Forest-fire-scar aging using SPOT-VEGETATION for Canadian ecoregions

2003 ◽  
Vol 33 (6) ◽  
pp. 1116-1125 ◽  
Author(s):  
Brian D Amiro ◽  
Jing M Chen
Keyword(s):  
Near Infrared ◽  
Forest Succession ◽  
Short Wave ◽  
Federal Agencies ◽  
Infrared Band ◽  
Fire Scars ◽  
Fire Scar ◽  
Remote Sensing Techniques ◽  
Large Effort ◽  
Nominal Resolution

The mapping of Canadian fires is a large effort supported by provincial, territorial, and federal agencies. Remote sensing techniques can aid in mapping, especially in remote areas and during busy fire seasons. The SPOT-VEGETATION (SPOT-VGT) sensor has previously shown promise at distinguishing fire scars on the landscape. The usefulness of SPOT-VGT to age fires in 18 Canadian ecoregions was evaluated for a period up to 50 years since fire, analysing more than 250 000 pixels (nominal resolution about 1 km2). The SPOT-VGT reflectances were evaluated using the ratio of the short-wave infrared band (1.58–1.75 µm) to near-infrared band (0.78–0.89 µm), compared with the Canadian large-fire database (fires greater than 200 ha in size). Nonlinear regressions were significant for all ecoregions with r2 values being greater than 0.57 for 16 of them. Five ecoregions groupings had similar relationships, consistent with their contiguous pattern on the landscape. The prediction of fire-scar age depends on ecoregion and can be successful over periods as short as 6 years to as long as 30 years. The root mean square error for all ecoregions ranged from 5 years for recent burns to about 12 years for three decades following fire. This tool is useful to get approximate fire-scar ages, but the accuracy is limited because of the variation in forest succession on the landscape, and it cannot replace more detailed mapping done currently by fire agencies.

scholarly journals Forest and land fire smoke detection using GCOM-C data (case study: Pulang Pisau, Central Kalimantan)

2021 ◽  
Vol 893 (1) ◽  
pp. 012068
Author(s):  
K I N Rahmi ◽  
N Febrianti ◽  
I Prasasti
Keyword(s):  
Near Infrared ◽  
Thermal Infrared ◽  
Short Wave ◽  
Forest Land ◽  
Visual Interpretation ◽  
Infrared Band ◽  
Central Kalimantan ◽  
Fire Smoke ◽  
Shortwave Infrared

Abstract Forest/land fire give bad impact of heavy smoke on peatland area in Indonesia. Forest/land fire smoke need to be identified the distribution periodically. New satellite of GCOM-C has been launched to monitor climate condition and have visible, near infrared and thermal infrared. This study has objective to identify fire smoke from GCOM-C data. GCOM-C data has wavelength range from 0.38 to 12 μm it covers visible, near infrared, short-wave infrared and thermal infrared. It is relatively similar to MODIS or Himawari-8 images which could identify forest/land fire smoke. The methodology is visual interpretation to detect forest/land fire smoke using near infrared band (VN08), shortwave infrared band (SW03), and thermal bands (T01 and T02). Hotspot data is overlaid with GCOM-C image to represent the location of fire events. Combination of composite RGB image has been applied to detect forest/land fire smoke. GCOM-C image of VN8 bands and combination of thermal band in composite image could be used to detect fire smoke in Pulang Pisau, Central Kalimantan.

scholarly journals Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study

2019 ◽  
Vol 11 (7) ◽  
pp. 807 ◽  
Author(s):  
Jibo Yue ◽  
Qingjiu Tian ◽  
Xinyu Dong ◽  
Kaijian Xu ◽  
Chengquan Zhou
Keyword(s):  
Remote Sensing ◽  
Laboratory Study ◽  
Crop Residue ◽  
Near Infrared ◽  
Crop Residues ◽  
Broad Band ◽  
Field Testing ◽  
Short Wave ◽  
Spectral Indices ◽  
Infrared Band

