scholarly journals Monitoring of the 2015 Villarrica Volcano Eruption by Means of DLR’s Experimental TET-1 Satellite

2018 ◽  
Vol 10 (9) ◽  
pp. 1379 ◽  
Author(s):  
Simon Plank ◽  
Michael Nolde ◽  
Rudolf Richter ◽  
Christian Fischer ◽  
Sandro Martinis ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Thermal Emission ◽  
Atmospheric Correction ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Villarrica Volcano ◽  
Radiant Power ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
German Aerospace ◽  
Active Volcanoes

Villarrica Volcano is one of the most active volcanoes in the South Andes Volcanic Zone. This article presents the results of a monitoring of the time before and after the 3 March 2015 eruption by analyzing nine satellite images acquired by the Technology Experiment Carrier-1 (TET-1), a small experimental German Aerospace Center (DLR) satellite. An atmospheric correction of the TET-1 data is presented, based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GDEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor data with the shortest temporal baseline to the TET-1 acquisitions. Next, the temperature, area coverage, and radiant power of the detected thermal hotspots were derived at subpixel level and compared with observations derived from MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data. Thermal anomalies were detected nine days before the eruption. After the decrease of the radiant power following the 3 March 2015 eruption, a stronger increase of the radiant power was observed on 25 April 2015. In addition, we show that the eruption-related ash coverage of the glacier at Villarrica Volcano could clearly be detected in TET-1 imagery. Landsat-8 imagery was analyzed for comparison. The information extracted from the TET-1 thermal data is thought be used in future to support and complement ground-based observations of active volcanoes.

scholarly journals Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean

2021 ◽  
Vol 13 (2) ◽  
pp. 184
Author(s):  
Rongjie Liu ◽  
Jie Zhang ◽  
Tingwei Cui ◽  
Haocheng Yu
Keyword(s):  
Remote Sensing ◽  
Indian Ocean ◽  
Infrared Imaging ◽  
Atmospheric Correction ◽  
Spatiotemporal Pattern ◽  
Anthropogenic Aerosols ◽  
Remote Sensing Reflectance ◽  
The Indian Ocean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis

Spectral remote sensing reflectance (Rrs(λ), sr−1) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where Rrs(λ) accuracy has not been well documented, the quality of Rrs(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual Rrs(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of Rrs(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly Rrs(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the Rrs(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.

scholarly journals The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment

2021 ◽  
Vol 13 (8) ◽  
pp. 1459
Author(s):  
Michael Nolde ◽  
Simon Plank ◽  
Rudolf Richter ◽  
Doris Klein ◽  
Torsten Riedlinger
Keyword(s):  
Infrared Imaging ◽  
Global Scale ◽  
Fire Intensity ◽  
Small Satellite ◽  
Satellite Mission ◽  
Active Fire ◽  
Radiative Power ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Patterns And Processes ◽  
German Aerospace

Wildfires significantly influence ecosystem patterns and processes on a global scale. In many cases, they pose a threat to human lives and property. Through greenhouse gas emissions, wildfires also directly contribute to climate change. The monitoring of such events and the analysis of acquired data is crucial for understanding wildfire and ecosystem interactions. The FireBIRD small satellite mission, operated by the German Aerospace Center (DLR), was specifically designed for the detection of wildfires. It features a higher spatial resolution than available with other Earth-observation systems. In addition to the detection of active fire locations, the system also allows the derivation of fire intensity by means of the Fire Radiative Power (FRP). This indicator can be used as a basis to derive the amount of emitted pollutant, which makes it valuable for climate studies. With the FireBIRD mission facing its end of life in 2021, this study retrospectively evaluates the performance of the system through an inter-comparison with data from two satellite missions of the National Aeronautics and Space Administration (NASA) and discusses the potential of such a system. The comparison is performed regarding both geometrical and radiometric aspects, the latter focusing on the FRP. This study uses and compares two different methods to derive the FRP from FireBIRD data. The data are analyzed regarding six major fire incidents in different regions of the world. The FireBIRD results are in accordance with the reference data, showing a geometrical overlapping rate of 83% and 84% regarding MODIS (Moderate-resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) overpasses in close temporal proximity. Furthermore, the results show a positive bias in FRP of about 11% compared to MODIS.

scholarly journals Urban climate and registration of thermal anomalies of territories using satellite imagery

