ON-ORBIT MTF EVALUATION FOR THERMAL INFRARED BAND OF FY-2 SATELLITE AND ITS APPLICATION IN IMAGE QUALITY IMPROVEMENTS

Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms.<br><br> This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.

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Forest and land fire smoke detection using GCOM-C data (case study: Pulang Pisau, Central Kalimantan)

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/893/1/012068 ◽

2021 ◽

Vol 893 (1) ◽

pp. 012068

Author(s):

K I N Rahmi ◽

N Febrianti ◽

I Prasasti

Keyword(s):

Near Infrared ◽

Thermal Infrared ◽

Short Wave ◽

Forest Land ◽

Visual Interpretation ◽

Infrared Band ◽

Central Kalimantan ◽

Fire Smoke ◽

Shortwave Infrared

Abstract Forest/land fire give bad impact of heavy smoke on peatland area in Indonesia. Forest/land fire smoke need to be identified the distribution periodically. New satellite of GCOM-C has been launched to monitor climate condition and have visible, near infrared and thermal infrared. This study has objective to identify fire smoke from GCOM-C data. GCOM-C data has wavelength range from 0.38 to 12 μm it covers visible, near infrared, short-wave infrared and thermal infrared. It is relatively similar to MODIS or Himawari-8 images which could identify forest/land fire smoke. The methodology is visual interpretation to detect forest/land fire smoke using near infrared band (VN08), shortwave infrared band (SW03), and thermal bands (T01 and T02). Hotspot data is overlaid with GCOM-C image to represent the location of fire events. Combination of composite RGB image has been applied to detect forest/land fire smoke. GCOM-C image of VN8 bands and combination of thermal band in composite image could be used to detect fire smoke in Pulang Pisau, Central Kalimantan.

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Investigations on infrared-channel-image quality improvements for multispectral imaging

Journal of Physics Conference Series ◽

10.1088/1742-6596/1044/1/012039 ◽

2018 ◽

Vol 1044 ◽

pp. 012039

Author(s):

M. Rosenberger ◽

C. Zhang ◽

R. Celestre ◽

G. Notni

Keyword(s):

Image Quality ◽

Multispectral Imaging ◽

Quality Improvements ◽

Channel Image ◽

Infrared Channel

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Methane profiles from GOSAT thermal infrared spectra

Atmospheric Measurement Techniques ◽

10.5194/amt-11-3815-2018 ◽

2018 ◽

Vol 11 (6) ◽

pp. 3815-3828 ◽

Cited By ~ 2

Author(s):

Arno de Lange ◽

Jochen Landgraf

Keyword(s):

Lower Troposphere ◽

Principal Component ◽

Thermal Infrared ◽

Total Carbon ◽

Atmospheric Composition ◽

Data Sets ◽

Atmospheric Methane ◽

Infrared Band ◽

Correction Scheme ◽

Infrared Measurements

Abstract. This paper discusses the retrieval of atmospheric methane profiles from the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) between 1210 and 1310 cm−1, using the RemoTeC analysis software. Approximately one degree of information on the vertical methane distribution is inferred from the measurements, with the main sensitivity at about 9 km altitude but little sensitivity to methane in the lower troposphere. For verification, we compare the GOSAT-TIR methane profile retrieval results with profiles from model fields provided by the Monitoring Atmospheric Composition and Climate (MACC) project, scaled to the total column measurements of the Total Carbon Column Observing Network (TCCON) at ground-based measurement sites. Without any radiometric corrections of GOSAT observations, differences between both data sets can be as large as 10 %. To mitigate these differences, we developed a correction scheme using a principal component analysis of spectral fit residuals and airborne observations of methane during the HIAPER pole-to-pole observations (HIPPO) campaign II and III. When the correction scheme is applied, the bias in the methane profile can be reduced to less than 2 % over the whole altitude range with respect to MACC model methane fields. Furthermore, we show that, with this correction, the retrievals result in smooth methane fields over land and ocean crossings and no differences can be discerned between daytime and nighttime measurements. Finally, a cloud filter is developed for the nighttime and ocean measurements. This filter is rooted in the GOSAT-TIR (thermal infrared) measurements and its performance, in terms of biases, is consistent with the cloud filter based on the GOSAT-SWIR (shortwave infrared) measurements. The TIR filter shows a higher acceptance rate of observations than the SWIR filter, at the cost of a higher uncertainty in the retrieved methane profiles.

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