scholarly journals Ground-Based Corroboration of GOES-17 Fire Detection Capabilities During Ignition of the Kincade Fire

2020 ◽  
pp. 105-110
Author(s):  
T. Todd Lindley ◽  
Alexander B. Zwink ◽  
Chad M. Gravelle ◽  
Christopher C. Schmidt ◽  
Cynthia K. Palmer ◽  
...  

Corroboration of Geostationary Operational Environmental Satellite-17 (GOES-17) wildland fire detection capabilities occurred during the 24 October 2019 (evening of 23 October LST) ignition of the Kincade Fire in northern California. Post-analysis of remote sensing data compared to observations by the ALERTWildfire fire surveillance video system suggests that the emerging Kincade Fire hotspot was visually evident in GOES17 shortwave infrared imagery 52 s after the initial near-infrared heat source detected by the ground-based camera network. GOES-17 Advanced Baseline Imager Fire Detection Characteristic algorithms registered the fire 5 min after ignition. These observations represent the first documented comparative dataset between fire initiation and satellite detection, and thus provide context for GOES-16/17 wildland fire detections.

Author(s):  
D. Spiller ◽  
L. Ansalone ◽  
S. Amici ◽  
A. Piscini ◽  
P. P. Mathieu

Abstract. This paper deals with the analysis and detection of wildfires by using PRISMA imagery. Precursore IperSpettrale della Mis­sione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 0.4–2.5 µm and an average spectral resolution less than 10 nm. In this work, we used the PRISMA hypercube acquired during the Australian bushfires of December 2019 in New South Wales. The analysis of the image is presented considering the unique amount of information contained in the continuous spectral signature of the hypercube. The Carbon dioxide Continuum-Interpolated Band Ratio (CO2 CIBR), Hyperspectral Fire Detection Index (HFDI), and Normalized Burn Index (NBR) will be used to analyze the informative content of the image, along with the analysis of some specific visible, near-infrared and shortwave-infrared bands. A multiclass classification is presented by using a I-dimensional convolutional neural network (CNN), and the results will be com­pared with the ones given by a support vector machine classifier reported in literature. Finally, some preliminary results related to wildfire temperature estimation are presented.


2019 ◽  
Author(s):  
Arundhati Deshmukh ◽  
Danielle Koppel ◽  
Chern Chuang ◽  
Danielle Cadena ◽  
Jianshu Cao ◽  
...  

Technologies which utilize near-infrared (700 – 1000 nm) and short-wave infrared (1000 – 2000 nm) electromagnetic radiation have applications in deep-tissue imaging, telecommunications and satellite telemetry due to low scattering and decreased background signal in this spectral region. However, there are few molecular species, which absorb efficiently beyond 1000 nm. Transition dipole moment coupling (e.g. J-aggregation) allows for redshifted excitonic states and provides a pathway to highly absorptive electronic states in the infrared. We present aggregates of two cyanine dyes whose absorption peaks redshift dramatically upon aggregation in water from ~ 800 nm to 1000 nm and 1050 nm with sheet-like morphologies and high molar absorptivities (e ~ 10<sup>5 </sup>M<sup>-1</sup>cm<sup>-1</sup>). To describe this phenomenology, we extend Kasha’s model for J- and H-aggregation to describe the excitonic states of <i> 2-dimensional aggregates</i> whose slip is controlled by steric hindrance in the assembled structure. A consequence of the increased dimensionality is the phenomenon of an <i>intermediate </i>“I-aggregate”, one which redshifts yet displays spectral signatures of band-edge dark states akin to an H-aggregate. We distinguish between H-, I- and J-aggregates by showing the relative position of the bright (absorptive) state within the density of states using temperature dependent spectroscopy. Our results can be used to better design chromophores with predictable and tunable aggregation with new photophysical properties.


2021 ◽  
Vol 13 (3) ◽  
pp. 536
Author(s):  
Eve Laroche-Pinel ◽  
Mohanad Albughdadi ◽  
Sylvie Duthoit ◽  
Véronique Chéret ◽  
Jacques Rousseau ◽  
...  

