Reflectance processing of remote sensing spectroradiometer data
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- 作者：Peddle ; Derek R. ; Peter White ; H. ; et. al.
- 关键词：Remote sensing ; Reflectance ; Spectroradiometer ; BOREAS ; Calibration ; Radiance
- 刊名：Computers and Geosciences
- 出版年：2001
- 出版时间：March, 2001
- 年：2001
- 卷：27
- 期：2
- 页码：203-213
- 全文大小：420 K
文摘
Spectral reflectance is the ratio of incident-to-reflected radiant flux measured from an object or area over specified wavelengths. Unlike radiance and irradiance values, reflectance is an inherent property of an object and is independent of time, location, illumination intensity, atmospheric conditions and weather. Although reflectance is a key unit of measure in remote sensing, it is not measured directly and instead must be derived. Accordingly, the conversion of field and laboratory measurements of spectral radiance into reflectance values is a frequent requirement with ground data in support of airborne and satellite remote sensing applications in the environmental and earth sciences. In this paper, laboratory and computer methods for processing field spectroradiometer measurements of spectral radiance into calibrated absolute reflectance values are described. Target radiance measures are obtained under direct and diffuse illumination using a portable field spectroradiometer, with irradiance spectra captured by near simultaneous acquisition of reflected radiation from a reference panel. The approach for converting raw target and panel radiance spectra to calibrated reflectance involves five major processing stages: (i) panel calibration, (ii) solar zenith angle computations, (iii) spectral and angular interpolation, (iv) computation of reflectance, and (v) automated batch mode execution of stages (ii)–(iv) for processing large data volumes. Equipment, methods, and computer programs for achieving these stages are described. Example forestry ground spectra acquired in the Boreal Ecosystem Atmosphere Study (BOREAS) are presented to illustrate raw field measurements and final reflectance products. These methods would also be useful in other applications such as agriculture, water resources, oceanic studies, rangeland management, and geological exploration and mineral identification.