2021 ◽  
Vol 266 ◽  
pp. 08008
Author(s):  
A.D. Biryukov ◽  
V.D. Olenkov ◽  
A.О. Kolmogorova
Keyword(s):  
Satellite Images ◽  
Urban Climate ◽  
Atmospheric Correction ◽  
Optimization Methods ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Before And After ◽  
Landsat 7 ◽  
Automated Processing ◽  
Urban Heat

This paper describes a simplified method of mapping of the ur-ban environment surface to obtain a map of the thermal anomalies distribu-tion and study the structure of the urban heat island. Those maps allow evaluating or planning the urban microclimate optimization methods and studying the effect of land cover type on the site temperature. The article discusses the processing of five satellite images for the summer and winter from 2002 to 2019. We propose a simpler and more automated processing of thermal images for Landsat 7 and Landsat 8. The stages of automatic atmospheric correction according to the DOS1 method and calculation of the emissivity with surface classification are considered. Image processing was carried out in the QGIS software package using the Semiautomatic Classification Plugin extension. As a result, thermal anomalies in Chelya-binsk were localized and a comparison of the thermal map for the specific region before and after urbanization was made.

scholarly journals Implementation of the NHI (Normalized Hot Spot Indices) Algorithm on Infrared ASTER Data: Results and Future Perspectives

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1538
Author(s):  
Giuseppe Mazzeo ◽  
Micheal S. Ramsey ◽  
Francesco Marchese ◽  
Nicola Genzano ◽  
Nicola Pergola
Keyword(s):  
Near Infrared ◽  
Thermal Emission ◽  
Hot Spot ◽  
Thermal Anomaly ◽  
Google Earth ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Aster Data ◽  
Shortwave Infrared

The Normalized Hotspot Indices (NHI) tool is a Google Earth Engine (GEE)-App developed to investigate and map worldwide volcanic thermal anomalies in daylight conditions, using shortwave infrared (SWIR) and near infrared (NIR) data from the Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively, onboard the Sentinel 2 and Landsat 8 satellites. The NHI tool offers the possibility of ingesting data from other sensors. In this direction, we tested the NHI algorithm for the first time on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. In this study, we show the results of this preliminary implementation, achieved investigating the Kilauea (Hawaii, USA), Klyuchevskoy (Kamchatka; Russia), Shishaldin (Alaska; USA), and Telica (Nicaragua) thermal activities of March 2000–2008. We assessed the NHI detections through comparison with the ASTER Volcano Archive (AVA), the manual inspection of satellite imagery, and the information from volcanological reports. Results show that NHI integrated the AVA observations, with a percentage of unique thermal anomaly detections ranging between 8.8% (at Kilauea) and 100% (at Shishaldin). These results demonstrate the successful NHI exportability to ASTER data acquired before the failure of SWIR subsystem. The full ingestion of the ASTER data collection, available in GEE, within the NHI tool allows us to develop a suite of multi-platform satellite observations, including thermal anomaly products from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+), which could support the investigation of active volcanoes from space, complementing information from other systems.

scholarly journals Intercomparison of MODIS and VIIRS Fire Products in Khanty-Mansiysk Russia: Implication for Characterizing Gas Flaring from Space

2017 ◽  
Author(s):  
Ambrish Sharma ◽  
Jun Wang
Keyword(s):  
Infrared Imaging ◽  
Thermal Anomaly ◽  
Google Earth ◽  
Anthropogenic Source ◽  
Thermal Anomalies ◽  
Gas Flaring ◽  
Cold Environments ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Shortwave Infrared ◽  
Level 2