The main challenge encountered by Mediterranean winegrowers is water management. Indeed, with climate change, drought events are becoming more intense each year, dragging the yield down. Moreover, the quality of the vineyards is affected and the level of alcohol increases. Remote sensing data are a potential solution to measure water status in vineyards. However, important questions are still open such as which spectral, spatial, and temporal scales are adapted to achieve the latter. This study aims at using hyperspectral measurements to investigate the spectral scale adapted to measure their water status. The final objective is to find out whether it would be possible to monitor the vine water status with the spectral bands available in multispectral satellites such as Sentinel-2. Four Mediterranean vine plots with three grape varieties and different water status management systems are considered for the analysis. Results show the main significant domains related to vine water status (Short Wave Infrared, Near Infrared, and Red-Edge) and the best vegetation indices that combine these domains. These results give some promising perspectives to monitor vine water status.


2020 ◽  
Author(s):  
L. Granlund ◽  
M. Keinänen ◽  
T. Tahvanainen

Abstract Aims Hyperspectral imaging (HSI) has high potential for analysing peat cores, but methodologies are deficient. We aimed for robust peat type classification and humification estimation. We also explored other factors affecting peat spectral properties. Methods We used two laboratory setups: VNIR (visible to near-infrared) and SWIR (shortwave infrared) for high resolution imaging of intact peat profiles with fen-bog transitions. Peat types were classified with support vector machines, indices were developed for von Post estimation, and K-means clustering was used to analyse stratigraphic patterns in peat quality. With separate experiments, we studied spectral effects of drying and oxidation. Results Despite major effects, oxidation and water content did not impede robust HSI classification. The accuracy between Carex peat and Sphagnum peat in validation was 80% with VNIR and 81% with SWIR data. The spectral humification indices had accuracies of 82% with VNIR and 56%. Stratigraphic HSI patterns revealed that 36% of peat layer shifts were inclined by over 20 degrees. Spectral indices were used to extrapolate visualisations of element concentrations. Conclusions HSI provided reliable information of basic peat quality and was useful in visual mapping, that can guide sampling for other analyses. HSI can manage large amounts of samples to widen the scope of detailed analysis beyond single profiles and it has wide potential in peat research beyond the exploratory scope of this paper. We were able to confirm the capacity of HSI to reveal shifts of peat quality, connected to ecosystem-scale change.


2021 ◽  
Vol 13 (10) ◽  
pp. 5518
Author(s):  
Honglyun Park ◽  
Jaewan Choi

Worldview-3 satellite imagery provides panchromatic images with a high spatial resolution and visible near infrared (VNIR) and shortwave infrared (SWIR) bands with a low spatial resolution. These images can be used for various applications such as environmental analysis, urban monitoring and surveying for sustainability. In this study, mineral detection was performed using Worldview-3 satellite imagery. A pansharpening technique was applied to the spatial resolution of the panchromatic image to effectively utilize the VNIR and SWIR bands of Worldview-3 satellite imagery. The following representative similarity analysis techniques were implemented for the mineral detection: the spectral angle mapper (SAM), spectral information divergence (SID) and the normalized spectral similarity score (NS3). In addition, pixels that could be estimated to indicate minerals were calculated by applying an empirical threshold to each similarity analysis result. A majority voting technique was applied to the results of each similarity analysis and pixels estimated to indicate minerals were finally selected. The results of each similarity analysis were compared to evaluate the accuracy of the proposed methods. From that comparison, it could be confirmed that false negative and false positive rates decreased when the methods proposed in the present study were applied.


