detect cross-city communities in urban agglomerations using fine-grained mobile signaling data. The results show the existence of potential communities at different scales, which can benefit transportation planning, urban zoning, and administrative boundary re-delineation.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Public, Environmental & Occupational Health
Jingyuan Chen, Cheng Wang, Yunbin Zhang, Dan Li
Summary: The reasonable distribution of urban green space (UGS) is crucial for improving the health level of a city. This study examines the central urban area of Hefei as an example and evaluates the accessibility of UGS under different transportation modes and time thresholds. The study also analyzes the spatial distribution equilibrium of UGS by integrating accessibility evaluation results with recreational data. It provides practical guidance for optimizing the distribution of UGS.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Construction & Building Technology
Mengru Zhang, Fei Zhang, Daosheng Chen, Mou Leong Tan, Ngai Weng Chan
Summary: This study investigates the prediction of local land surface temperature using vegetation and landscape indices as independent variables and gray-green space. The findings show that the Gradient Boosting Decision Tree (GBRT) model has the best prediction effect, and the proportion of urban green space (UGS) patches in the landscape area is the most influential index. The study highlights the importance of considering gray space and building materials in mitigating the heat island effect and improving thermal comfort in urban areas.
BUILDING AND ENVIRONMENT
(2022)
Article
Ecology
Ping Chang, Anton Stahl Olafsson
Summary: This study utilized multiscale geographically weighted regression to examine the relationship between landscape variables and nature experiences, highlighting the importance of context and scale effects.
Article
Environmental Sciences
Daosheng Chen, Fei Zhang, Mengru Zhang, Qingyan Meng, Chi Yung Jim, Jingchao Shi, Mou Leong Tan, Xu Ma
Summary: This study investigated the influence of urban green space landscape and vegetation factors on surface temperature in Urumqi city in northwest China. Numerical models were developed using remote sensing techniques to predict surface temperature. The results showed that a combination of landscape metrics and vegetation indexes can effectively predict surface temperature, with the random forest model demonstrating the highest accuracy. The most influential factor was found to be the difference vegetation index.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Biodiversity Conservation
Songze Wu, Dongyan Wang, Zhuoran Yan, Xingjia Wang, Jiaqi Han
Summary: This study investigates the spatial and temporal variations, landscape patterns, and driving forces of urban green spaces (UGSs) in Changchun from 1990 to 2020. The results show that the evolution of UGSs can be categorized into three stages: significant decline, balance between increase and decrease, and surge increase, accompanied by noticeable landscape changes. Various factors, including natural conditions, urbanization, and greening policies, have contributed to these changes. In the third decade of the research period, UGSs greatly expanded, reflecting achievements in UGS construction under the background of ecological civilization.
ECOLOGICAL INDICATORS
(2023)
Article
Remote Sensing
Yong Cheng, Wei Wang, Zhoupeng Ren, Yingfen Zhao, Yilan Liao, Yong Ge, Jun Wang, Jiaxin He, Yakang Gu, Yixuan Wang, Wenjie Zhang, Ce Zhang
Summary: Accurate extraction of urban green space is critical for preserving urban ecological balance and enhancing urban life quality. This study proposed a novel deep learning method called MFFTNet, which utilizes multi-scale feature fusion, transformer network, and vegetation feature extraction to effectively extract urban green space from high-resolution images. Experimental results demonstrate that MFFTNet outperforms existing popular deep learning models in urban green space segmentation.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Biodiversity Conservation
Bo Pang, Jingyuan Zhao, Jianxin Zhang, Li Yang
Summary: With the rapid urbanization in China, the concept of the Park City has emerged as a solution to the increasingly severe urban problems. This concept considers the comprehensive value of green space in order to promote sustainable development. Using Xi'an as a case study, this research comprehensively examines the socioeconomic and ecological benefits of urban green space and calculates the optimal scale. The findings suggest that the optimal scale of urban green space should be determined based on both socioeconomic and ecological factors, with ecological effects playing a more significant role.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Yingqi Wang, Huiping Huang, Guang Yang, Wei Chen
Summary: This study proposed a novel methodological framework to match each ecosystem service function with corresponding functional types of urban green space and consider both supply and demand sides to meet the needs of residents' production and life. The results showed that the supply-demand situation of different functional types of urban green spaces varied in different ecosystem service functions, and considering both supply and demand was more intuitive to see whether the city's demand for green spaces had been met.
