Spectral reflectance of sea foam in the visible and near-infrared: In situ measurements and remote sensing implications

1996 ◽  
Vol 101 (C6) ◽  
pp. 14361-14371 ◽  
Author(s):  
Robert Frouin ◽  
Myriam Schwindling ◽  
Pierre-Yves Deschamps
Keyword(s):  
Remote Sensing ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
In Situ Measurements

A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards

2019 ◽  
pp. 271-294 ◽  
Author(s):  
Adam J. Mathews
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Spectral Information ◽  
Digital Cameras ◽  
Individual Bands ◽  
Aerial Vehicle ◽  
Best Fit

This paper explores the use of compact digital cameras to remotely estimate spectral reflectance based on unmanned aerial vehicle imagery. Two digital cameras, one unaltered and one altered, were used to collect four bands of spectral information (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to allow the sensor to be additionally sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and abilities of the cameras were observed. This information along with on-site collected spectral data were used to aid in converting aerial imagery digital numbers to estimates of scaled surface reflectance using the empirical line method. The resulting images were used to create spectrally-consistent orthophotomosaics of a vineyard study site. Individual bands were subsequently validated with in situ spectroradiometer data. Results show that red and NIR bands exhibited the best fit (R2: 0.78 for red; 0.57 for NIR).

A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards

2019 ◽  
pp. 298-322
Author(s):  
Adam J. Mathews
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Spectral Information ◽  
Digital Cameras ◽  
Individual Bands ◽  
Aerial Vehicle ◽  
Best Fit

This paper explores the use of compact digital cameras to remotely estimate spectral reflectance based on unmanned aerial vehicle imagery. Two digital cameras, one unaltered and one altered, were used to collect four bands of spectral information (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to allow the sensor to be additionally sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and abilities of the cameras were observed. This information along with on-site collected spectral data were used to aid in converting aerial imagery digital numbers to estimates of scaled surface reflectance using the empirical line method. The resulting images were used to create spectrally-consistent orthophotomosaics of a vineyard study site. Individual bands were subsequently validated with in situ spectroradiometer data. Results show that red and NIR bands exhibited the best fit (R2: 0.78 for red; 0.57 for NIR).

Particulate matter variability in Kathmandu based on in-situ measurements, remote sensing, and reanalysis data

2021 ◽  
pp. 105623
Author(s):  
Stefan Becker ◽  
Ramesh Prasad Sapkota ◽  
Binod Pokharel ◽  
Loknath Adhikari ◽  
Rudra Prasad Pokhrel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Reanalysis Data ◽  
In Situ Measurements

scholarly journals Aerosol optical and microphysical retrievals from a hybrid multiwavelength lidar data set – DISCOVER-AQ 2011

2014 ◽  
Vol 7 (9) ◽  
pp. 3095-3112 ◽  
Author(s):  
P. Sawamura ◽  
D. Müller ◽  
R. M. Hoff ◽  
C. A. Hostetler ◽  
R. A. Ferrare ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
Index Of Refraction ◽  
High Spectral Resolution ◽  
Lidar Data ◽  
Data Set ◽  
Microphysical Properties ◽  
Lidar Measurements ◽  
Multiwavelength Lidar

Abstract. Retrievals of aerosol microphysical properties (effective radius, volume and surface-area concentrations) and aerosol optical properties (complex index of refraction and single-scattering albedo) were obtained from a hybrid multiwavelength lidar data set for the first time. In July 2011, in the Baltimore–Washington DC region, synergistic profiling of optical and microphysical properties of aerosols with both airborne (in situ and remote sensing) and ground-based remote sensing systems was performed during the first deployment of DISCOVER-AQ. The hybrid multiwavelength lidar data set combines ground-based elastic backscatter lidar measurements at 355 nm with airborne High-Spectral-Resolution Lidar (HSRL) measurements at 532 nm and elastic backscatter lidar measurements at 1064 nm that were obtained less than 5 km apart from each other. This was the first study in which optical and microphysical retrievals from lidar were obtained during the day and directly compared to AERONET and in situ measurements for 11 cases. Good agreement was observed between lidar and AERONET retrievals. Larger discrepancies were observed between lidar retrievals and in situ measurements obtained by the aircraft and aerosol hygroscopic effects are believed to be the main factor in such discrepancies.

scholarly journals The Ship Detection Using Airborne and In-situ Measurements Based on Hyperspectral Remote Sensing

2017 ◽  
Vol 38 (7) ◽  
pp. 535-545 ◽  
Author(s):  
Jae-Jin Park ◽  
◽  
Sangwoo Oh ◽  
Kyung-Ae Park ◽  
Pierre-Yves Foucher ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
In Situ Measurements ◽  
Ship Detection

scholarly journals ESTIMATION OF SURFACE SNOW WETNESS USING SENTINEL-2 MULTISPECTRAL DATA

