Hyperspectral remote sensing data of typical vegetation along Sichuan Tibet Railway (2019)

Hyperspectral remote sensing data of typical vegetation along Sichuan Tibet Railway (2019)

This data set is hyperspectral observation data of typical vegetation along Sichuan Tibet Railway in September 2019, using the airborne spectrometer of Dajiang M600 resonon imaging system. Including the hyperspectral data observed in the grassland area of Lhasa in 2019, with its own latitude and longitude. The hyperspectral survey was mainly sunny. Before flight, whiteboard calibration was carried out; when data were collected, there was a target (that is, the standard reflective cloth suitable for the grass), which was used for spectral calibration; there were ground mark points (that is, letters with foam plates), and the longitude and latitude coordinates of each mark were recorded for geometric precise calibration. The DN value recorded by Hyperspectral camera of UAV can be converted into reflectivity by using Spectron Pro software. Hyperspectral data is used to extract spectral characteristics of different vegetation types, vegetation classification, inversion of vegetation coverage and so on.

File naming and required software

Naming method: Date_ Vegetation types_ Location_ Data type, such as "2019"_ grassland_ Lasa_ Hyperspectral remote sensing data of UAV "represents the hyperspectral data of UAV observed in grassland area of Lhasa in 2019. Among them, "hyperspectral remote sensing data"_ "Lasa" is the original data of hyperspectral measurement carried by UAV, "GPS shooting is used to correct the GPS position points of hyperspectral images" file is the longitude and latitude information of fixed-point position captured by GPS in the hyperspectral shooting area (there are files corresponding to hyperspectral data in it), which is used for the correction of hyperspectral images; "data description" is the data description file.
How to use: convert it into reflectivity grid layer by Spectron Pro software, and then analyze it by envi software or other hyperspectral processing software.

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Cite as:

Zhou, G., Ji, Y., Lv, X., Song, X. (2021). Hyperspectral remote sensing data of typical vegetation along Sichuan Tibet Railway (2019). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Ecolo.tpdc.271238. CSTR: 18406.11.Ecolo.tpdc.271238. (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.

Support Program

Second Tibetan Plateau Scientific Expedition Program

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License: This work is licensed under an Attribution 4.0 International (CC BY 4.0)

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Geographic coverage
East: 91.00 West: 90.70
South: 29.00 North: 29.20
  • Temporal resolution: Daily
  • Spatial resolution: 1m - 10m
  • File size: 3,389 MB
  • Views: 4224
  • Downloads: 0
  • Access: Protection period
  • Temporal coverage: 2019-09-10 To 2019-09-10
  • Updated time: 2022-04-18

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: ZHOU Guangsheng   JI Yuhe   LV Xiaomin   SONG Xingyang  

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

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