calculating viewing angles pixel by pixel in optical remote sensing satellite imagery using the rational function model

calculating viewing angles pixel by pixel in optical remote sensing satellite imagery using the rational function model

;Kai Xu;Guo Zhang;Qingjun Zhang;Deren Li
Journal of pharmacological sciences 2018 Vol. 10 pp. 478-
102
xu2018remotecalculating

Abstract

In studies involving the extraction of surface physical parameters using optical remote sensing satellite imagery, sun-sensor geometry must be known, especially for sensor viewing angles. However, while pixel-by-pixel acquisitions of sensor viewing angles are of critical importance to many studies, currently available algorithms for calculating sensor-viewing angles focus only on the center-point pixel or are complicated and are not well known. Thus, this study aims to provide a simple and general method to estimate the sensor viewing angles pixel by pixel. The Rational Function Model (RFM) is already widely used in high-resolution satellite imagery, and, thus, a method is proposed for calculating the sensor viewing angles based on the space-vector information for the observed light implied in the RFM. This method can calculate independently the sensor-viewing angles in a pixel-by-pixel fashion, regardless of the specific form of the geometric model, even for geometrically corrected imageries. The experiments reveal that the calculated values differ by approximately 10−40 for the Gaofen-1 (GF-1) Wide-Field-View-1 (WFV-1) sensor, and by ~10−70 for the Ziyuan-3 (ZY3-02) panchromatic nadir (NAD) sensor when compared to the values that are calculated using the Rigorous Sensor Model (RSM), and the discrepancy is analyzed. Generally, the viewing angles for each pixel in imagery are calculated accurately with the proposed method.

Citation

ID: 244745
Ref Key: xu2018remotecalculating
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
244745
Unique Identifier:
10.3390/rs10030478
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet