| Autor: |
Jordan R. Bell, Tiebiao Zhao, Haiyang Chao, Pengzhi Tian, Lori Schultz, Andrew Molthan, Harold P. Flanagan, Saket Gowravaram |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Photogrammetric Engineering & Remote Sensing. 87:735-746 |
| ISSN: |
0099-1112 |
| DOI: |
10.14358/pers.20-00091r2 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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