The algorithm firstly adopts the canopy BRDF model and represents the canopy reflectivity as a function of a series of parameters such as LAI/FAPAR, wavelength, reflectivity of soil and leaves, aggregation index, incidence and observation Angle.The parameter table is established for several key parameters as the input of inversion.Then input the pre-processed surface reflectance data and land cover data, and use look-up table (LUT) inversion to obtain FAPAR products.See references for detailed algorithms.
Image format: tif
Image size: about 1M per scene
Time range: 2000-2012
Temporal resolution: 8 days
Spatial resolution: 1km
File name: the data is stored in a grid tif format with the file name "Ayyyydddh25v04fpar_sg.tif", where yyyy represents the year and DDD represents the day, such as a2000049h25v04fpar_sg.tif, representing the FPAR product data on the 49th day of 2000.</p><p>Data reading: Arcgis, Envi and other remote sensing software can be used to open and read.
1. Liu, Y. , Fan, W. , Xu, X. , & Chen, G. . (2013). A new FAPAR retrieval model for continuous vegetation. doi:10.1109/IGARSS.2013.6723470(View Details)
Cite as:Fan, W. (2015). < b>Heihe 1km FAPAR production (2000-2012)</b>2015. doi: 10.3972/heihe.089.2014.db. (Download the reference: RIS | Bibtex )
Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.
1.Liao, Y. , Fan, W. , & Xu, X. . (2013). Algorithm of leaf area index product for HJ-CCD over Heihe River Basin. IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE. (View Details )
To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.
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1.The leaf water potential dataset in the downstream of the Heihe River Basin (2012)
2.HiWATER: the albedo in the middle reaches of the Heihe River Basin (Jun. 29, 2012)
3.Grassland interception dataset of Tianlaochi watershed in Qilian Mountain
4.HiWATER: Dataset of infrared temperature in Zhanye Airport desert
8.Data of SPAC system in the lower reaches of Heihe River (2012-2013)
10.The data of desert plants photosynthetic organ traits (2011)
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East:102.1548642 South:37.7401842 |
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Resource Provider: FAN Wenjie
Data has intellectual property rights because it is not only the result of physical labor, but also the achievements of intellectual activities. Data sharing needs to protect the intellectual property rights of Data, so that we can protect the rights and interests of data producers and make data sharing sustainable development. The core intellectual property rights of data include the right of signature, the right of publication and the right of recompilation, among which the right of signature is the most basic right. In academia, the traditional literature citation is the best way to reflect the right of signature. It has been widely recognized by scientists, so the intellectual property rights of data can be embodied through data reference.
1. Liu, Y. , Fan, W. , Xu, X. , & Chen, G. . (2013). A new FAPAR retrieval model for continuous vegetation. doi:10.1109/IGARSS.2013.6723470
Fan, W. (2015). < b>Heihe 1km FAPAR production (2000-2012)</b>2015. doi: 10.3972/heihe.089.2014.db.