2021 ◽  
Vol 13 (13) ◽  
pp. 2604
Author(s):  
Patrick Osei Darko ◽  
Margaret Kalacska ◽  
J. Pablo Arroyo-Mora ◽  
Matthew E. Fagan

Hyperspectral remote sensing across multiple spatio-temporal scales allows for mapping and monitoring mangrove habitats to support urgent conservation efforts. The use of hyperspectral imagery for assessing mangroves is less common than for terrestrial forest ecosystems. In this study, two well-known measures in statistical physics, Mean Information Gain (MIG) and Marginal Entropy (ME), have been adapted to high spatial resolution (2.5 m) full range (Visible-Shortwave-Infrared) airborne hyperspectral imagery. These two spectral complexity metrics describe the spatial heterogeneity and the aspatial heterogeneity of the reflectance. In this study, we compare MIG and ME with surface reflectance for mapping mangrove extent and species composition in the Sierpe mangroves in Costa Rica. The highest accuracy for separating mangroves from forest was achieved with visible-near infrared (VNIR) reflectance (98.8% overall accuracy), following by shortwave infrared (SWIR) MIG and ME (98%). Our results also show that MIG and ME can discriminate dominant mangrove species with higher accuracy than surface reflectance alone (e.g., MIG–VNIR = 93.6% vs. VNIR Reflectance = 89.7%).


2002 ◽  
Vol 34 ◽  
pp. 81-88 ◽  
Author(s):  
Massimo Frezzotti ◽  
Stefano Gandolfi ◽  
Floriana La Marca ◽  
Stefano Urbini

AbstractAs part of the International Trans-Antarctic Scientific Expedition project, the Italian Antarctic Programme undertook two traverses from the Terra Nova station to Talos Dome and to Dome C. Along the traverses, the party carried out several tasks (drilling, glaciological and geophysical exploration). The difference in spectral response between glazed surfaces and snow makes it simple to identify these areas on visible/near-infrared satellite images. Integration of field observation and remotely sensed data allows the description of different mega-morphologic features: wide glazed surfaces, sastrugi glazed surface fields, transverse dunes and megadunes. Topography global positioning system, ground penetrating radar and detailed snow-surface surveys have been carried out, providing new information about the formation and evolution of mega-morphologic features. The extensive presence, (up to 30%) of glazed surface caused by a long hiatus in accumulation, with an accumulation rate of nil or slightly negative, has a significant impact on the surface mass balance of a wide area of the interior part of East Antarctica. The aeolian processes creating these features have important implications for the selection of optimum sites for ice coring, because orographic variations of even a few metres per kilometre have a significant impact on the snow-accumulation process. Remote-sensing surveys of aeolian macro-morphology provide a proven, high-quality method for detailed mapping of the interior of the ice sheet’s prevalent wind direction and could provide a relative indication of wind intensity.


2021 ◽  
Vol 13 (2) ◽  
pp. 318
Author(s):  
Jae-Jin Park ◽  
Kyung-Ae Park ◽  
Pierre-Yves Foucher ◽  
Philippe Deliot ◽  
Stephane Le Floch ◽  
...  

With an increase in the overseas maritime transport of hazardous and noxious substances (HNSs), HNS-related spill accidents are on the rise. Thus, there is a need to completely understand the physical and chemical properties of HNSs. This can be achieved through establishing a library of spectral characteristics with respect to wavelengths from visible and near-infrared (VNIR) bands to shortwave infrared (SWIR) wavelengths. In this study, a ground HNS measurement experiment was conducted for artificially spilled HNS by using two hyperspectral cameras at VNIR and SWIR wavelengths. Representative HNSs such as styrene and toluene were spilled into an outdoor pool and their spectral characteristics were obtained. The relative ratio of HNS to seawater decreased and increased at 550 nm and showed different constant ratios at the SWIR wavelength. Noise removal and dimensional compression procedures were conducted by applying principal component analysis on HNS hyperspectral images. Pure HNS and seawater endmember spectra were extracted using four spectral mixture techniques—N-FINDR, pixel purity index (PPI), independent component analysis (ICA), and vertex component analysis (VCA). The accuracy of detection values of styrene and toluene through the comparison of the abundance fraction were 99.42% and 99.56%, respectively. The results of this study are useful for spectrum-based HNS detection in marine HNS accidents.


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