Article
Engineering, Electrical & Electronic
Yueze Zheng, Junhuan Peng, Xue Chen, Cheng Huang, Pinxiang Chen, Sen Li, Yuhan Su
Summary: Due to overexploitation of water resources, ground subsidence has become a serious problem in Beijing, China's capital. This article investigates the relationship between ground subsidence, changes in groundwater depth, and water supply in a long-term perspective. The study uses multisource synthetic aperture radar (SAR) data and the interferometric SAR (InSAR) technique, combined with leveling and ground subsidence data from 2003 to 2020. The results show that ground subsidence in the plain area has steadily increased, but slowed down since 2016, thanks to the completion of the South-to-North Water Diversion Project (SNWDP) in 2008 and 2015, which reduced groundwater exploitation and increased water recycling.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Construction & Building Technology
Yunqiang Zheng, Shihong Du, Xiuyuan Zhang, Lubin Bai, Haoyu Wang
Summary: This study explored carbon emissions derived from energy consumption in Beijing using multi-source data and developed a novel framework to calculate the carbon emissions. The results showed spatial auto-correlation and high-value clusters in the central area of Beijing. Additionally, institutional, residential, and industrial zones had the highest levels of carbon emissions.
BUILDING AND ENVIRONMENT
(2022)
Article
Environmental Sciences
Seyedeh Fatemeh Nemati, Naser Hafezi Moghadas, Gholam Reza Lashkaripour, Hosein Sadeghi
Summary: Characterizing the subsurface structure is crucial for seismic hazard assessment, with lack of knowledge leading to potential disasters. Shear wave velocity sections can help identify hidden faults and structures for a more comprehensive understanding of the subsurface.
JOURNAL OF MOUNTAIN SCIENCE
(2021)
Article
Environmental Sciences
Lin Wang, Chaofan Zhou, Huili Gong, Beibei Chen, Xinyue Xu
Summary: This study utilized remote sensing data and mathematical models to predict land subsidence along the high-speed railways in the Beijing-Tianjin-Hebei region. It was found that some sections of the railways have already passed through or approached areas of land subsidence. The results of this study are of critical importance for ensuring the safety of high-speed railway operation.
Article
Plant Sciences
Shuaibing Liu, Xiuliang Jin, Chenwei Nie, Siyu Wang, Xun Yu, Minghan Cheng, Mingchao Shao, Zixu Wang, Nuremanguli Tuohuti, Yi Bai, Yadong Liu
Summary: Our research aims to determine the contribution of multimodal data to LAI and propose a framework for estimating LAI based on remote-sensing data; evaluate the robustness and adaptability of an LAI estimation model that uses multimodal data fusion and deep neural networks (DNNs) in single- and whole growth stages; and explore how soil background and maize tasseling affect LAI estimation. Using low-cost UAVs and DNNs, multimodal data fusion accurately and reliably estimates LAI for crops, which is valuable for high-throughput phenotyping and high-spatial precision farmland management.
Article
Environmental Sciences
Shunkang Zhang, Beibei Chen, Huili Gong, Kunchao Lei, Min Shi, Chaofan Zhou
Summary: The research in the Beijing Plain found that surface displacement is mainly vertical, with significant horizontal displacement in the eastern region related to vertical displacement centers. The main cause of displacement is long-term groundwater overexploitation, with geological structures and stratigraphic conditions also playing a role in influencing surface displacement.
Article
Environmental Sciences
Mohamed Mourad, Takeshi Tsuji, Tatsunori Ikeda, Kazuya Ishitsuka, Shigeki Senna, Kiyoshi Ide
Summary: This study presents a novel approach to mapping the storage coefficient (Sk) using InSAR-derived surface deformation and S-wave velocity (Vs), successfully applied in the Kumamoto area. The clear relationship between Sk and Vs suggests that the compressibility of an aquifer is related to its stiffness. The method is effective for estimating aquifer storage properties even with limited groundwater-level data and can also estimate groundwater-level variation from geodetic data.
