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A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system
We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of mu...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501970/ https://www.ncbi.nlm.nih.gov/pubmed/28654086 http://dx.doi.org/10.1038/sdata.2017.83 |
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author | Li, Xin Liu, Shaomin Xiao, Qin Ma, Mingguo Jin, Rui Che, Tao Wang, Weizhen Hu, Xiaoli Xu, Ziwei Wen, Jianguang Wang, Liangxu |
author_facet | Li, Xin Liu, Shaomin Xiao, Qin Ma, Mingguo Jin, Rui Che, Tao Wang, Weizhen Hu, Xiaoli Xu, Ziwei Wen, Jianguang Wang, Liangxu |
author_sort | Li, Xin |
collection | PubMed |
description | We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWATER observation system consists of a flux observation matrix of eddy covariance towers, large aperture scintillometers, and automatic meteorological stations; an eco-hydrological sensor network of soil moisture and leaf area index; hyper-resolution airborne remote sensing using LiDAR, imaging spectrometer, multi-angle thermal imager, and L-band microwave radiometer; and synchronical ground measurements of vegetation dynamics, and photosynthesis processes. All observational data were carefully quality controlled throughout sensor calibration, data collection, data processing, and datasets generation. The data are freely available at figshare and the Cold and Arid Regions Science Data Centre. The data should be useful for elucidating multiscale eco-hydrological processes and developing upscaling methods. |
format | Online Article Text |
id | pubmed-5501970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-55019702017-07-12 A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system Li, Xin Liu, Shaomin Xiao, Qin Ma, Mingguo Jin, Rui Che, Tao Wang, Weizhen Hu, Xiaoli Xu, Ziwei Wen, Jianguang Wang, Liangxu Sci Data Data Descriptor We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWATER observation system consists of a flux observation matrix of eddy covariance towers, large aperture scintillometers, and automatic meteorological stations; an eco-hydrological sensor network of soil moisture and leaf area index; hyper-resolution airborne remote sensing using LiDAR, imaging spectrometer, multi-angle thermal imager, and L-band microwave radiometer; and synchronical ground measurements of vegetation dynamics, and photosynthesis processes. All observational data were carefully quality controlled throughout sensor calibration, data collection, data processing, and datasets generation. The data are freely available at figshare and the Cold and Arid Regions Science Data Centre. The data should be useful for elucidating multiscale eco-hydrological processes and developing upscaling methods. Nature Publishing Group 2017-06-27 /pmc/articles/PMC5501970/ /pubmed/28654086 http://dx.doi.org/10.1038/sdata.2017.83 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Data Descriptor Li, Xin Liu, Shaomin Xiao, Qin Ma, Mingguo Jin, Rui Che, Tao Wang, Weizhen Hu, Xiaoli Xu, Ziwei Wen, Jianguang Wang, Liangxu A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
title | A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
title_full | A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
title_fullStr | A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
title_full_unstemmed | A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
title_short | A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
title_sort | multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501970/ https://www.ncbi.nlm.nih.gov/pubmed/28654086 http://dx.doi.org/10.1038/sdata.2017.83 |
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