Yao Li

Southwest University

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i-10 index

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Huilin Gao

Texas A&M University System

Gang Zhao

Carnegie Institution for Science

Shuai Zhang

Anhui Medical University

Dewi Surinati

National Research and Innovation Agency

Dongliang Yuan

University of Chinese Academy of Sciences

Xiang Li

Goddard Space Flight Center

Xiaojun She

Southwest University

George H. Allen

Virginia Tech

Jing Wang

Affiliated Hospital of Hangzhou Normal University

Corry Corvianawatie

Indonesian Institute of Sciences

Cooperative Institutions

Chinese Academy of Sciences

University of Chinese Academy of Sciences

Institute of Oceanology

Southwest University

Texas A&M University

Qingdao National Laboratory for Marine Science and Technology

Indonesian Institute of Sciences

Zhejiang University

Wuhan University

Ministry of Natural Resources

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Reduced Runoff in the Upper Yangtze River Due To Comparable Contribution of Anthropogenic and Climate Changes

Earth s Future (2024)

F. J. Zeng Qiulan He Yao Li Weiyu Shi Ruowen Yang

Abstract The changing climate and intensifying human activities have made an impact on the hydrological processes in the upper Yangtze River (UYR), but quantifying their effects remains uncertain. This study used the Budyko framework to investigate the response of runoff ( Q ) to climate change and human activities during 1956–2017 and evaluate the impacts of human activities, including land use/cover change, water use, dam construction, and vegetation change, on watershed characteristic. Results show that climate change is the dominant driver of Q variations in the Wujiang River (WJR), Jialing River (JLR), and Jinsha River (JSR) watersheds, with contributions of 58.6%, 66.9%, and 67.6%, respectively. However, in Mingjiang River (MJR) and UYR watersheds, human activities contribute more to Q variations with 55.2% and 51.2%, respectively. Human activities play important roles in variation of watershed characteristics, and they can explain 22%, 26%, 36%, 25%, and 53% of the watershed character change in UYR, WJR, JLR, MJR, and JSR, respectively. This study conducts a comprehensive analysis of the causes of Q change in UYR, and provides a new perspective to explore the effects of specific human activities on watershed characteristics.

Yangtze river

Land Cover

10.1029/2023ef004028

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Citations (5)

An integrated learning framework for seamless high-resolution soil moisture estimation

IEEE Transactions on Geoscience and Remote Sensing (2024)

Yinghong Jing Yao Li Xinghua Li Liupeng Lin Xiaojun She

10.1109/tgrs.2024.3461717

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Citations (1)

A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry

Remote Sensing of Environment (2020)

Yao Li Huilin Gao Gang Zhao Kuo‐Hsin Tseng

Elevation (ballistics)

Bathymetric chart

10.1016/j.rse.2020.111831

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Citations (104)

Varied responses of Amazon forests to the 2005, 2010, and 2015/2016 droughts inferred from multi-source satellite data

Agricultural and Forest Meteorology (2024)

Xiaojun She Yao Li Wenzhe Jiao Yuanheng Sun Xiangnan Ni

10.1016/j.agrformet.2024.110051

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Citations (4)

The Evolution Characteristics and Influence Mechanism of Chinese Venture Capital Spatial Agglomeration

International Journal of Environmental Research and Public Health (2021)

Yao Li Alex Singleton Pingjun Sun Guanpeng Dong

As an emerging financial entity, venture capital has a significant impact on regional development. However, the research on venture capital mainly focuses on the fields of finance, management, and economics, and fewer researchers study venture capital from the perspective of geography and space. This research explored the evolution characteristics and influence mechanism of Chinese venture capital spatial agglomeration. The innovation of this paper lies in including the spatial effect and conducting a spatial econometric analysis of the spatial agglomeration of venture capital in China after the exploratory analysis of the factors affecting the spatial agglomeration of venture capital. Firstly, based on the data of study area, this paper found that the spatial distribution of venture capital in China had an obvious agglomeration characteristic by using multiple measurement methods. Secondly, by constructing the spatial econometric model based on three different spatial weight matrices, we found that the science and technology environment, financial environment, social environment, and entrepreneurial environment levels were the main factors to affect the agglomeration of venture capital. Thirdly, due to the degree of spatial agglomeration of venture capital being divided into three stages in terms of time dimension, after the regression analysis of different periods, we found that the factors which affected spatial agglomeration of venture capital changed significantly with the passage of time. In addition, from the regression results of eastern, central, and western region samples, we can see that the degree of spillover effect was the lowest in the central region, the highest in the western region, and the middle in the eastern region. At last, this paper provided useful policy enlightenment for enterprise innovation, industrial upgrading, and regional economic management.

