Traditional space- and airborne imaging spectrometers, such as the Moderate Resolution Imaging Spectroradiometer1 and Airborne Visible/Infrared Imaging Spectrometer,2 are used for precise remote sensing applications. However, many of these sensors are limited to being purely image-based or purely spectroscopy-based sensors. In contrast, imaging spectrometry3—a hyperspectral technique that combines the image and spectrum of an object—has aroused growing interest as a new method for remote sensing. Such sensors have successfully been used in specific target detection, precise classification, and quantitative retrieval. However, wider use of imaging spectrometry is limited because ground resolution of only a few meters to several kilometers is typically achieved. Here, we describe the design and evaluation of a new imaging spectrometer for remote sensing with improved ground resolution.
Spectra extracted from both space- and airborne imaging spectrometers are rarely pure because of a combination of low spatial resolution and complex ground features. Deemed ‘mixed spectra’, these complications bring a certain degree of bias to subsequent analyses. To address these issues, many countries—including the United States and Japan—have launched a series of mature field imaging spectrometers, which have been successfully used in agriculture, food monitoring, vegetation observation, and geological mapping. However, no such device has been reported in China. To address this need, we developed a novel field imaging spectrometer system (FISS), which is the first imaging sensor aimed specifically at field imaging spectrometry in China.4
Figure 1. Basic principle of our field imaging spectrometer system (FISS).
Figure 2. The key, optomechanical subsystem of our FISS.
Table 1.Main parameters and performance of FISS.
|Number of bands
||−20° to +20°
||>500:1 (60% bands)
|precision in laboratory
|Spectral sampling interval
We designed FISS based on the Chinese aviation push-broom imaging spectrometer (PHI).5, 6 Operation depends on spatial image lines, which are made along one direction from the lens entrance slit (see Figure 1). Perpendicular to this slit, the spectrum for each line pixel is measured by the dispersion component while other dimensions are imaged by the scanning mirror. Importantly, we included an integrated semiconductor refrigeration system with the CCD. The cooled CCD is designed to reduce thermal noise, which can reduce image quality, especially during low-light fluorescent imaging. Additionally, high and unstable temperatures can cause spectral shifts, affecting the quantitative analyses. The complete FISS is comprised of three main parts—the computer, optomechanical subsystems, and electronic subsystems—all of which are required to achieve high performance. However, the essential part of the FISS is the optomechanical subsystem (see Figure 2). It incorporates the key functional devices, such as the scanning mirror, objective lens, dispersing unit, and CCD camera. Thus, it performs the scanning, imaging, dispersion, photoelectric conversion, analog-to-digital conversion, and other important tasks.
We calibrated FISS spectrally, radiometrically, and spatially using a DK-242 monochromator, an integrating sphere, and indoor targets in a precise optics laboratory.7 FISS achieved high performance levels in terms of signal-to-noise ratio, response stability, response linearity, response uniformity, and spectral linearity (see Table 1). Importantly, the instantaneous field of view (FOV) of FISS is ∼1mrad and its spectral resolution is better than 5nm over the continuous spectral range of ∼437–902nm.
Figure 3. Diurnal variation of fluorescence intensity information produced by Folium mori. (a) Original image of the target, fluorescence intensity at (b) 9am, (c) 10am, (d) 11am, (e) noon, (f) 1pm, (g) 2pm, (h) 3pm, and (i) 4pm.
Extracted reflectance spectra from individual components—an adult leaf (orange), leaf vein (blue), leaflet (green), and leaf in shadow (black)—of the F. mori plant shown in Figure 3
Having assessed these important features, we field-tested FISS by extracting solar-induced fluorescence information from a sample of the mulberry plant Folium mori (see Figure 3). From our images (with spatial resolution of ∼1mm), we easily extracted spectral curves of individual pixels (see Figure 4). The high spatial resolution allowed us to ‘see’ one kind of object from each pixel and the resulting spectra may be considered pure. In contrast, the traditional field spectrometer, FieldSpec Pro FR (Analytical Spectral Devices, Inc.), is a one-point record-scanning sensor with a FOV that depends on its fore-optics. Using the common 1.5m fiber optic with a 25° FOV, the spectra obtained by this sensor at a height if 1m are limited to a circular field with a diameter of ∼44cm. The spectrum is often formed from all the targets within the circular field (i.e., a mixed spectrum). Thus, our FISS is superior to traditional field spectrometers and can be used for quantitative studies, precise information mapping, and spectral mixture analysis under variable spatial scales.
In summary, we have designed, built, and tested the first imaging spectrometer with a cooled CCD in China. We achieved high-spatial-resolution images, and spectra obtained from these images were considered pure. Although high performance was achieved by our FISS sensor, it will be further optimized to facilitate field measurements and to suit the requirements of precise applications. We will extend its spectral range to shortwave IR (2500nm) for wider applications, such as in mineral drill core detection. Additionally, we will improve the frames per second data collection speed of our FISS for future airborne use.
Jinnian Wang, Lifu Zhang, Jun Yan, Qingxi Tong
Department of Hyperspectral Remote Sensing
Institute of Remote Sensing Applications
Jinnian Wang is the deputy director of the Institute. He also serves as the secretary general of The Associate on Environment Remote Sensing of China. His major research interests include hyperspectral remote sensing and applications to mineral mapping and environment monitoring.
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