Stefania Amici

Thermal remote sensing of active vegetation fires and biomass burning events [Chapter 18]

his book provides a comprehensive overview of the state of the art in the field of thermal infrared remote sensing. Temperature is one of the most important physical environmental variables monitored by earth observing remote sensing systems. Temperature ranges define the boundaries of habitats on our planet. Thermal hazards endanger our resources and well-being. In this book renowned international experts have contributed chapters on currently available thermal sensors as well as innovative plans for future missions. Further chapters discuss the underlying physics and image processing techniques for analyzing thermal data. Ground-breaking chapters on applications present a wide variety of case studies leading to a deepened understanding of land and sea surface temperature dynamics, urban heat island effects, forest fires, volcanic eruption precursors, underground coal fires, geothermal systems, soil moisture variability, and temperature-based mineral discrimination. ‘Thermal Infrared Remote Sensing: Sensors, Methods, Applications’ is unique because of the large field it spans, the potentials it reveals, and the detail it providesThermal remote sensing is widely used in the detection, study, and management of biomass burning occurring in open vegetation fires. Such fires may be planned for land management purposes, may occur as a result of a malicious or accidental ignition by humans, or may result from lightning or other natural phenomena. Under suitable conditions, fires may spread rapidly and extensively, affecting the land cover properties of large areas, and releasing a wide variety of gases and particulates directly into Earth’s troposphere. On average, around 3.4 % of the Earth’s terrestrially vegetated area burns annually in this way. Vegetation fires inevitably involve high temperatures, so thermal remote sensing is well suited to its identification and study. Here we review the theoretical basis of the key approaches used to (1) detect actively burning fires; (2) characterize sub-pixel fires; and (3) estimate fuel consumption and smoke emissions. We describe the types of airborne and spaceborne systems that deliver data for use with these active fire thermal remote sensing methods, and provide some examples of how operational fire management and fire research have both benefited from the resulting information. We commence with a brief review of the significance and magnitude of biomass burning, both within the ‘whole Earth’ system and in more regional situations, aiming to highlight why thermal remote sensing has become so important to the study and management of open vegetation burning.

The 2011 Tohoku (Japan) Tsunami Inundation and Liquefaction Investigated Through Optical, Thermal, and SAR Data

We studied the disastrous effects of the tsunami triggered by the Mw 9.0 earthquake that occurred on March 11, 2011, offshore the Honshu island (Japan). The tsunami caused a huge amount of casualties and severe damage along most of the eastern coastline of the island. The data set used is composed of images from ASTER, visible and thermal, and ENVISAT SAR sensors. The processing and the analysis of data from different sources were performed in order to obtain the tsunami inundation map of the Sendai coastal area, to analyze inland factors driving the tsunami inundation, and to detect the liquefaction effects in the Chiba bay area as well. The obtained inundation line, with a maximum value of about 6 km, has been jointly analyzed with digital elevation model providing the run-up values, which are generally below 21 m in the ca. 60-km-long study area of Sendai. Moreover, from SAR coherence and intensity correlation, a wide area of subsidence is mapped at Chiba bay, which is reasonably related to strong ground shaking and pervasive liquefaction.

Thermal Remote Sensing of Active Vegetation Fires and Biomass Burning Events

Thermal remote sensing is widely used in the detection, study, and management of biomass burning occurring in open vegetation fires. Such fires may be planned for land management purposes, may occur as a result of a malicious or accidental ignition by humans, or may result from lightning or other natural phenomena. Under suitable conditions, fires may spread rapidly and extensively, affecting the land cover properties of large areas, and releasing a wide variety of gases and particulates directly into Earth’s troposphere. On average, around 3.4 % of the Earth’s terrestrially vegetated area burns annually in this way. Vegetation fires inevitably involve high temperatures, so thermal remote sensing is well suited to its identification and study. Here we review the theoretical basis of the key approaches used to (1) detect actively burning fires; (2) characterize sub-pixel fires; and (3) estimate fuel consumption and smoke emissions. We describe the types of airborne and spaceborne systems that deliver data for use with these active fire thermal remote sensing methods, and provide some examples of how operational fire management and fire research have both benefited from the resulting information. We commence with a brief review of the significance and magnitude of biomass burning, both within the ‘whole Earth’ system and in more regional situations, aiming to highlight why thermal remote sensing has become so important to the study and management of open vegetation burning.