Gas flaring is commonly used by industrial plants for processing oil and natural gases in the atmosphere, and hence is an important anthropogenic source for various pollutants including CO2, CO, and aerosols. This study evaluates the feasibility of using satellite data to characterize gas flaring form space by focusing on the Khanty Mansiysk Autonomous Okrug in Russia, a region that is well known for its dominatingly gas flaring activities. Multiple satellite-based thermal anomaly data products at night are inter-compared and analyzed, including MODIS (Moderate Resolution Imaging Spectroradiometer) Terra level-2 Thermal Anomalies product (MOD14), MODIS Aqua level-2 Thermal Anomalies product (MYD14), VIIRS (Visible Infrared Imaging Radiometer Suite) Active Fires Applications Related Product (VAFP), and VIIRS level-2 data based Nightfire product (VNF). The analysis compares and contrasts the efficacy of these sensor products in detecting small, hot sources like flares on the ground in extremely cold environments such as Russia. We found that the VNF algorithm recently launched by NOAA has the unprecedented accuracy and efficiency in characterizing gas flares in the region owing primarily to the use of Shortwave Infrared (SWIR) bands. Reconciliation of VNF’s differences and similarities with other nighttime fire products is also conducted, indicating that MOD14/MYD14 and VAFP data are only effective in detecting those gas flaring pixels that are among the hottest in the region. Validation of VNF product of gas flaring location with Google Earth images are made. It is shown that that VNF’s estimates of gas flaring area (the area of gas flaming) agree well the counterparts from Google images with a linear correlation of 0.91, highlighting its potential use for routinely monitoring emissions of gas flaring from space.

scholarly journals Potential Underestimation of Satellite Fire Radiative Power Retrievals over Gas Flares and Wildland Fires

2020 ◽  
Vol 12 (2) ◽  
pp. 238 ◽  
Author(s):  
Sanath Sathyachandran Kumar ◽  
John Hult ◽  
Joshua Picotte ◽  
Birgit Peterson
Keyword(s):  
Oil And Gas ◽  
Infrared Imaging ◽  
Landsat 8 ◽  
Wildland Fires ◽  
Atmospheric Conditions ◽  
Gas Flaring ◽  
Gas Flares ◽  
Radiative Power ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Fire Radiative Power

Fire Radiative Power (FRP) is related to fire combustion rates and is used to quantify the atmospheric emissions of greenhouse gases and aerosols. FRP over gas flares and wildfires can be retrieved remotely using satellites that observe in shortwave infrared (SWIR) to middle infrared (MIR) wavelengths. Heritage techniques to retrieve FRP developed for wildland fires using the MIR 4 μm radiances have been adapted for the hotter burning gas flares using the SWIR 2 μm observations. Effects of atmosphere, including smoke and aerosols, are assumed to be minimal in these algorithms because of the use of longer than visual wavelengths. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and Landsat 8 observations acquired before and during emergency oil and gas flaring in eastern Saudi Arabia to show that dark, sooty smoke affects both 4 μm and 2 μm observations. While the 2 μm observations used to retrieve gas FRP may be reliable during clear atmospheric conditions, performance is severely impacted by dark smoke. Global remote sensing-based inventories of wildfire and gas flaring need to consider the possibility that soot and dark smoke can potentially lead to an underestimation of FRP over fires.

scholarly journals PACO: Python-Based Atmospheric Correction

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1428
Author(s):  
Raquel de los Reyes ◽  
Maximilian Langheinrich ◽  
Peter Schwind ◽  
Rudolf Richter ◽  
Bringfried Pflug ◽  
...  
Keyword(s):  
Atmospheric Correction ◽  
Landsat 8 ◽  
Imaging Spectrometer ◽  
Environmental Mapping ◽  
Sensing Applications ◽  
Satellite Sensors ◽  
New Space ◽  
German Aerospace ◽  
Sentinel 2

The atmospheric correction of satellite images based on radiative transfer calculations is a prerequisite for many remote sensing applications. The software package ATCOR, developed at the German Aerospace Center (DLR), is a versatile atmospheric correction software, capable of processing data acquired by many different optical satellite sensors. Based on this well established algorithm, a new Python-based atmospheric correction software has been developed to generate L2A products of Sentinel-2, Landsat-8, and of new space-based hyperspectral sensors such as DESIS (DLR Earth Sensing Imaging Spectrometer) and EnMAP (Environmental Mapping and Analysis Program). This paper outlines the underlying algorithms of PACO, and presents the validation results by comparing L2A products generated from Sentinel-2 L1C images with in situ (AERONET and RadCalNet) data within VNIR-SWIR spectral wavelengths range.