Crop residue left in the field after harvest helps to protect against water and wind erosion, increase soil organic matter, and improve soil quality, so a proper estimate of the quantity of crop residue is crucial to optimize tillage and for research into environmental effects. Although remote-sensing-based techniques to estimate crop residue cover (CRC) have proven to be good tools for determining CRC, their application is limited by variations in the moisture of crop residue and soil. In this study, we propose a crop residue angle index (CRAI) to estimate the CRC for four distinct soils with varying soil moisture (SM) content and crop residue moisture (CRM). The current study uses laboratory-based tests ((i) a dry dataset (air-dried soils and crop residues, n = 392); (ii) a wet dataset (wet soils and crop residues, n = 822); (iii) a saturated dataset (saturated soils and crop residues, n = 402); and (iv) all datasets (n = 1616)), which allows us to analysis the soil and crop residue hyperspectral response to varying SM/CRM. The CRAI combines two features that reflect the moisture content in soil and crop residue. The first is the different reflectance of soil and crop residue as a function of moisture in the near-infrared band (833 nm) and short-wave near-infrared band (1670 nm), and the second is different reflectance of soils and crop residues to lignin, cellulose, and moisture in the bands at 2101, 2031, and 2201 nm. The effects of moisture and soil type on the proposed CRAI and selected traditional spectral indices ((i) hyperspectral cellulose absorption index; (ii) hyperspectral shortwave infrared normalized difference residue index; and (iii) selected broad-band spectral indices) were compared by using a laboratory-based dataset. The results show that the SM/CRM significantly affects the broad-band spectral indices and all other spectral indices investigated are less correlated with CRC when using all datasets than when using only the dry, wet, or saturated dataset. Laboratory study suggests that the CRAI is promising for estimating CRC with the four soils and with varying SM/CRM. However, because the CRAI was only validated by a laboratory-based dataset, additional field testing is thus required to verify the use of satellite hyperspectral remote-sensing images for different crops and ecological areas.

scholarly journals Estimation of Water Coverage in Permanent and Temporary Shallow Lakes and Wetlands by Combining Remote Sensing Techniques and Genetic Programming: Application to the Mediterranean Basin of the Iberian Peninsula

2021 ◽  
Vol 13 (4) ◽  
pp. 652
Author(s):  
Carolina Doña ◽  
Daniel Morant ◽  
Antonio Picazo ◽  
Carlos Rochera ◽  
Juan Manuel Sánchez ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Shallow Lakes ◽  
Near Infrared ◽  
Salt Ponds ◽  
Infrared Band ◽  
Landsat 7 ◽  
Global Change Scenarios ◽  
Remote Sensing Techniques ◽  
Ecological Types ◽  
Sentinel 2

This work aims to validate the wide use of an algorithm developed using genetic programing (GP) techniques allowing to discern between water and non-water pixels using the near infrared band and different thresholds. A total of 34 wetlands and shallow lakes of 18 ecological types were used for validation. These include marshes, salt ponds, and saline and freshwater, temporary and permanent shallow lakes. Furthermore, based on the spectral matching between Landsat and Sentinel-2 sensors, this methodology was applied to Sentinel-2 imagery, improving the spatial and temporal resolution. When compared to other techniques, GP showed better accuracy (over 85% in most cases) and acceptable kappa values in the estimation of water pixels (κ ≥ 0.7) in 10 of the 18 assayed ecological types evaluated with Landsat-7 and Sentinel-2 imagery. The improvements were especially achieved for temporary lakes and wetlands, where existing algorithms were scarcely reliable. This shows that GP algorithms applied to remote sensing satellite imagery can be a valuable tool to monitor water coverage in wetlands and shallow lakes where multiple factors cause a low resolution by commonly used water indices. This allows the reconstruction of hydrological series showing their hydrological behaviors during the last three decades, being useful to predict how their hydrological pattern may behave under future global change scenarios.