Article
Environmental Sciences
Yingqiang Song, Lu Kang, Fan Lin, Na Sun, Aziguli Aizezi, Zhongkang Yang, Xinya Wu
Summary: In this study, the contribution of air quality to soil heavy metals in an oil mining area was investigated. Samples from surface soil and air quality monitoring data were collected. Hybrid geostatistical models were used to estimate and map heavy metals in soil. The results showed a sources-receptor relationship between air quality and soil heavy metals, with oil wells and factories being the main sources. This study provides important insights for preventing and early warning of heavy metal pollution in mine soil.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Forestry
Jiali Jin, Stephen R. J. Sheppard, Baoquan Jia, Cheng Wang
Summary: This study focuses on the Beijing Plain Afforestation Project, analyzing the spatial and landscape changes during the implementation. It found that the project increased forest and park land, but also faced challenges such as discrepancies between planned and actual sites and conversion of cropland to forest. The study demonstrates the importance of spatial analysis in optimizing large-scale urban afforestation projects.
Article
Agriculture, Multidisciplinary
Shoujia Ren, Bin Guo, Xi Wu, Liguo Zhang, Min Ji, Juan Wang
Summary: Accurate and timely monitoring of crop areas and yield modeling are crucial for food security and sustainability. This study presents a rapid and robust method for monitoring winter wheat planted area and yield modeling based on MODIS data. The research found an increasing trend in winter wheat planted area and the models can accurately estimate yield with sufficient NDVI data.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Engineering, Environmental
T. Nash Skipper, Yongtao Hu, M. Talat Odman, Barron H. Henderson, Christian Hogrefe, Rohit Mathur, Armistead G. Russell
Summary: This study focuses on the fusion of observed O-3 with simulated US-B O-3, and adjustments for model bias, revealing that CTM US-B O-3 estimates are typically low in spring and high in fall.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Geosciences, Multidisciplinary
Kimiyuki Asano, Tomotaka Iwata, Kunikazu Yoshida, Naoto Inoue, Kazuhiro Somei, Ken Miyakoshi, Michihiro Ohori
Summary: The Hakodate Plain in Japan's Hokkaido is a sedimentary basin surrounded by mountains. Microtremor array surveys were conducted to estimate the velocity structure and develop a three-dimensional model. The model was validated through gravity anomaly modeling and ground motion simulation, and the spatial variation of ground motion amplification was discussed.
EARTH PLANETS AND SPACE
(2022)
Article
Geography, Physical
Mingyuan Lyu, Xiaojuan Li, Yinghai Ke, Jiyi Jiang, Lin Zhu, Lin Guo, Huili Gong, Beibei Chen, Zhihe Xu, Ke Zhang, Zhanpeng Wang
Summary: Beijing has experienced severe settlement in recent years, and a new method was proposed to reconstruct spatially continuous time-series deformation. The PS-InSAR technique was used to retrieve deformation data, and polynomial curve fitting and data analysis techniques were used to estimate the measurement gaps in nonurban areas. The results showed that the nonlinear model provided a better fit for the time-series deformation.
GISCIENCE & REMOTE SENSING
(2023)
Article
Geography, Physical
Yong-Fei Zhang, Cecilia M. Bitz, Jeffrey L. Anderson, Nancy S. Collins, Timothy J. Hoar, Kevin D. Raeder, Edward Blanchard-Wrigglesworth
Summary: Uncertain or inaccurate parameters in sea ice models can impact seasonal predictions and climate change projections. Applying an ensemble Kalman filter to estimate parameters in the model can improve performance at local scales, especially during the forecast period when no observations are available for assimilation.
Article
Multidisciplinary Sciences
Emily Breza, Arun G. Chandrasekhar, Shane Lubold, Tyler H. McCormick, Mengjie Pan
Summary: Aggregated Relational Data (ARD) provide a low-cost option for collecting network data when complete data is not feasible. This paper characterizes conditions under which ARD can accurately recover features of the unobserved network and provides consistent estimates of network model parameters. Simulated networks based on ARD can allow for the consistent estimation of unobserved network statistics and response functions.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
