scholarly journals Subpixel Analysis of Primary and Secondary Infrared Emitters with Nighttime VIIRS Data

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 83
Author(s):  
Christopher D. Elvidge ◽  
Mikhail Zhizhin ◽  
Feng Chi Hsu ◽  
Tamara Sparks ◽  
Tilottama Ghosh

Biomass burning is a coupled exothermic/endothermic system that transfers carbon in several forms to the atmosphere, ultimately leaving mineral ash. The exothermic phases include flaming and smoldering, which produce the heat that drives the endothermic processes. The endothermic components include pre-heating and pyrolysis, which produce the fuel consumed by flaming and smoldering. These components can be broadly distinguished from each other based on temperature. For several years, we have researched the subpixel analysis of two temperature phases present in fire pixels detected in nighttime VIIRS data. Here, we present the flaming subtractive method, with which we have successfully derived temperatures and source areas for two infrared (IR) emitters and a cooler background. This is developed as an add-on to the existing VIIRS nightfire algorithm version 3 (VNF v.3) which uses Planck curve fitting to calculate temperatures and source areas for a single IR emitter and background. The flaming subtractive method works with data collected in four spectral ranges: near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR) and long-wave infrared (LWIR). With sunlight eliminated, the NIR and SWIR radiances can be fully attributed to the primary IR emitter. The analysis begins with Planck curve modeling for the primary emitter based on the NIR and SWIR radiances, yielding temperature, source area and primary emitter radiances in all spectral bands. The primary emitter radiances are subtracted from each spectral band and then the residual radiance is analyzed for a secondary IR emitter and the background. Spurious results are obtained in pixels lacking a discernable secondary emitter. These misfit pixels revert back to the single IR emitter analysis of VNF v.3. In tests run for two California megafires, we found that the primary emitters straddle the temperature ranges for flaming and smoldering, the exothermic portions of biomass burning, which are apparently commingled on the ground. The secondary emitter temperatures span 350–750 K, corresponding to pre-heating and slow pyrolysis. The natural gas flare test case had few numbers of successful secondary emitter retrievals and a wide range of secondary emitter temperatures. The flaming subtractive analysis is the key addition to VNF version 4, which will commence production later in 2021. In 2022, we will seek validation of the VNF v.4 from nighttime Landsat and other data sources.

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.


2016 ◽  
Vol 22 (1) ◽  
pp. 95-107 ◽  
Author(s):  
Eder Paulo Moreira* ◽  
Márcio de Morisson Valeriano ◽  
Ieda Del Arco Sanches ◽  
Antonio Roberto Formaggio

The full potentiality of spectral vegetation indices (VIs) can only be evaluated after removing topographic, atmospheric and soil background effects from radiometric data. Concerning the former effect, the topographic effect was barely investigated in the context of VIs, despite the current availability correction methods and Digital elevation Model (DEM). In this study, we performed topographic correction on Landsat 5 TM spectral bands and evaluated the topographic effect on four VIs: NDVI, RVI, EVI and SAVI. The evaluation was based on analyses of mean and standard deviation of VIs and TM band 4 (near-infrared), and on linear regression analyses between these variables and the cosine of the solar incidence angle on terrain surface (cos i). The results indicated that VIs are less sensitive to topographic effect than the uncorrected spectral band. Among VIs, NDVI and RVI were less sensitive to topographic effect than EVI and SAVI. All VIs showed to be fully independent of topographic effect only after correction. It can be concluded that the topographic correction is required for a consistent reduction of the topographic effect on the VIs from rugged terrain.


Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5481 ◽  
Author(s):  
Beatriz Martinez ◽  
Raquel Leon ◽  
Himar Fabelo ◽  
Samuel Ortega ◽  
Juan F. Piñeiro ◽  
...  

Hyperspectral imaging (HSI) is a non-ionizing and non-contact imaging technique capable of obtaining more information than conventional RGB (red green blue) imaging. In the medical field, HSI has commonly been investigated due to its great potential for diagnostic and surgical guidance purposes. However, the large amount of information provided by HSI normally contains redundant or non-relevant information, and it is extremely important to identify the most relevant wavelengths for a certain application in order to improve the accuracy of the predictions and reduce the execution time of the classification algorithm. Additionally, some wavelengths can contain noise and removing such bands can improve the classification stage. The work presented in this paper aims to identify such relevant spectral ranges in the visual-and-near-infrared (VNIR) region for an accurate detection of brain cancer using in vivo hyperspectral images. A methodology based on optimization algorithms has been proposed for this task, identifying the relevant wavelengths to achieve the best accuracy in the classification results obtained by a supervised classifier (support vector machines), and employing the lowest possible number of spectral bands. The results demonstrate that the proposed methodology based on the genetic algorithm optimization slightly improves the accuracy of the tumor identification in ~5%, using only 48 bands, with respect to the reference results obtained with 128 bands, offering the possibility of developing customized acquisition sensors that could provide real-time HS imaging. The most relevant spectral ranges found comprise between 440.5–465.96 nm, 498.71–509.62 nm, 556.91–575.1 nm, 593.29–615.12 nm, 636.94–666.05 nm, 698.79–731.53 nm and 884.32–902.51 nm.