Two-Dimensional Near-Infrared and Shortwave Infrared Molecular Aggregates: Taking Kasha’s Model to the Next Dimension

2019 ◽  
Author(s):  
Arundhati Deshmukh ◽  
Danielle Koppel ◽  
Chern Chuang ◽  
Danielle Cadena ◽  
Jianshu Cao ◽  
...  
Keyword(s):  
Near Infrared ◽  
Photophysical Properties ◽  
Satellite Telemetry ◽  
Transition Dipole Moment ◽  
Short Wave ◽  
Tissue Imaging ◽  
Transition Dipole ◽  
Deep Tissue Imaging ◽  
Excitonic States ◽  
Shortwave Infrared

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.

scholarly journals Understanding Vine Hyperspectral Signature through Different Irrigation Plans: A First Step to Monitor Vineyard Water Status

2021 ◽  
Vol 13 (3) ◽  
pp. 536
Author(s):  
Eve Laroche-Pinel ◽  
Mohanad Albughdadi ◽  
Sylvie Duthoit ◽  
Véronique Chéret ◽  
Jacques Rousseau ◽  
...  
Keyword(s):  
Near Infrared ◽  
Water Status ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Short Wave ◽  
Spatial And Temporal Scales ◽  
Spectral Bands ◽  
Main Challenge ◽  
Spectral Scale ◽  
Grape Varieties

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.

scholarly journals Atmospheric Compensation of PRISMA Data by Means of a Learning Based Approach

2021 ◽  
Vol 13 (15) ◽  
pp. 2967
Author(s):  
Nicola Acito ◽  
Marco Diani ◽  
Gregorio Procissi ◽  
Giovanni Corsini
Keyword(s):  
Spectral Range ◽  
Near Infrared ◽  
Random Noise ◽  
Synthetic Data ◽  
Regression Function ◽  
Short Wave ◽  
Hyperspectral Data ◽  
Electromagnetic Spectrum ◽  
Great Opportunity ◽  
Atmospheric Compensation

Atmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named LBAC, has been proposed for the AC of airborne hyperspectral data in the visible and near-infrared (VNIR) spectral range. LBAC makes use of a parametric regression function whose parameters are learned by a strategy based on synthetic data that accounts for (1) a physics-based model for the radiative transfer, (2) the variability of the surface reflectance spectra, and (3) the effects of random noise and spectral miscalibration errors. In this work we extend LBAC with respect to two different aspects: (1) the platform for data acquisition and (2) the spectral range covered by the sensor. Particularly, we propose the extension of LBAC to spaceborne hyperspectral sensors operating in the VNIR and short-wave infrared (SWIR) portion of the electromagnetic spectrum. We specifically refer to the sensor of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission, and the recent Earth Observation mission of the Italian Space Agency that offers a great opportunity to improve the knowledge on the scientific and commercial applications of spaceborne hyperspectral data. In addition, we introduce a curve fitting-based procedure for the estimation of column water vapor content of the atmosphere that directly exploits the reflectance data provided by LBAC. Results obtained on four different PRISMA hyperspectral images are presented and discussed.

scholarly journals The Equivalent Thermal Conductivity of the Micro/Nano Scaled Periodic Cubic Frame Silver and Its Thermal Radiation Mechanism Analysis

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4158
Author(s):  
Haiyan Yu ◽  
Haochun Zhang ◽  
Heming Wang ◽  
Dong Zhang
Keyword(s):  
Thermal Conductivity ◽  
Thermal Radiation ◽  
Cell Size ◽  
Near Infrared ◽  
High Porosity ◽  
Mechanism Analysis ◽  
Infrared Band ◽  
Spectral Radiation ◽  
Radiation Mechanism ◽  
Equivalent Thermal Conductivity

Currently, there are few studies on the influence of microscale thermal radiation on the equivalent thermal conductivity of microscale porous metal. Therefore, this paper calculated the equivalent thermal conductivity of high-porosity periodic cubic silver frame structures with cell size from 100 nm to 100 µm by using the microscale radiation method. Then, the media radiation characteristics, absorptivity, reflectivity and transmissivity were discussed to explain the phenomenon of the radiative thermal conductivity changes. Furthermore, combined with spectral radiation properties at the different cross-sections and wavelength, the radiative transmission mechanism inside high-porosity periodic cubic frame silver structures was obtained. The results showed that the smaller the cell size, the greater radiative contribution in total equivalent thermal conductivity. Periodic cubic silver frames fluctuate more in the visible band and have better thermal radiation modulation properties in the near infrared band, which is formed by the Surface Plasmon Polariton and Magnetic Polaritons resonance jointly. This work provides design guidance for the application of this kind of periodic microporous metal in the field of thermal utilization and management.

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