A high-resolution dataset of the distribution of water bodies across the Tibetan Plateau

On By Vaseline

  • Lehner, B. & Döll, P. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 2961–22, https://doi.org/10.1016/j.jhydrol.2004.03.028 (2004).

    Article ADVERTISEMENTS Google Scholar

  • Mother, RH et al. China’s lakes at present: number, area and spatial distribution. Science China-Earth Sci. 54283–289, https://doi.org/10.1007/s11430-010-4052-6 (2011).

    Article ADS CAS Google Scholar

  • Zou, ZH et al. Divergent trends in open water body area in the contiguous United States from 1984 to 2016. Proceedings of the National Academy of Sciences of the United States of America 1153810–3815, https://doi.org/10.1073/pnas.1719275115 (2018).

    Article ADS CAS PubMed PubMed Central Google Scholar

  • Piao, SL et al. The impacts of climate change on water resources and agriculture in China. Nature 46743–51, https://doi.org/10.1038/nature09364 (2010).

    Article ADS CAS PubMed Google Scholar

  • Verpoorter, C., Kutser, T., Seekell, D.A. & Tranvik, L.J. A global inventory of lakes based on high-resolution satellite images. Geophysics. Res. Let. 416396–6402, https://doi.org/10.1002/2014gl060641 (2014).

    Article ADVERTISEMENTS Google Scholar

  • Hamilton, SK, Melack, JM, Goodchild, MF & Lewis, WM Estimation of the fractal dimension of terrain from lake size distributions. (1992).

  • Newman, MEJ Power Laws, Pareto Distributions, and Zipf’s Law. Contemporary physics 46323–351, https://doi.org/10.1080/00107510500052444 (2005).

    Article ADVERTISEMENTS Google Scholar

  • Downing, JA et al. The global abundance and size distribution of lakes, ponds and impoundments. Limnol. Oceanogr. 512388–2397, https://doi.org/10.4319/lo.2006.51.5.2388 (2006).

    Article ADVERTISEMENTS Google Scholar

  • Seekell, DA & Pace, ML Does the Pareto distribution adequately describe the size distribution of lakes? Limnol. Oceanogr. 56350–356, https://doi.org/10.4319/lo.2011.56.1.0350 (2011).

    Article ADVERTISEMENTS Google Scholar

  • Seekell, DA, Pace, ML, Tranvik, LJ & Verpoorter, C. A fractal-based approach to lake size distribution. Geophysics. Res. Let. 40517–521, https://doi.org/10.1002/grl.50139 (2013).

    Article ADVERTISEMENTS Google Scholar

  • McDonald, CP, Rover, JA, Stets, EG & Striegl, RG The regional abundance and size distribution of lakes and reservoirs in the United States and implications for global lake size estimates. Limnol. Oceanogr. 57597–606, https://doi.org/10.4319/lo.2012.57.2.0597 (2012).

    Article ADVERTISEMENTS Google Scholar

  • Mosquera, P. V., Hampel, H., Vázquez, R. F., Alonso, M. & Catalan, J. J. W. R. Abundance and morphometry change across the gradient of high mountain lakes in the tropical Andes of southern Ecuador. (2017).

  • Rodrigues, LN, Sano, EE, Steenhuis, TS & Passo, DP Estimating the storage capacity of small reservoirs with remote sensing in the Brazilian savanna region. Water resources management 26873–882, https://doi.org/10.1007/s11269-011-9941-8 (2012).

    Article Google Scholar

  • Crétaux, J.F., Biancamaria, S., Arsen, A., Bergé-Nguyen, M. & Becker, M. Global surveys of reservoirs and lakes from satellites and regional application to the Syrdarya River basin. Environment. Res. Let. 10https://doi.org/10.1088/1748-9326/10/1/015002 (2015).

  • Pachauri, RK et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. (Ipcc, 2014).

  • Fang, WZ et al. Recognition of global reservoirs from Landsat 8 images: a deep learning approach. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 123168–3177, https://doi.org/10.1109/jstars.2019.2929601 (2019).

    Article ADVERTISEMENTS Google Scholar

  • Work, Gilmer, DSJPE & Sensing, R. Use of satellite data to inventory prairie ponds and lakes. 42 (1976).

  • Wang, X. et al. A northern hemisphere lake ice phenology dataset based on passive microwave remote sensing. Big earth data1-19 (2022).

  • Du, Z. et al. Analysis of Landsat-8 OLI images for land surface water mapping. 5672-681 (2014).

  • Wang, N., Cheng, J., Zhang, H., Cao, H. & Liu, J.J.RSLR Application of U-net model to water extraction with high-resolution remote sensing data. 32 (2020).

  • Pekel, JF, Cottam, A., Gorelick, N. & Belward, AS High-resolution mapping of global surface water and its long-term changes. Nature 540418–422, https://doi.org/10.1038/nature20584 (2016).

