DOI: 10.5194/hess-21-1017-2017
Scopus记录号: 2-s2.0-85013082960
论文题名: Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion
作者: Yang Y ; , Anderson M ; C ; , Gao F ; , Hain C ; R ; , Semmens K ; A ; , Kustas W ; P ; , Noormets A ; , Wynne R ; H ; , Thomas V ; A ; , Sun G
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 2 起始页码: 1017
结束页码: 1037
语种: 英语
Scopus关键词: Atmospheric temperature
; Climate change
; Data fusion
; Evapotranspiration
; Forestry
; Geostationary satellites
; Image reconstruction
; Land use
; Mean square error
; Radiometers
; Remote sensing
; Satellite imagery
; Satellites
; Transpiration
; Water supply
; Heterogeneous landscapes
; Land surface temperature
; Moderate resolution imaging spectroradiometer
; Root mean square errors
; Satellite remote sensing
; Spatial and temporal resolutions
; Thermal infrared remote sensing
; Two-source energy balance model
; Sensor data fusion
; cloud cover
; eddy covariance
; evapotranspiration
; geostationary satellite
; land cover
; land surface
; land use change
; Landsat
; MODIS
; plantation
; remote sensing
; surface temperature
; water use
; water yield
; North Carolina
; United States
; Pinus taeda
英文摘要: As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal resolution of satellite data, combined with the effects of cloud contamination, constrain the amount of detail that a single satellite can provide. In this study, we describe an application of a multi-sensor ET data fusion system over a mixed forested/agricultural landscape in North Carolina, USA, during the growing season of 2013. The fusion system ingests ET estimates from the Two-Source Energy Balance Model (TSEB) applied to thermal infrared remote sensing retrievals of land surface temperature from multiple satellite platforms: hourly geostationary satellite data at 4 km resolution, daily 1 km imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) and biweekly Landsat thermal data sharpened to 30 m. These multiple ET data streams are combined using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to estimate daily ET at 30m resolution to investigate seasonal water use behavior at the level of individual forest stands and land cover patches. A new method, also exploiting the STARFM algorithm, is used to fill gaps in the Landsat ET retrievals due to cloud cover and/or the scan-line corrector (SLC) failure on Landsat 7. The retrieved daily ET time series agree well with observations at two AmeriFlux eddy covariance flux tower sites in a managed pine plantation within the modeling domain: US-NC2 located in a mid-rotation (20-year-old) loblolly pine stand and USNC3 located in a recently clear-cut and replanted field site. Root mean square errors (RMSEs) for NC2 and NC3 were 0.99 and 1.02mmday-1, respectively, with mean absolute errors of approximately 29% at the daily time step, 12% at the monthly time step and 0.7% over the full study period at the two flux tower sites. Analyses of water use patterns over the plantation indicate increasing seasonal ET with stand age for young to mid-rotation stands up to 20 years, but little dependence on age for older stands. An accounting of consumptive water use by major land cover classes representative of the modeling domain is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T ) components obtained with the TSEB. The study provides new insights about the effects of management and land use change on water yield over forested landscapes. © Author(s) 2017. CC Attribution 3.0 License. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79253
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: Hydrology and Remote Sensing Laboratory, USDA ARS, Beltsville, MD, United States; Marshall Space Flight Center, Earth Science Branch, Huntsville, AL, United States; Nurture Nature Center, Easton, PA, United States; Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, United States; Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States; Southern Research Station, Eastern Forest Environmental Threat Assessment Center, USDA Forest Service, Raleigh, NC, United States
Recommended Citation:
Yang Y,, Anderson M,C,et al. Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion[J]. Hydrology and Earth System Sciences,2017-01-01,21(2)