Article
Environmental Studies
Yuyang Zhang, Qilin Wu, Lei Wu, Yan Li
Summary: Green spaces exposure is beneficial for the physical and mental health of community residents, but the spatial distribution of green space is often inequitable. This study proposed a methodology to assess community green equity using metrics in morphology, visibility, and accessibility categories, which revealed large differences and complementarities between different categories of metrics, while similarities exist within the same category. The findings can guide decision makers and urban green designers in creating and maintaining more equitable community green spaces, and can be combined with other studies for more comprehensive conclusions in the future.
Article
Engineering, Civil
Xiaoyue Zhang, Lei Chen, Chenxi Guo, Haifeng Jia, Zhenyao Shen
Summary: The composition and configuration of urban patches have a significant impact on hydrological processes. Low impact development practices (LIDs) are widely used worldwide to manage stormwater runoff quantity and quality issues. This study constructed a two-scale optimization framework to integrate spatial layout and landscape configuration of LIDs. The results showed that the area of sink landscape increased as the distance to outlets decreased. A site-scale optimization using a new landscape metric, CRSS, was conducted to achieve LIDs-based landscape configuration optimization. The study found that runoff flow and pollution were correlated with CRSS, and identified thresholds for optimal stormwater management.
JOURNAL OF HYDROLOGY
(2023)
Article
Remote Sensing
Kai Liu, Xueke Li, Shudong Wang, Xiaojie Gao
Summary: The study investigates the effects of landscape pattern on the urban thermal environment in Shijiazhuang, China using different datasets and models. The results show that there are noticeable differences in land surface temperature response to urban green landscape metrics between trees and lawns. The composition of urban green space has a substantial impact on land surface temperature throughout summer. The configurations of urban green space exhibit less impact on land surface temperature and these effects vary temporally in magnitude. The study also confirms that the impact of urban green space landscape metrics on land surface temperature is consistent at different spatial scales.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Studies
Bo-Xun Huang, Shang-Chia Chiou, Wen-Ying Li
Summary: During the process of urbanization in Fuzhou, the city center has shown apparent urbanization trends and serious issues with green space fragmentation. The green space planning in Fuzhou has been ineffective in improving existing green spaces, while the planned ecological network has helped increase the complexity of green patches and landscape connectivity, reducing landscape fragmentation and improving urban ecological environment quality.