2020 ◽  
Vol 12 (8) ◽  
pp. 1238 ◽  
Author(s):  
Andrew Fletcher ◽  
Richard Mather

Small uncrewed aerial systems (UASs) generate imagery that can provide detailed information regarding condition and change if the products are reproducible through time. Densified point clouds form the basic information for digital surface models and orthorectified mosaics, so variable dense point reconstruction will introduce uncertainty. Eucalyptus trees typically have sparse and discontinuous canopies with pendulous leaves that present a difficult target for photogrammetry software. We examine how spectral band, season, solar azimuth, elevation, and some processing settings impact completeness and reproducibility of dense point clouds for shrub swamp and Eucalyptus forest canopy. At the study site near solar noon, selecting near infrared camera increased projected tree canopy fourfold, and dense point features more than 2 m above ground were increased sixfold compared to red spectral bands. Near infrared (NIR) imagery improved projected and total dense features two- and threefold, respectively, compared to default green band imagery. The lowest solar elevation captured (25°) consistently improved canopy feature reconstruction in all spectral bands. Although low solar elevations are typically avoided for radiometric reasons, we demonstrate that these conditions improve the detection and reconstruction of complex tree canopy features in natural Eucalyptus forests. Combining imagery sets captured at different solar elevations improved the reproducibility of dense point clouds between seasons. Total dense point cloud features reconstructed were increased by almost 10 million points (20%) when imagery used was NIR combining solar noon and low solar elevation imagery. It is possible to use agricultural multispectral camera rigs to reconstruct Eucalyptus tree canopy and shrub swamp by combining imagery and selecting appropriate spectral bands for processing.


2015 ◽  
Vol 45 (8) ◽  
pp. 1077-1085 ◽  
Author(s):  
Nea Kuusinen ◽  
Pauline Stenberg ◽  
Erkki Tomppo ◽  
Pierre Bernier ◽  
Frank Berninger

Inherent variability in the spectral properties of boreal forests complicates the retrieval of canopy properties such as canopy leaf area index from satellite images. Understanding the drivers of this variability could help provide better estimates of desired canopy cover properties. Field plot data from the Finnish National Forest Inventory and Landsat thematic mapper (TM) images were used to investigate the variation in canopy and understory reflectance during stand development in coniferous boreal forests. Spectral data for each plot were obtained from the Landsat pixel within which the plot center coordinates fell. Nonlinear unmixing was used to estimate the bidirectional reflectance factors (BRFs) of the “sunlit understory” and “canopy and shaded ground” components by site fertility and stand development classes. A forest albedo model was used to estimate the contribution of diffuse radiation reflected downwards from the canopy to the sunlit understory component. The sunlit understory BRF in the near-infrared spectral band decreased as the site fertility decreased and the forest matured, whereas the sunlit understory BRFs in the red and shortwave-infrared spectral bands concurrently increased. The BRFs of the canopy and shaded ground component decreased slightly during stand development, mostly in the near-infrared spectral band. Adding the diffuse contribution to the sunlit understory component changed the estimated component BRFs only a little (0.1%–1.7%) compared with those obtained using a linear mixing assumption. This effect was largest in the near-infrared spectral band and smallest in the red spectral band. For Norway spruce plots, the measured and estimated forest variables were well correlated with the BRFs in all of the studied spectral bands, but for the Scots pine plots, the correlations were notably weaker. Results show a greater importance of the fraction of visible sunlit understory on forest reflectance in Scots pine than in Norway spruce forests.


