Spectral Reflectance Estimation of UAS Multispectral Imagery Using Satellite Cross-Calibration Method

被引：2

作者：

Gowravaram, Saket ^{[1
]}

Chao, Haiyang ^{[1
]}

Molthan, Andrew ^{[2
]}

Zhao, Tiebiao ^{[3
]}

Tian, Pengzhi ^{[1
]}

Flanagan, Harold ^{[1
]}

Schultz, Lori ^{[4
]}

Bell, Jordan ^{[2
]}

机构：

[1] Univ Kansas, Lawrence, KS 66045 USA

[2] NASA Marshall Space Flight Ctr, Huntsville, AL 35808 USA

[3] Univ Calif, Merced, CA 95343 USA

[4] Univ Alabama, Huntsville, AL 35487 USA

来源：

PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING | 2021年 / 87卷 / 10期

关键词：

RADIOMETRIC CALIBRATION; GRASSLAND; PARAMETERS; MANAGEMENT; RETRIEVAL; AIRCRAFT;

D O I：

10.14358/PERS.20-00091R2

中图分类号：

P9 [自然地理学];

学科分类号：

0705 ; 070501 ;

摘要：

This paper introduces a satellite-based cross-calibration (SCC) method for spectral reflectance estimation of unmanned aircraft system (UAS) multispectral imagery. The SCC method provides a low-cost and feasible solution to convert high-resolution UAS images in digital numbers (DN) to reflectance when satellite data is available. The proposed method is evaluated using a multispectral data set, including orthorectified KHawk UAS DN imagery and Landsat 8 Operational Land Imager Level-2 surface reflectance (SR) data over a forest/grassland area. The estimated UAS reflectance images are compared with the National Ecological Observatory Network's imaging spectrometer (NIS) SR data for validation. The UAS reflectance showed high similarities with the NIS data for the near-infrared and red bands with Pearson's r values being 97 and 95.74, and root-mean-square errors being 0.0239 and 0.0096 over a 32-subplot hayfield.

引用

页码：735 / 746

页数：12

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