Next Article in Journal
Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery
Next Article in Special Issue
Atmospheric Correction of OLCI Imagery over Extremely Turbid Waters Based on the Red, NIR and 1016 nm Bands and a New Baseline Residual Technique
Previous Article in Journal
Integrating Airborne Hyperspectral, Topographic, and Soil Data for Estimating Pasture Quality Using Recursive Feature Elimination with Random Forest Regression
Open AccessArticle

Persistent Hot Spot Detection and Characterisation Using SLSTR

Max Planck Institute for Chemistry, 55128 Mainz, Germany
Zebris GbR, 81373 Munich, Germany
DLR, 12489 Berlin, Germany
DLR, 17235 Neustrelitz, Germany
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(7), 1118;
Received: 30 April 2018 / Revised: 29 June 2018 / Accepted: 5 July 2018 / Published: 13 July 2018
Gas flaring is a disposal process widely used in the oil extraction and processing industry. It consists in the burning of unwanted gas at the tip of a stack and due to its thermal characteristic and the thermal emission it is possible to observe and to quantify it from space. Spaceborne observations allows us to collect information across regions and hence to provide a base for estimation of emissions on global scale. We have successfully adapted the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire algorithm for the detection and characterisation of persistent hot spots, including gas flares, to the Sea and Land Surface Temperature Radiometer (SLSTR) observations on-board the Sentinel-3 satellites. A hot event at temperatures typical of a gas flare will produce a local maximum in the night-time readings of the shortwave and mid-infrared (SWIR and MIR) channels of SLSTR. The SWIR band centered at 1.61 μm is closest to the expected spectral radiance maximum and serves as the primary detection band. The hot source is characterised in terms of temperature and area by fitting the sum of two Planck curves, one for the hot source and another for the background, to the radiances from all the available SWIR, MIR and thermal infra-red channels of SLSTR. The flaring radiative power is calculated from the gas flare temperature and area. Our algorithm differs from the original VIIRS Nightfire algorithm in three key aspects: (1) It uses a granule-based contextual thresholding to detect hot pixels, being independent of the number of hot sources present and their intensity. (2) It analyses entire clusters of hot source detections instead of individual pixels. This is arguably a more comprehensive use of the available information. (3) The co-registration errors between hot source clusters in the different spectral bands are calculated and corrected. This also contributes to the SLSTR instrument validation. Cross-comparisons of the new gas flare characterisation with temporally close observations by the higher resolution German FireBIRD TET-1 small satellite and with the Nightfire product based on VIIRS on-board the Suomi-NPP satellite show general agreement for an individual flaring site in Siberia and for several flaring regions around the world. Small systematic differences to VIIRS Nightfire are nevertheless apparent. Based on the hot spot characterisation, gas flares can be identified and flared gas volumes and pollutant emissions can be calculated with previously published methods. View Full-Text
Keywords: gas flaring; SLSTR gas flaring; SLSTR
Show Figures

Graphical abstract

MDPI and ACS Style

Caseiro, A.; Rücker, G.; Tiemann, J.; Leimbach, D.; Lorenz, E.; Frauenberger, O.; Kaiser, J.W. Persistent Hot Spot Detection and Characterisation Using SLSTR. Remote Sens. 2018, 10, 1118.

AMA Style

Caseiro A, Rücker G, Tiemann J, Leimbach D, Lorenz E, Frauenberger O, Kaiser JW. Persistent Hot Spot Detection and Characterisation Using SLSTR. Remote Sensing. 2018; 10(7):1118.

Chicago/Turabian Style

Caseiro, Alexandre; Rücker, Gernot; Tiemann, Joachim; Leimbach, David; Lorenz, Eckehard; Frauenberger, Olaf; Kaiser, Johannes W. 2018. "Persistent Hot Spot Detection and Characterisation Using SLSTR" Remote Sens. 10, no. 7: 1118.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop