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Xinqi Zheng      
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Xinqi Zheng published an article in January 2019.
Top co-authors See all
Weiming Cheng

51 shared publications

State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Wei Luo

26 shared publications

Department of Geography, Northern Illinois University, DeKalb, IL 60115, USA

Gang Ai

5 shared publications

School of Information Engineering, China University of Geoscience Beijing, Beijing 100083, China

Lulu Zhang

4 shared publications

School of Information Engineering, China University of Geosciences, Beijing 100083, China

Qing Huang

4 shared publications

School of Information Engineering, China University of Geosciences, Beijing 100083, China

Publication Record
Distribution of Articles published per year 
(2009 - 2019)
Total number of journals
published in
Publications See all
Article 0 Reads 0 Citations Integrated Multiscale Method for Obtaining Accurate Forest Surface Area Statistics over Large Areas Shilun Kang, Xinqi Zheng, Yongqiang Lv Published: 28 January 2019
ISPRS International Journal of Geo-Information, doi: 10.3390/ijgi8020058
DOI See at publisher website ABS Show/hide abstract
Forest surface area is a fundamental input for forest-related research, such as carbon balance, biodiversity conservation, and ecosystem functioning and services. However, an accurate assessment of the area of forestland in China is not available because the forested area is usually calculated as a 2D projected area rather than a 3D surface area, and the impact of changes in the surface terrain on the area is ignored. In this study, we propose an integrated multiscale method that combines geomorphic regionalization and surface area algorithms to calculate the forest surface area in China. The results show that (1) China’s forested area is approximately 4.91% larger than the conventional estimates and corresponds to a carbon storage estimate that is approximately 383.72 million tons higher; (2) the integrated multiscale method exhibits good adaptability and high precision for large-scale surface area calculations; and (3) the calculation results of this method are superior to those of remote sensing data or single surface area algorithms, and the calculation efficiency is high.
Article 0 Reads 0 Citations Dynamic analysis method to open the “black box” of urban metabolism Qing Huang, Xinqi Zheng, Fei Liu, Yecui Hu, Yuqiang Zuo Published: 01 December 2018
Resources, Conservation and Recycling, doi: 10.1016/j.resconrec.2018.09.010
DOI See at publisher website
Article 0 Reads 2 Citations Generating a High-Precision True Digital Orthophoto Map Based on UAV Images Yu Liu, Xinqi Zheng, Gang Ai, Yi Zhang, Yuqiang Zuo Published: 21 August 2018
ISPRS International Journal of Geo-Information, doi: 10.3390/ijgi7090333
DOI See at publisher website ABS Show/hide abstract
Unmanned aerial vehicle (UAV) low-altitude remote sensing technology has recently been adopted in China. However, mapping accuracy and production processes of true digital orthophoto maps (TDOMs) generated by UAV images require further improvement. In this study, ground control points were distributed and images were collected using a multi-rotor UAV and professional camera, at a flight height of 160 m above the ground and a designed ground sample distance (GSD) of 0.016 m. A structure from motion (SfM), revised digital surface model (DSM) and multi-view image texture compensation workflow were outlined to generate a high-precision TDOM. We then used randomly distributed checkpoints on the TDOM to verify its precision. The horizontal accuracy of the generated TDOM was 0.0365 m, the vertical accuracy was 0.0323 m, and the GSD was 0.0166 m. Tilt and shadowed areas of the TDOM were eliminated so that buildings maintained vertical viewing angles. This workflow produced a TDOM accuracy within 0.05 m, and provided an effective method for identifying rural homesteads, as well as land planning and design.
Article 0 Reads 0 Citations Interoperable scenario simulation of land-use policy for Beijing–Tianjin–Hebei region, China Dongya Liu, Xinqi Zheng, HongBin Wang, Chunxiao Zhang, Jiaya... Published: 01 June 2018
Land Use Policy, doi: 10.1016/j.landusepol.2018.03.040
DOI See at publisher website
Article 0 Reads 1 Citation Quantitative Analysis of the Determinants Influencing Urban Expansion: A Case Study in Beijing, China Qiurong Xu, Xinqi Zheng, Chunxiao Zhang Published: 18 May 2018
Sustainability, doi: 10.3390/su10051630
DOI See at publisher website ABS Show/hide abstract
A quantitative analysis of spatial influencing factors on urban sprawl can offer better support for urban planning and management. There are many concerns regarding the influence of each factor. However, a quantitative analysis to detect the interactions between factors is limited because of the complexity of the urban systems, especially the role of planning. Additionally, spatial heterogeneity is often overlooked. This study aims to improve and strengthen the knowledge in this field through a spatial statistical method known as GeoDetector. A new spatial quantification of urban expansion was presented in this study and the spatio-temporal characteristics and mechanism of urban growth in Beijing from 2010 to 2015 were also analyzed. The results show that urban expansion presents spatial heterogeneity with different grid cells, and the optimal scale was 4500 m. At this scale, urban expansion in Beijing linearly expands along the traffic trunk. In addition, urban expansion in Beijing is jointly influenced by socioeconomic, geographical, and policy factors. Population density has had the greatest influence on urban expansion from 2010 to 2015, and policy factors rank first. The impact of economic factors on urban growth is gradually weakening. It is important for urban geographical research to further plans and guide urban development.
Article 0 Reads 0 Citations Implementation of a Parallel GPU-Based Space-Time Kriging Framework Yueheng Zhang, Xinqi Zheng, Zhenhua Wang, Gang Ai, Qing Huan... Published: 17 May 2018
ISPRS International Journal of Geo-Information, doi: 10.3390/ijgi7050193
DOI See at publisher website ABS Show/hide abstract
In the study of spatiotemporal geographical phenomena, the space–time interpolation method is widely applied, and the demands for computing speed and accuracy are increasing. For nonprofessional modelers, utilizing the space–time interpolation method quickly is a challenge. To solve this problem, the classical ordinary kriging algorithm was selected and expanded to a spatiotemporal kriging algorithm. Using the OpenCL framework to integrate central processing unit (CPU) and graphic processing unit (GPU) computing resources, a parallel spatiotemporal kriging algorithm was implemented, and three experiments were conducted in this work to verify the results. The results indicated the following: (1) when the size of the prediction point dataset is consistent, the performance of the method is robust with the increasing size of the observation point dataset; (2) the acceleration effect of the parallel method increases with an increased number of predicted points. Compared with the original sequential program, the implementation of the improved parallel framework showed a 3.23 speedup, which obviously shortens the interpolation time; (3) when cross-validating the temperature data in the Beijing Tianjin Hebei region, the space–time acceleration model provides a better fit than traditional pure space interpolation.