Author(s):  
C. Gomez ◽  
A. Gholizadeh ◽  
L. Borůvka ◽  
P. Lagacherie

Mapping of topsoil properties using Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery requires large sets of ground measurements for calibrating the models that estimate soil properties. To avoid collecting such expensive data, we proposed a procedure including two steps that involves only legacy soil data that were collected over and?or around the study site: <i>1)</i> estimation of a soil property using a spectral index of the literature and <i>2)</i> standardisation of the estimated soil property using legacy soil data. This approach was tested for mapping clay contents in a Mediterranean region in which VNIR/SWIR AISA-DUAL hyperspectral airborne data were acquired. The spectral index was the one proposed by Levin et al (2007) using the spectral bands at 2209, 2133 and 2225 nm. Two legacy soil databases were tested as inputs of the procedure: the <i>Focused-Legacy</i> database composed of 67 soil samples collected in 2000 over the study area, and the No-Focused-Legacy database composed of 64 soil samples collected between 1973 and 1979 around but outside of the study area. The results were compared with those obtained from 120 soil samples collected over the study area during the hyperspectral airborne data acquisition, which were considered as a reference. <br><br> Our results showed that: <i>1)</i> the spectral index with no further standardisation offered predictions with high accuracy in term of coefficient of correlation <i>r</i> (0.71), but also high <i>bias</i> (&minus;414 g/kg) and <i>SEP</i> (439 g/kg), <i>2)</i> the standardisation using both legacy soil databases allowed an increase of accuracy (<i>r</i> = 0.76) and a reduction of <i>bias</i> and <i>SEP</i> and <i>3)</i> a better standardisation was obtained by using the <i>Focused-Legacy</i> database rather than the <i>No-Focused-Legacy</i> database. Finally, the clay predicted map obtained with standardisation using the <i>Focused-Legacy</i> database showed pedologically-significant soil spatial structures with clear short-scale variations of topsoil clay contents in specific areas. <br><br> This study, associated with the coming availability of a next generation of hyperspectral VNIR/SWIR satellite data for the entire globe, paves the way for inexpensive methods for delivering high resolution soil properties maps.


2009 ◽  
Vol 6 (3) ◽  
pp. 4107-4124
Author(s):  
J. A. Sobrino ◽  
J. C. Jiménez-Muñoz ◽  
P. J. Zarco-Tejada ◽  
G. Sepulcre-Cantó ◽  
E. de Miguel ◽  
...  

Abstract. The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004. This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for land surface temperature and emissivity retrieval as well as the estimation of evapotranspiration from AHS data. Errors were found to be around 1.5 K for land surface temperature and 1 mm/day for evapotranspiration.


2011 ◽  
Vol 83 (4) ◽  
pp. 1231-1242 ◽  
Author(s):  
Sílvia N. M. Yanagi ◽  
Marcos H. Costa

This study evaluates the sensitivity of the surface albedo simulated by the Integrated Biosphere Simulator (IBIS) to a set of Amazonian tropical rainforest canopy architectural and optical parameters. The parameters tested in this study are the orientation and reflectance of the leaves of upper and lower canopies in the visible (VIS) and near-infrared (NIR) spectral bands. The results are evaluated against albedo measurements taken above the K34 site at the INPA (Instituto Nacional de Pesquisas da Amazônia) Cuieiras Biological Reserve. The sensitivity analysis indicates a strong response to the upper canopy leaves orientation (x up) and to the reflectivity in the near-infrared spectral band (rNIR,up), a smaller sensitivity to the reflectivity in the visible spectral band (rVIS,up) and no sensitivity at all to the lower canopy parameters, which is consistent with the canopy structure. The combination of parameters that minimized the Root Mean Square Error and mean relative error are Xup = 0.86, rVIS,up = 0.062 and rNIR,up = 0.275. The parameterizations performed resulted in successful simulations of tropical rainforest albedo by IBIS, indicating its potential to simulate the canopy radiative transfer for narrow spectral bands and permitting close comparison with remote sensing products.


2017 ◽  
Vol 98 (8) ◽  
pp. 1637-1658 ◽  
Author(s):  
Jun Yang ◽  
Zhiqing Zhang ◽  
Caiying Wei ◽  
Feng Lu ◽  
Qiang Guo

Abstract China is developing a new generation of geostationary meteorological satellites called Fengyun-4 (FY-4), which is planned for launch beginning in 2016. Following upon the current FY-2 satellite series, FY-4 will carry four new instruments: the Advanced Geosynchronous Radiation Imager (AGRI), the Geosynchronous Interferometric Infrared Sounder (GIIRS), the Lightning Mapping Imager (LMI), and the Space Environment Package (SEP). The first satellite of the FY-4 series launched on 11 December 2016 is experimental, and the following four or more satellites will be operational. The main objectives of the FY-4 series are to monitor rapidly changing weather systems and to improve warning and forecasting capabilities. The FY-4 measurements are aimed at accomplishing 1) high temporal and spatial resolution imaging in 14 spectral bands from the visible, near-infrared, and infrared (IR) spectral regions; 2) lightning imaging; and 3) high-spectral-resolution IR sounding observations over China and adjacent regions. FY-4 will also enhance the space weather monitoring and warning with SEP. Current products from FY-2 will be improved by FY-4, and a number of new products will also be introduced. FY-4’s sounding and imaging data will be used to improve applications in a wide range of ocean, land, and atmosphere monitoring plus forecasting extreme weather (especially typhoons and thunderstorms); overall, FY-4 will contribute to more accurate understanding and forecasting of China’s weather, climate, environment, and natural disasters. This new generation of Chinese geostationary weather satellites is being developed in parallel with the new generation of geostationary meteorological satellite systems from the international community of satellite providers and is intended to be an important contribution to the global observing system.


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