Carbon dioxide retrieval of Argus 1000 space data by using GENSPECT line-by-line radiative transfer model

et al. 2022

The Radiance Enhancement (RE) method was introduced for efficient detection of clouds from the space. Recently, we have also reported that due to high reflectance of combustion-originated smokes, this approach can also be generalized for detection of the forest fires by retrieving and analyzing datasets collected from a space orbiting micro-spectrometer operating in the near infrared spectral range. In our previous publication, we have performed a comparison of observed and synthetic radiance spectra by developing a method for computation of surface reflectance consisting of different canopies by weighted sum based on their areal coverage. However, this approach should be justified by a method based on corresponding proportions of the upwelling radiance. The results of computations we performed in this study reveal a good match between areal coverage of canopies and the corresponding proportions of the upwelling radiance due to effect of the instrument slit function.

Section: Introductionmentioning

confidence: 99%

Effect of the Instrument Slit Function on Upwelling Radiance from a Wavelength Dependent Surface Reflectance

Jagpal¹,

Siddiqui²,

et al. 2022

“…The ultra-light (about 0.25 kg only), small-size and inexpensive Argus 1000 instrument was launched into space in 2008 from India as a payload of the CanX-2 nanosatellite [19] [20]. Being in space it provides the large-scale datasets as shown in Figure 1 that can be used to extract valuable information about atmospheric gas constituents like concentration of CO 2 and other greenhouse gases by retrieving of the IR spectral radiance [20] [21] [22]. Inset in Figure 1 demonstrates a photo of the Argus 1000 micro-spectrometer.…”

Section: Introductionmentioning

confidence: 99%

Efficient Application of the Radiance Enhancement Method for Detection of the Forest Fires Due to Combustion-Originated Reflectance

Siddiqui¹,

Jagpal²,

et al. 2021

JEP

The existing methods for detection of the cloud scenes are applied at relatively small spectral range within shortwave upwelling radiative wavelength flux. We have reported a new method for detection of the cloud scenes based on the Radiance Enhancement (RE). This method can be used to cover a significantly wider spectral range from 1100 nm to 1700 nm by using datasets from the space-orbiting micro-spectrometer Argus 1000. Due to high sunlight reflection of the smoke originated from the forest or field fires the proposed RE method can also be implemented for detection of combustion aerosols. This approach can be a promising technique for efficient detection and continuous monitor of the seasonal forest and field fires. To the best of our knowledge this is the first report showing how a cloud method can be generalized for efficient detection of the forest fires due to combustion-originated reflectance.

“…Being in space it provides the large-scale datasets as shown in Fig. 1 that can be used to extract valuable information about atmospheric gas constituents like concentration of CO 2 and other greenhouse gases by retrieving of the IR spectral radiance [21][22][23]. Inset in Fig.…”

Section: Introductionmentioning

confidence: 99%

Efficient application of the Radiance Enhancement method for detection of the forest fires due to combustion-originated reflectance

Siddiqui¹,

Jagpal²,

et al. 2021

Preprint

The existing methods detect the cloud scenes are applied at relatively small spectral range within shortwave upwelling radiative wavelength flux. We have reported a new method for detection of the cloud scenes based on the Radiance Enhancement (RE). This method can be used to cover a significantly wider spectral range from 1100 nm to 1700 nm (Siddiqui et al., 2015) by using datasets from the space-orbiting micro-spectrometer Argus 1000. Due to high sunlight reflection of the smoke originated from the forest or field fires the proposed RE method can also be implemented for detection of combustion aerosols. The approach can be a promising technique for efficient detection and continuous monitor of the seasonal forest and field fires. To the best of our knowledge this is the first report showing how a cloud method can be generalized for efficient detection of the forest fires due to combustion-originated reflectance.