Spectral analysis of aster and hyperion data for geological classification of volcano teide

This work is an evaluation, to which degree geological information can be obtained from modern remote sensing systems like the multispectral ASTER or the hyperspectral Hyperion sensor for a volcanic region like Teide Volcano (Tenerife, Canary Islands). To account for the enhanced information content these sensors provide, hyperspectral analysis methods, incorporating for example Minimum Noise Fraction-Transformation (MNF) for data quality assessment and noise reduction as well as Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) for supervised classification, were applied. Ground Truth reflectance data were obtained with a FieldSpec Pro measurements campaign conducted during later summer of 2007 in the frame of the EC project PREVIEW (http://www.preview-risk.com/).

Exploitation of SAR data to detect burned areas in the Sila mountain area (southern Italy)

This study focuses on testing the SAR coherence changes from Sentinel-1 data to detect burned areas and to compare the results with optical Sentinel-2 derived burned area product to be used as validation. Visible Infrared Imaging Radiometer Suite (VIIRS) data at 350 m resolution was used to identify active fires locations. We focused on a sequence of wildfires that affected the Sila mountain area during the summer of the 2017. This area of the Calabria region (southern Italy) was interested by a range of fires for the second half of July and the whole month of August ([1], [2]) due also to an extremely dry and hot summer. We used a pair of optical images acquired from Sentinel- 2 satellites on 24 July 2017 (pre-events) and 23 August 2017 (post-events). Firstly, we computed the Normalized Difference Vegetation Index (NDVI) for both images and calculated the difference between these two (dNDVI) at 10m resolution; the results put in evidence several areas characterized by vegetation reduction, with dNDVI values up to 0.3-0.4. Concerning the SAR data, we evaluated the coherence changes by exploiting two pairs of Sentinel-1 SAR data over the same area. Both pairs were acquired along descending orbit, respectively before (on July, 19th and 31st) and after (on September, 5th and 17th) the fires occurred in the Sila mountain area. The coherence was computed separately for the first (γpre) and the second pair (γpost) and the difference γpost - γpre was calculated. In this way, we evaluated the difference in coherence between September, i.e. post-fires, and July, i.e. pre-fires expecting a higher coherence after burning, due to the vegetation reduction. In several areas, the coherence seems to be consistent with the fire events showing increments up to 0.20-0.25. However, the increasing of coherence difference could also be due to other reasons such as the soil moisture variations in the proximity of lakes/rivers or the seasonal cultivation changes. Further analysis integrating more information such as the SAR amplitude signal and the cross-polarized backscattering coefficient will be conducted in order to better evaluate and discriminate any contributions.

Lava emplacement mapping with SAR and optical satellite data

In this paper, we exploited satellite remote sensing data, acquired by SAR and optical sensors to map the lava emplacement during the eruption of Pico do Fogo volcano, in Cape Verde. The eruption took place in November 2014, and lasted for about 2 months. The event was imaged by several satellite missions. In particular, the ESA Sentinel-1A platform operated in that area, collecting several images with its novel acquisition mode, the so-called TOPSAR. SAR images have been processed to extract changes automatically and to infer the advancement of the lava emitted from November 23, 2014 to January 2017, by using an adaptive parametric thresholding and a hierarchical split based approach. This automatic procedure allowed mapping the evolution of the lava coverage. The results obtained thanks to this method were compared to the ones derived by using the optical images collected by Landsat-8 and EO-1 optical sensors.

Aster temperature and emissivity validation on Volcano Teide

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ) has operated since 19 December 1999 from NASAs Terra Earth-orbiting, sun synchronous satellite. Emissivity and temperature standard products are based on the TES algorithms and required periodical validation campaign. In the frame of the EC project PREVIEW (http://www.preview-risk.com/) a field campaign on Volcano Teide was carried on, from the 16th to 24th of September 2007, to validate and to integrate the satellite derived products services.