2018 ◽  
Vol IV-5 ◽  
pp. 223-228 ◽  
Author(s):  
D. Varade ◽  
O. Dikshit
Keyword(s):  
Remote Sensing ◽  
Water Resource Management ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Physical Relationship ◽  
Sensing Data ◽  
Surface Snow ◽  
Sentinel 2

<p><strong>Abstract.</strong> Snow cover characterization and estimation of snow geophysical parameters is a significant area of research in water resource management and surface hydrological processes. With advances in spaceborne remote sensing, much progress has been achieved in the qualitative and quantitative characterization of snow geophysical parameters. However, most of the methods available in the literature are based on the microwave backscatter response of snow. These methods are mostly based on the remote sensing data available from active microwave sensors. Moreover, in alpine terrains, such as in the Himalayas, due to the geometrical distortions, the missing data is significant in the active microwave remote sensing data. In this paper, we present a methodology utilizing the multispectral observations of Sentinel-2 satellite for the estimation of surface snow wetness. The proposed approach is based on the popular triangle method which is significantly utilized for the assessment of soil moisture. In this case, we develop a triangular feature space using the near infrared (NIR) reflectance and the normalized differenced snow index (NDSI). Based on the assumption that the NIR reflectance is linearly related to the liquid water content in the snow, we derive a physical relationship for the estimation of snow wetness. The modeled estimates of snow wetness from the proposed approach were compared with in-situ measurements of surface snow wetness. A high correlation determined by the coefficient of determination of 0.94 and an error of 0.535 was observed between the proposed estimates of snow wetness and in-situ measurements.</p>

scholarly journals Validation of aerosol backscatter profiles from Raman lidar and ceilometer using balloon-borne measurements

2021 ◽  
Vol 21 (3) ◽  
pp. 2267-2285
Author(s):  
Simone Brunamonti ◽  
Giovanni Martucci ◽  
Gonzague Romanens ◽  
Yann Poltera ◽  
Frank G. Wienhold ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
Aerosol Size Distribution ◽  
Spatial And Temporal Variability ◽  
Raman Lidar ◽  
Backscatter Coefficient ◽  
Custom Made ◽  
Aerosol Backscatter ◽  
Good Agreement

Abstract. Remote-sensing measurements by light detection and ranging (lidar) instruments are fundamental for the monitoring of altitude-resolved aerosol optical properties. Here we validate vertical profiles of aerosol backscatter coefficient (βaer) measured by two independent lidar systems using co-located balloon-borne measurements performed by Compact Optical Backscatter Aerosol Detector (COBALD) sondes. COBALD provides high-precision in situ measurements of βaer at two wavelengths (455 and 940 nm). The two analyzed lidar systems are the research Raman Lidar for Meteorological Observations (RALMO) and the commercial CHM15K ceilometer (Lufft, Germany). We consider in total 17 RALMO and 31 CHM15K profiles, co-located with simultaneous COBALD soundings performed throughout the years 2014–2019 at the MeteoSwiss observatory of Payerne (Switzerland). The RALMO (355 nm) and CHM15K (1064 nm) measurements are converted to 455 and 940 nm, respectively, using the Ångström exponent profiles retrieved from COBALD data. To account for the different receiver field-of-view (FOV) angles between the two lidars (0.01–0.02∘) and COBALD (6∘), we derive a custom-made correction using Mie-theory scattering simulations. Our analysis shows that both lidar instruments achieve on average a good agreement with COBALD measurements in the boundary layer and free troposphere, up to 6 km altitude. For medium-high-aerosol-content measurements at altitudes below 3 km, the mean ± standard deviation difference in βaer calculated from all considered soundings is −2 % ± 37 % (−0.018 ± 0.237 Mm−1 sr−1 at 455 nm) for RALMO−COBALD and +5 % ± 43 % (+0.009 ± 0.185 Mm−1 sr−1 at 940 mm) for CHM15K−COBALD. Above 3 km altitude, absolute deviations generally decrease, while relative deviations increase due to the prevalence of air masses with low aerosol content. Uncertainties related to the FOV correction and spatial- and temporal-variability effects (associated with the balloon's drift with altitude and different integration times) contribute to the large standard deviations observed at low altitudes. The lack of information on the aerosol size distribution and the high atmospheric variability prevent an accurate quantification of these effects. Nevertheless, the excellent agreement observed in individual profiles, including fine and complex structures in the βaer vertical distribution, shows that under optimal conditions, the discrepancies with the in situ measurements are typically comparable to the estimated statistical uncertainties in the remote-sensing measurements. Therefore, we conclude that βaer profiles measured by the RALMO and CHM15K lidar systems are in good agreement with in situ measurements by COBALD sondes up to 6 km altitude.

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