基于卫星交叉定标法的UAS多光谱影像光谱反射率估算

IF 1 4区地球科学 Q4 GEOGRAPHY, PHYSICAL

Photogrammetric Engineering and Remote Sensing Pub Date : 2021-10-01 DOI:10.14358/pers.20-00091r2

Saket Gowravaram, Haiyang Chao, A. Molthan, Tiebiao Zhao, Pengzhi Tian, H. Flanagan, L. Schultz, J. Bell

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引用次数: 3

摘要

介绍了一种基于卫星交叉定标的无人机多光谱图像光谱反射率估计方法。SCC方法提供了一种低成本和可行的解决方案，可以在卫星数据可用的情况下将高分辨率的数字(DN) UAS图像转换为反射率。该方法使用多光谱数据集进行评估，包括正校正KHawk UAS DN图像和Landsat 8 Operational Land Imager Level-2表面反射率(SR)数据，覆盖森林/草原地区。估计的UAS反射率图像与国家生态观测站网络的成像光谱仪(NIS) SR数据进行了对比验证。UAS反射率与NIS数据在近红外和红色波段具有较高的相似性，Pearson’s r值分别为97和95.74，均方根误差分别为0.0239和0.0096。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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来源期刊

Photogrammetric Engineering and Remote Sensing 地学-成像科学与照相技术

CiteScore

1.70

自引率

15.40%

发文量

审稿时长

9 months

期刊介绍： Photogrammetric Engineering & Remote Sensing commonly referred to as PE&RS, is the official journal of imaging and geospatial information science and technology. Included in the journal on a regular basis are highlight articles such as the popular columns “Grids & Datums” and “Mapping Matters” and peer reviewed technical papers. We publish thousands of documents, reports, codes, and informational articles in and about the industries relating to Geospatial Sciences, Remote Sensing, Photogrammetry and other imaging sciences.