Article
Engineering, Multidisciplinary
Shijia Li, Zhenyu Fan
Summary: This paper conducts an evaluation simulation of urban green space landscape planning scheme based on the PSO-BP neural network model. The PSO-BP neural network can integrate more evaluation indicators of ecology and urban development into the planning scheme, and understand and predict human behavior in a simpler way, leading to a more comprehensive evaluation and prediction of the urban green space landscape planning scheme. The experiments show that the PSO-BP neural network has smaller error and better generalization ability than the BP neural network. The PSO-BP neural network rating model can analyze the relationship between different types of green space and indicators, and provide corresponding adjustment suggestions, which are of guiding significance for modifying and adjusting the urban green space landscape planning scheme.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Environmental Sciences
Junichi Susaki, Naoyuki Maruo, Masahiro Tsujino, Tirawat Boonyatee
Editorial Material
Geochemistry & Geophysics
Akira Hirose, Motofumi Arii, Irena Hajnsek, Akira Iwasaki, Shouhei Kidera, Tsunekazu Kimura, Hiroaki Kuze, Shoichiro Kojima, Yu Okada, Ryo Natsuaki, Takuya Sakamoto, Motoyuki Sato, Ryoichi Sato, Fang Shang, Josaphat T. S. Sumantyo, Junichi Susaki, Kei Suwa, Takeo Tadono, Kazunori Takahashi, Kuniaki Uto, Manabu Watanabe, Hiroyoshi Yamada, Aya Yamamoto, Naoto Yokoya, Chinatsu Yonezawa
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2019)
Article
Remote Sensing
Tamer ElGharbawi, Junichi Susaki, Kamolratn Chureesampant, Chomchanok Arunplod, Juthasinee Thanyapraneedkul, Ponthip Limlahapun, Amany Suliman
Summary: This paper proposes two deep convolutional neural network (CNN) variants based on Seg-Net and Res-Net architectures for accurate estimation of forest canopy heights using Sentinel-2 data and a digital surface model. The results show that the Seg-Net model has an average MAE, RMSE, and R2 of 1.38 m, 1.85 m, and 0.87, respectively, and is approximately 4.8 times faster than the Res-Net model.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2023)
Proceedings Paper
Geosciences, Multidisciplinary
Tomoya Kusunose, Junichi Susaki, Yu Fujiwara, Hirofumi Hisada
Summary: In recent years, heavy rain has caused significant damage to various infrastructures in Japan. This study applies PSInSAR technology to monitor ground deformation and proposes a noise-robust system for early detection of landslide signs in the Takeo Junction area of western Japan.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Proceedings Paper
Engineering, Aerospace
Tomoya Kusunose, Junichi Susaki
Summary: Land subsidence, a serious social problem in Japan, has been controlled with groundwater pumping regulations, but new ground uplift problems are now a concern, particularly in urban areas. The study found a strong correlation between rising groundwater levels and ground uplift, suggesting potential for further research in this area.
2021 7TH ASIA-PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR (APSAR)
(2021)
Proceedings Paper
Environmental Sciences
H. Ito, J. Susaki, T. Anahara
ISPRS TECHNICAL COMMISSION III WG III/2, 10 JOINT WORKSHOP MULTIDISCIPLINARY REMOTE SENSING FOR ENVIRONMENTAL MONITORING
(2019)
Proceedings Paper
Environmental Sciences
J. Susaki, R. Miyagaki, A. Kuriki, S. Jin
ISPRS TECHNICAL COMMISSION III WG III/2, 10 JOINT WORKSHOP MULTIDISCIPLINARY REMOTE SENSING FOR ENVIRONMENTAL MONITORING
(2019)
Proceedings Paper
Geosciences, Multidisciplinary
Junichi Susaki, Hiroki Ito, Takuma Anahara
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
(2019)
Proceedings Paper
Geosciences, Multidisciplinary
Takaya Kusakabe, Junichi Susaki, Takuma Anahara
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
(2019)
Proceedings Paper
Geography, Physical
S. Yadav, Y. Yamashiki, J. Susaki, Y. Yamashita, K. Ishikawa
ISPRS TECHNICAL COMMISSION III WG III/2, 10 JOINT WORKSHOP MULTIDISCIPLINARY REMOTE SENSING FOR ENVIRONMENTAL MONITORING
(2019)
Proceedings Paper
Engineering, Electrical & Electronic
Sheng-ye Jin, Junichi Susaki, Ryota Miyagaki, Amane Kuriki
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
(2018)
Proceedings Paper
Engineering, Electrical & Electronic
Hiroki Ito, Junichi Susaki
IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
(2018)
Article
Engineering, Multidisciplinary
Shin Akatsuka, Junichi Susaki, Masataka Takagi
ENGINEERING JOURNAL-THAILAND
(2018)
Proceedings Paper
Geosciences, Multidisciplinary
Mehwish Ghulam Zuhra, Junichi Susaki, Masayuki Tamura
2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
(2017)
Proceedings Paper
Geosciences, Multidisciplinary
Junichi Susaki, Masahiro Tsujino, Takuma Anahara
2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
(2017)
