Jianghao Wang

Dr. Jianghao Wang

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 January 2019 in Nature Human Behaviour
Verified
Journal Article
Closed access
PDF file
SZSiqi Zheng
Siqi Zheng
JWJianghao Wang
Jianghao Wang
CSCong Sun
Cong Sun
XZXiaonan Zhang
Xiaonan Zhang
MKMatthew E. Kahn
Matthew E. Kahn

17 March 2022 in Nature Human Behaviour
Verified
Journal Article
Closed access
PDF file
JWJianghao Wang
Jianghao Wang
YFYichun Fan
Yichun Fan
JPJuan Palacios
Juan Palacios
YCYuchen Chai
Yuchen Chai
NGNicolas Guetta-Jeanrenaud
Nicolas Guetta-Jeanrenaud
SZSiqi Zheng
Siqi Zheng

1 March 2019 in Transportation Research Part D: Transport and Environment
Verified
Journal Article
Closed access
SZSiqi Zheng
Siqi Zheng
XZXiaonan Zhang
Xiaonan Zhang
WSWeizeng Sun
Weizeng Sun
JWJianghao Wang
Jianghao Wang

8 November 2024 in Science Advances
Verified
Journal Article
Open access
YGYongxuan Guo
Yongxuan Guo
JWJianghao Wang
Jianghao Wang
Yong GeYong Ge
Yong Ge
CZChenghu Zhou
Chenghu Zhou
Rapidly increasing human-nature interactions exacerbate the risk of exposure to wildfires for human society. The wildland-urban interface (WUI) represents the nexus of human-nature interactions, where the risk of exposure to natural hazards such as wildfire is most pronounced. However, quantifying long-term global WUI change and the corresponding driving factors at fine resolution remain challenging. Here, we mapped and analyzed the global WUI at 30-meter resolution in 2000, 2010, and 2020. Our analysis revealed that the global WUI expanded by 35.6% since 2000, reaching 1.93 million square kilometer in 2020. Notably, 85% of this growth occurred between 2010 and 2020. The increase in WUI was primarily driven by the unprecedented expansion of global urbanization, contributing an additional 589,914 square kilometer of WUI. In addition, the number of small fires occurring in WUI areas has increased substantially since 2010. These findings underscore the rising wildfire risk to human society and highlight the urgency of implementing tailored fire management strategies in WUI areas.

3 June 2022 in Nature Communications
Verified
Journal Article
Open access
PDF file
Yong GeYong Ge
Yong Ge
WZWenbin Zhang
Wenbin Zhang
XWXilin Wu
Xilin Wu
CRCorrine Ruktanonchai
Corrine Ruktanonchai
HLHaiyan Liu
Haiyan Liu
SLShengjie Lai
Shengjie Lai
Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants.

10 July 2018 in Journal of Geophysical Research: Atmospheres
Verified
Journal Article
Open access
PDF file
XLXiang Li
Xiang Li
SLShaomin Liu
Shaomin Liu
HLHuaixiang Li
Huaixiang Li
YMYanfei Ma
Yanfei Ma
JWJianghao Wang
Jianghao Wang
ZGZhixia Guo
Zhixia Guo
Land surface evapotranspiration (ET) is an important component of the surface energy budget and water cycle. To solve the problem of the spatial‐scale mismatch between in situ observations and remotely sensed ET, it is necessary to find the most appropriate upscaling approach for acquiring ground truth ET data at the satellite pixel scale. Based on a data set from two flux observation matrices in the middle stream and downstream of the Heihe River Basin, six upscaling methods were intercompared via direct validation and cross validation. The results showed that the area‐weighted method performed better than the other five upscaling methods introducing auxiliary variables (the integrated Priestley‐Taylor equation, weighted area‐to‐area regression kriging [WATARK], artificial neural network, random forest [RF], and deep belief network methods) over homogeneous underlying surfaces. Over moderately heterogeneous underlying surfaces, the WATARK method performed better. However, the RF method performed better over highly heterogeneous underlying surfaces. A combined method (using the area‐weighted and WATARK methods for homogeneous and moderately heterogeneous underlying surfaces, respectively, and using the RF method for highly heterogeneous underlying surfaces) was proposed to acquire the daily ground truth ET data at the satellite pixel scale, and the errors in the ground truth ET data were evaluated. The Dual Temperature Difference (DTD) and ETMonitor were validated using ground truth ET data, which solve the problem of the spatial‐scale mismatch and quantify uncertainties in the validation process.