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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...

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Autores principales: Li, Xin, Liu, Shaomin, Xiao, Qin, Ma, Mingguo, Jin, Rui, Che, Tao, Wang, Weizhen, Hu, Xiaoli, Xu, Ziwei, Wen, Jianguang, Wang, Liangxu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
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.
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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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