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author:

Gao, Y. (Gao, Y..) [1] (Scholars:高永刚) | Fang, M. (Fang, M..) [2] | Xu, H. (Xu, H..) [3] (Scholars:徐涵秋) | Liu, Y. (Liu, Y..) [4]

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Abstract:

In recent years, China has launched a number of Gaofen (GF) series earth observation satellites. It is crucial to understand the relationship between the data of the GF series of satellite sensors for the selection of sensor images for scientific research. Taking the same-day transit image pairs of three regions as the study data, this paper compares the consistency of the Top of Atmosphere (TOA) reflectance of GF-1 WFV4 and GF-6 WFV sensors by using the TOA mean comparison method, and discusses the differences in water body and vegetation extraction. The results indicate that the satellite signal intensity in different land cover types and areas differs significantly. In the bare soil-dominated region, GF-1 WFV4 has a larger signal strength than GF-6 WFV, while in the vegetation-dominated region, it turns out to be just the opposite. The difference between the two sensors is mainly related to the difference in the spectral response function and the radiometric resolution of the two satellites. In addition, the determination coefficient (R2) of the corresponding bands of the two sensors is all greater than 0.90, indicating that the two sensors have strong linear correlation and good complementarity. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Keyword:

comparative analysis GF-1 WFV4 GF-6 WFV top of Atmosphere (TOA) reflectance

Community:

  • [ 1 ] [Gao Y.]College of Environment and Safety Engineering, Fuzhou University, Fujian, Fuzhou, China
  • [ 2 ] [Gao Y.]Fujian Provincial Key Laboratory of Remote Sensing Monitoring and Assessment of Soil Erosion and Disaster Prevention, Fujian, Fuzhou, China
  • [ 3 ] [Fang M.]College of Environment and Safety Engineering, Fuzhou University, Fujian, Fuzhou, China
  • [ 4 ] [Xu H.]College of Environment and Safety Engineering, Fuzhou University, Fujian, Fuzhou, China
  • [ 5 ] [Xu H.]Fujian Provincial Key Laboratory of Remote Sensing Monitoring and Assessment of Soil Erosion and Disaster Prevention, Fujian, Fuzhou, China
  • [ 6 ] [Liu Y.]College of Environment and Safety Engineering, Fuzhou University, Fujian, Fuzhou, China

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Source :

International Journal of Remote Sensing

ISSN: 0143-1161

Year: 2024

Issue: 16

Volume: 45

Page: 5443-5463

3 . 0 0 0

JCR@2023

CAS Journal Grade:4

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WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

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30 Days PV: 0

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