Operational Validation of Space-based Albedo Products from Upscaled Tower-based Albedometer Measurements

2020 ◽  
Author(s):  
Rui Song ◽  
Jan-Peter Muller
Keyword(s):  
High Resolution ◽  
Surface Albedo ◽  
Atmospheric Correction ◽  
Ground Level ◽  
Correction Method ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces ◽  
Sentinel 2

<p>Surface albedo is a fundamental radiative parameter which controls the Earth’s energy budget by determining the amount of solar radiation which is either absorbed by the surface or reflected back to atmosphere. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their repeated global coverage. In this work, a new method of upscaling surface albedo from ground level footprints of a few tens of metres to coarse satellite scales (≈1km) is reported [1]. Tower-mounted albedometer measurements are upscaled and used to validate global space-based albedo products, including Copernicus Global Land Service (CGLS) 1km albedo data (from Proba-V and previously form VEGETATION-2), MODerate resolution Imaging Spectroradiometer (MODIS) 500m albedo data, and Multi-angle Imaging SpectroRadiometer (MISR) 1.1km albedo data. MODIS albedo retrievals show the closest agreement with tower measurements, followed by the MISR retrievals, and then followed by the CGLS retrievals. The upscaling method uses high-resolution surface reflectance retrievals (from Landsat-8, Sentinel-2) to fill the spatial gaps between the albedometer’s field-of-view (FoV) and coarse satellite scales. High-resolution surface albedo products are generated by combining high-resolution surface reflectance data and MODIS bi-directional reflectance distribution function (BRDF) climatology data. This upscaling framework also uses a novel Sensor Invariant Atmospheric Correction (SIAC) method [2] to improve the accuracy of upscaled tower albedo values. Total uncertainties of upscaled albedo products are estimated by considering uncertainties from both the tower albedometer raw measurements and SIAC atmospheric corrections. This surface albedo upscaling method can be used over both heterogenous and homogenous land surfaces, and has been examined at the SURFRAD, BSRN and FLUXNET tower sites.</p><p><strong>Keywords</strong>: surface albedo, upscale, CGLS, MODIS, MISR, SIAC</p><p>[1] Song, R.; Muller, J.-P.; Kharbouche, S.; Woodgate, W. Intercomparison of Surface Albedo Retrievals from MISR, MODIS, CGLS Using Tower and Upscaled Tower Measurements. Remote Sens. 2019, 11, 644, doi:10.3390/rs11060644.</p><p>[2] Yin, F., Lewis, P. E., Gomez-Dans, J., & Wu, Q. A sensor-invariant atmospheric correction method: application to Sentinel-2/MSI and Landsat 8/OLI. EarthArXiv 2019, https://doi.org/10.31223/osf.io/ps957.</p>

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals Consistent Long-Term Monthly Coastal Wetland Vegetation Monitoring Using a Virtual Satellite Constellation

2021 ◽  
Vol 13 (3) ◽  
pp. 438
Author(s):  
Subrina Tahsin ◽  
Stephen C. Medeiros ◽  
Arvind Singh
Keyword(s):  
Vegetation Index ◽  
Coastal Wetland ◽  
Thermal Emission ◽  
Mean Squared Error ◽  
Wetland Vegetation ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Vegetation Monitoring ◽  
Time Space

Long-term monthly coastal wetland vegetation monitoring is the key to quantifying the effects of natural and anthropogenic events, such as severe storms, as well as assessing restoration efforts. Remote sensing data products such as Normalized Difference Vegetation Index (NDVI), alongside emerging data analysis techniques, have enabled broader investigations into their dynamics at monthly to decadal time scales. However, NDVI data suffer from cloud contamination making periods within the time series sparse and often unusable during meteorologically active seasons. This paper proposes a virtual constellation for NDVI consisting of the red and near-infrared bands of Landsat 8 Operational Land Imager, Sentinel-2A Multi-Spectral Instrument, and Advanced Spaceborne Thermal Emission and Reflection Radiometer. The virtual constellation uses time-space-spectrum relationships from 2014 to 2018 and a random forest to produce synthetic NDVI imagery rectified to Landsat 8 format. Over the sample coverage area near Apalachicola, Florida, USA, the synthetic NDVI showed good visual coherence with observed Landsat 8 NDVI. Comparisons between the synthetic and observed NDVI showed Root Mean Squared Error and Coefficient of Determination (R2) values of 0.0020 sr−1 and 0.88, respectively. The results suggest that the virtual constellation was able to mitigate NDVI data loss due to clouds and may have the potential to do the same for other data. The ability to participate in a virtual constellation for a useful end product such as NDVI adds value to existing satellite missions and provides economic justification for future projects.

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