    Article ADS CAS PubMed Google Scholar

  • Zhang, GQ et al. Regional differences in lake evolution across China between 1960 and 2015 and their natural and anthropogenic causes. Sens. remote Environment. 221386–404, https://doi.org/10.1016/j.rse.2018.11.038 (2019).

    Article ADVERTISEMENTS Google Scholar

  • Feng, S.L et al. Inland water bodies in China: features discovered in long-term satellite data. Proceedings of the National Academy of Sciences of the United States of America 11625491–25496, https://doi.org/10.1073/pnas.1910872116 (2019).

    Article ADS CAS PubMed PubMed Central Google Scholar

  • Yang, XK & Lu, XX Drastic changes in Chinese lakes and reservoirs in recent decades. Scientific representative 4https://doi.org/10.1038/srep06041 (2014).

  • Wang, XX et al. Improved maps of surface water bodies, major dams, reservoirs and lakes in China. Earth system. Science Data 143757–3771, https://doi.org/10.5194/essd-14-3757-2022 (2022).

    Article ADVERTISEMENTS Google Scholar

  • Tan, CQ et al. in 27th International Conference on Artificial Neural Networks (ICANN). 270-279 (2018).

  • Li, LW et al. Extraction of water bodies from remote sensing data with very high spatial resolution, based on fully convolutional networks. Remote sensing 11https://doi.org/10.3390/rs11101162 (2019).

  • Li, MY et al. A deep learning method for water body extraction from high-resolution multi-sensor remote sensing images. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 143120–3132, https://doi.org/10.1109/jstars.2021.3060769 (2021).

    Article ADVERTISEMENTS Google Scholar

  • Zhang, G., Yao, T., Xie, H., Wang, W. & Yang, W. An inventory of glacial lakes in the Third Polar Region and their changes in response to global warming. Global and planetary change 131148–157, https://doi.org/10.1016/j.gloplacha.2015.05.013 (2015).

    Article ADVERTISEMENTS Google Scholar

  • Chen, W.F et al. What controls lake contraction and subsequent expansion in the Endorheic Basin of the Tibetan Plateau over the past half century? Geophysics. Res. Let. 49https://doi.org/10.1029/2022gl101200 (2022).

  • Cao, H. et al. Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation. (2021).

  • Ronneberger, O., Fischer, P. & Brox, T. in 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 234-241 (2015).

  • Chen, L. C., Papandreou, G., Schroff, F. & Adam, H. Rethinking atrous convolution for semantic image segmentation. (2017).

  • Buslaev, A., Parinov, A., Khvedchenya, E., Iglovikov, VI & Kalinin, AA Albumentations: fast and flexible image enlargements. (2018).

  • Chen, Z., Guo, L., Chen, P., Wu, Y. & Zhang, B. 2020 Inland Water Bodies over the Tibetan Plateau (WBTP). Fig share. https://doi.org/10.6084/m9.figshare.24616491.v2 (2023).

  • Zhang, G.Q., Luo, W., Chen, W.F. & Zheng, G.X. A robust but variable lake extension on the Tibetan Plateau. Science Taurus. 641306–1309, https://doi.org/10.1016/j.scib.2019.07.018 (2019).

    Article Google Scholar

  • Mao, D.H et al. Impacts of climate change on Tibetan lakes: patterns and processes. Remote sensing 10https://doi.org/10.3390/rs10030358 (2018).

  • Wan, W. et al. Monitoring the changes in the lakes of the Qinghai-Tibetan Plateau in the past 30 years using satellite remote sensing data. Chinese Science Bulletin 591021–1035, https://doi.org/10.1007/s11434-014-0128-6 (2014).

    Article ADVERTISEMENTS Google Scholar

  • Zhang, J., Hu, QW, Li, YK, Li, HD & Li, JY Area, lake level and volume variations of typical lakes on the Tibetan Plateau and their response to climate change, 1972-2019. Geospatial information science 24458–473, https://doi.org/10.1080/10095020.2021.1940318 (2021).

    Article Google Scholar

  • Mosquera, P. V., Hampel, H., Vázquez, R. F., Alonso, M. & Catalan, J. Abundance and morphometry change across the high mountain lake gradient in the tropical Andes of southern Ecuador. Water resources research 537269–7280, https://doi.org/10.1002/2017wr020902 (2017).

    Article ADVERTISEMENTS Google Scholar

  • Steele, MK & Heffernan, JB Land use and topography bend and break fractal rules for water body size distribution. Limnology and oceanography letters 270–79, https://doi.org/10.1002/lol2.10038 (2017).

    Article Google Scholar

  • Zhou, J., Wang, L., Zhang, Y.S., Guo, Y.H. & He, D. Spatiotemporal variations of actual evaporation over Lake Selin Co and surrounding small lakes (Tibetan Plateau) during 2003-2012. Science China-Earth Sci. 592441–2453, https://doi.org/10.1007/s11430-016-0023-6 (2016).

    Article ADS CAS Google Scholar

  • Downing, JA Emerging global role of small lakes and ponds: little things mean a lot. Limnetics 299–23 (2010).

    Article Google Scholar