Social venture capital

Capital (architecture)

Spillover effect

Econometric analysis

10.3390/ijerph18062974

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Citations (5)

Hydrodynamic field data near Galveston, Texas wetland edges to help assess storm impacts and erosion

Zenodo (CERN European Organization for Nuclear Research) (2023)

Jens Figlus Fangzhou Tong Kuang‐An Chang Scott A. Socolofsky James M. Kaihatu

Water free surface elevation measurements via submerged pressure transducers along transects near Galveston Bay wetland edges

10.5281/zenodo.10070373

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Citations (0)

Potential influence of the Deepwater Horizon oil spill on phytoplankton primary productivity in the northern Gulf of Mexico

Environmental Research Letters (2019)

Yao Li Chuanmin Hu Antonietta Quigg Huilin Gao

Abstract Nine years after the Deepwater Horizon (DwH) oil spill (20 April–15 July 2010), the recovery of primary productivity at the ocean surface remains to be investigated. Here, we used the normalized fluorescence line height (nFLH) from the Moderate Resolution Imaging Spectroradiometer as an indicator of chlorophyll a concentration (Chl a ). First, from the spatiotemporal variations of nFLH between 2001 and 2017, a reduction of nFLH after the DwH oil spill was observed (for a relatively long period, from 2011 to 2014). Second, a stepwise multiple regression model was used to examine which of the following environmental factors could explain the annual variations in nFLH: river discharge, total nitrogen load, total phosphorus load, photosynthetically available radiation, sea surface temperature and wind speed. Results show that river discharge, sea surface temperature and wind speed are the primary factors that regulated the annual nFLH variations in the DwH area during the pre-spill years. In contrast, this same model could not explain the reduction of nFLH for the four years after the DwH oil spill. After 2015, nFLH appears to have resumed to the pre-spill concentrations. Here we suggest that the nFLH reduction between 2011 and 2014 could have originated from the DwH oil spill, although the exact mechanism is yet to be determined.

Deepwater Horizon

Moderate-resolution imaging spectroradiometer

Discharge

Photosynthetically active radiation

10.1088/1748-9326/ab3735

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Citations (31)

Diminishing storage returns of reservoir construction

Nature Communications (2023)

Yao Li Gang Zhao George H. Allen Huilin Gao

Surface water reservoirs are increasingly being relied upon to meet rising demands in the context of growing population and changing climate. However, the amount of water available in reservoirs (and the corresponding trends) have not been well quantified at the global scale. Here we use satellite observations to estimate the storage variations of 7245 global reservoirs from 1999 to 2018. Total global reservoir storage has increased at a rate of 27.82 ± 0.08 km3/yr, which is mainly attributed to the construction of new dams. However, the normalized reservoir storage (NS)-the ratio of the actual storage to the storage capacity-has declined by 0.82 ± 0.01%. The decline of NS values is especially pronounced in the global south, while the global north mainly exhibits an NS increase. With predicted decreasing runoff and increasing water demand, these observed diminishing storage returns of reservoir construction will likely persist into the future.

Water storage

Global population

10.1038/s41467-023-38843-5

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Citations (42)

Multiscale Building Extraction With Refined Attention Pyramid Networks

IEEE Geoscience and Remote Sensing Letters (2021)

Qinglin Tian Yingjun Zhao Yao Li Jun Chen Xuejiao Chen

Automatic building extraction from high-resolution aerial and satellite images has many practical applications, such as urban planning and disaster management. However, the complex appearance and various scales of buildings in remote-sensing images bring a challenge for building extraction. In this study, we developed a novel multiscale building extraction method based on refined attention pyramid networks (RAPNets). We built an encoder–decoder structure, and combine atrous convolution, deformable convolution, attention mechanism, and pyramid pooling module to improve the performance of feature extraction in the encoding path. Moreover, the salient multiscale features were extracted by embedding the convolutional block attention module into the lateral connections. Finally, the refined feature pyramid structure was adopted in the decoding path to fuse the multiscale features to obtain the final extraction results. Experiments on two standard data sets (Inria aerial image labeling data set and xBD data set) show that our method achieves reliable results and outperforms the comparing methods.

Pyramid (geometry)

Convolution (computer science)

Pooling

Fuse (electrical)

10.1109/lgrs.2021.3075436

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Citations (33)

Constructing Reservoir Area–Volume–Elevation Curve from TanDEM-X DEM Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2021)

Yao Li Huilin Gao George H. Allen Zhe Zhang

Area-volume-elevation (AVE) curves are critical for reservoir operation rules. However, such curves are not publicly available for most global reservoirs. Here, we present a framework to derive reservoir AVE curves from TanDEM-X data, using Lake Mead (~600 km ² ) as an example. First, the maximum water extent from 1984 to 2018-provided by the global surface water (GSW) dataset-was used as a mask to obtain the TanDEM-X data. Then, the TanDEM-X water indication mask (WAM) was applied to the extracted TanDEM-X data to obtain the visible bathymetry, which represents the topography between the maximum extent (according to GSW) and the water extent from WAM. Last, the AVE curve was generated by integrating the volume values from the top to bottom layers. TanDEM-X also captures the elevation values of the transitional waters, which are defined as the difference between the highest and lowest water levels. The transitional waters were obtained by thresholding amplitude and coherence images, and their elevations were then added to the visible bathymetry to extend the AVE curves with an elevation range extending from 344-369 m to 341-369 m. Validation results against in situ lidar survey values suggest a high-accuracy of elevation-area (E-A) relationships with R ² values of >0.99 and NRMSE values from 2.11% to 2.45%, and elevation-volume (E-V) relationships with R ² values of 1 and NRMSE values from 1.11% to 1.29%. Results also show that TanDEM-X data can capture the interannual variations due to multiple acquisitions, and that the elevation measurements for the lake shore areas are reliable.

Elevation (ballistics)

Tandem

10.1109/jstars.2021.3051103

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Citations (20)