Site Characterization Using Integrated Imaging Analysis Methods on Satellite Data of the Islamabad, Pakistan, Region

We develop an integrated digital imaging analysis approach to produce a first-approximation site characterization map for Islamabad, Pakistan, based on remote-sensing data. We apply both pixel-based and object-oriented digital imaging analysis methods to characterize detailed (1:50,000) geomorphology and geology from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. We use stereo-correlated relative digital elevation models (rDEMs) derived from ASTER data, as well as spectra in the visible near-infrared (VNIR) to thermal infrared (TIR) domains. The resulting geomorphic units in the study area are classified as mountain (including the Margala Hills and the Khairi Murat Ridge), piedmont, and basin terrain units. The local geologic units are classified as limestone in the Margala Hills and the Khairi Murat Ridge and sandstone rock types for the piedmonts and basins. Shear-wave velocities for these units are assigned in ranges based on established correlations in California. These ranges include Vs30-values to be greater than 500 m/sec for mountain units, 200–600 m/sec for piedmont units, and less than 300 m/sec for basin units. While the resulting map provides the basis for incorporating site response in an assessment of seismic hazard for Islamabad, it also demonstrates the potential use of remote-sensing data for site characterization in regions where only limited conventional mapping has been done

Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS−MIROVA Thermal Data Series

In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

Thermal-infrared spectral and angular characterization of crude oil and seawater emissivities for oil slick identification

Previous work has shown that crude oil emissivity is lower than that of seawater in the thermal-infrared (TIR) spectrum. Thus, oil slicks cause an emissivity decrease relative to seawater in that region. The aim of this paper was to carry out experimental measurements to characterize crude oil and seawater emissivity spectral and angular variations. The results showed that crude oil emissivity is lower than seawater emissivity and essentially flat in the 8 - 13 μm atmospheric window. Crude oil emissivity has a marked emissivity decrease with angle (from 0.956±0.005 at 15º to 0.873±0.007 at 65º), even higher than that of seawater, and thus the seawater-crude emissivity difference increases with angle (from +0.030±0.007 at close-to-nadir angles up to +0.068±0.010 in average at 65º). In addition, the experimental results were checked by using the dual-angle viewing capability of the ENVISAT-AATSR images (i.e., 0º-22º and 53º-55º for nadir and forward views respectively), with data acquired during the BP Deepwater Horizon oil slick in 2010. The objective was to explore the applicability to satellite observations. Nadir-forward emissivity differences of +0.028 and +0.017 were obtained for the oil slick and surrounding clean seawater respectively. Emissivity differences between the seawater and oil slick were +0.035 and +0.046 for nadir and forward views respectively, in agreement with the experimental data. The increase of seawater-crude emissivity difference with angle gives significant differences for off-nadir observation angles, showing a new chance of crude oil slick identification from satellite TIR data

QUANTITATIVE THERMAL INFRARED ANALYSES OF VOLCANIC PROCESSES AND PRODUCTS: APPLICATION TO BEZYMIANNY VOLCANO, RUSSIA

Bezymianny (55.98°N, 160.59°E) is a Holocene andesitic composite volcano with a summit elevation of approximately 2,900 m and is located on the Kamchatka Peninsula, eastern Russia. Previously inactive for about 1,000 years, Bezymianny reactivated in 1955, culminating in a cataclysmic eruption on 30 March 1956. This directed blast generated a 1.3 km (north-south) by 2.8 km (east-west) horseshoe shaped crater opening to the east, similar in morphology and activity to Mt. St. Helens (USA). During the last 30 years Bezymianny has been regularly active, erupting one to two times per year on average. This work focuses on field-based and remote sensing observations of explosive eruptions and their products at Bezymianny, concentrating on the pyroclastic flow (PF) deposits on the southeast flank. The events of March 2000, January 2005, December 2006, May 2007 and October 2007 were focused on to elucidate information on the pyroclastic flow (PF) deposits that were emplaced. Two principal themes were addressed: (1) A thermal infrared (TIR) investigation of the eruptive events and products. This encompassed ground-based field work, Forward Looking Infrared Radiometer (FLIR) image data, and spaceborne data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). (2) A micrometer-scale textural investigation of vesicular block and ash samples collected in the field on the pyroclastic flow deposits. Scanning Electron Microscope (SEM) images were used to generate micron-scale digital elevation models (DEM) for the surfaces of each volcanic sample collected. These were compared to TIR emission spectra that were deconvolved to estimate surface vesicularity. This work demonstrates the utility of TIR observations from satellite, aerial, and ground-based data that, in combination with standard geological mapping, provide timely, accurate, and quantitative remote sensing data to assist in the prediction and monitoring of explosive volcanoes

Implementation of Robust Satellite Techniques for Volcanoes on ASTER Data under the Google Earth Engine Platform

The RST (Robust Satellite Techniques) approach is a multi-temporal scheme of satellite data analysis widely used to investigate and monitor thermal volcanic activity from space through high temporal resolution data from sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In this work, we present the results of the preliminary RST algorithm implementation to thermal infrared (TIR) data, at 90 m spatial resolution, from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Results achieved under the Google Earth Engine (GEE) environment, by analyzing 20 years of satellite observations over three active volcanoes (i.e., Etna, Shishaldin and Shinmoedake) located in different geographic areas, show that the RST-based system, hereafter named RASTer, detected a higher (around 25% more) number of thermal anomalies than the well-established ASTER Volcano Archive (AVA). Despite the availability of a less populated dataset than other sensors, the RST implementation on ASTER data guarantees an efficient identification and mapping of volcanic thermal features even of a low-intensity level. To improve the temporal continuity of the active volcanoes monitoring, the possibility of exploiting RASTer is here addressed, in the perspective of an operational multi-satellite observing system. The latter could include mid-high spatial resolution satellite data (e.g., Sentinel-2/MSI, Landsat-8/OLI), as well as those at higher-temporal (lower spatial) resolution (e.g., EOS/MODIS, Suomi-NPP/VIIRS, Sentinel-3/SLSTR), for which RASTer could provide useful algorithm’s validation and training dataset

Spatial Analysis of Post-Hurricane Katrina Thermal Pattern and Intensity in Greater New Orleans: Implications for Urban Heat Island Research

In 2005, Hurricane Katrina’s diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, caused by an extreme weather event. Using remote sensing visualization methods, field data, and local knowledge, the author found there was a measurable change in the pattern and intensity of the New Orleans UHI effect, as well as concomitant changes to vegetative land cover. This finding may be relevant for urban planners and citizens, especially in the context of recovery from a large-scale disaster of a coastal city, regarding future weather events, and other natural and human impacts