scholarly journals Factors that influence surface PM<sub>2.5</sub> values inferred from satellite observations: perspective gained for the US Baltimore–Washington metropolitan area during DISCOVER-AQ

2014 ◽  
Vol 14 (4) ◽  
pp. 2139-2153 ◽  
Author(s):  
S. Crumeyrolle ◽  
G. Chen ◽  
L. Ziemba ◽  
A. Beyersdorf ◽  
L. Thornhill ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Metropolitan Area ◽  
Scattering Coefficient ◽  
Data Set ◽  
Ambient Relative Humidity ◽  
Microphysical Properties ◽  
The Us ◽  
Dry Conditions ◽  
The Impact

Abstract. During the NASA DISCOVER-AQ campaign over the US Baltimore, MD–Washington, D.C., metropolitan area in July 2011, the NASA P-3B aircraft performed extensive profiling of aerosol optical, chemical, and microphysical properties. These in situ profiles were coincident with ground-based remote sensing (AERONET) and in situ (PM2.5) measurements. Here, we use this data set to study the correlation between the PM2.5 observations at the surface and the column integrated measurements. Aerosol optical depth (AOD550 nm) calculated with the extinction (550 nm) measured during the in situ profiles was found to be strongly correlated with the volume of aerosols present in the boundary layer (BL). Despite the strong correlation, some variability remains, and we find that the presence of aerosol layers above the BL (in the buffer layer – BuL) introduces significant uncertainties in PM2.5 estimates based on column-integrated measurements (overestimation of PM2.5 by a factor of 5). This suggests that the use of active remote sensing techniques would dramatically improve air quality retrievals. Indeed, the relationship between the AOD550 nm and the PM2.5 is strongly improved by accounting for the aerosol present in and above the BL (i.e., integrating the aerosol loading from the surface to the top of the BuL). Since more than 15% of the AOD values observed during DISCOVER-AQ are dominated by aerosol water uptake, the f(RH)amb (ratio of scattering coefficient at ambient relative humidity (RH) to scattering coefficient at low RH; see Sect. 3.2) is used to study the impact of the aerosol hygroscopicity on the PM2.5 retrievals. The results indicate that PM2.5 can be predicted within a factor up to 2 even when the vertical variability of the f(RH)amb is assumed to be negligible. Moreover, f(RH = 80%) and RH measurements performed at the ground may be used to estimate the f(RH)amb during dry conditions (RHBL < 55%).

scholarly journals Factors that influence surface PM2.5 values inferred from satellite observations: perspective gained for the Baltimore-Washington Area during DISCOVER-AQ

2013 ◽  
Vol 13 (9) ◽  
pp. 23421-23459 ◽  
Author(s):  
S. Crumeyrolle ◽  
G. Chen ◽  
L. Ziemba ◽  
A. Beyersdorf ◽  
L. Thornhill ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Metropolitan Region ◽  
Strongly Correlated ◽  
Data Set ◽  
Microphysical Properties ◽  
Remote Sensing Techniques ◽  
The Impact ◽  
Aerosol Hygroscopicity ◽  
532 Nm

Abstract. During the NASA DISCOVER-AQ campaign over the Washington D.C., - Baltimore, MD, metropolitan region in July 2011, the NASA P-3B aircraft performed extensive profiling of aerosol optical, chemical, and microphysical properties. These in-situ profiles were coincident with ground based remote sensing (AERONET) and in-situ (PM2.5) measurements. Here, we use this data set to study the correlation between the PM2.5 observations at the surface and the column integrated measurements. Aerosol optical depth (AOD) calculated with the extinction (532 nm) measured during the in-situ profiles was found to be strongly correlated with the volume of aerosols present in the boundary layer (BL). Despite the strong correlation, some variability remains, and we find that the presence of aerosol layers above the BL (in the buffer layer – BuL) introduces a significant uncertainties in PM2.5 estimates based on column-integrated measurements. This motivates the use of active remote sensing techniques to dramatically improve air quality retrievals. Since more than a quarter of the AOD values observed during DISCOVER-AQ are dominated by aerosol water uptake, the f(RH)amb (obtained from two nephelometers at different relative humidities – RHs) is used to study the impact of the aerosol hygroscopicity. The results indicate that PM2.5 can be predicted within a factor of 1.6 even when the vertical variability of the f(RH)amb is assumed to be negligible.

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 A comparative study of aerosol microphysical properties retrieved from ground-based remote sensing and aircraft in situ measurements during a Saharan dust event

2016 ◽  
Vol 9 (3) ◽  
pp. 1113-1133 ◽  
Author(s):  
María José Granados-Muñoz ◽  
Juan Antonio Bravo-Aranda ◽  
Darrel Baumgardner ◽  
Juan Luis Guerrero-Rascado ◽  
Daniel Pérez-Ramírez ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Volume Concentration ◽  
Mineral Dust ◽  
In Situ Measurements ◽  
Published Data ◽  
Dust Event ◽  
Data Set ◽  
Passive Remote Sensing ◽  
Microphysical Properties

Abstract. In this work we present an analysis of aerosol microphysical properties during a mineral dust event taking advantage of the combination of different state-of-the-art retrieval techniques applied to active and passive remote sensing measurements and the evaluation of some of those techniques using independent data acquired from in situ aircraft measurements. Data were collected in a field campaign performed during a mineral dust outbreak at the Granada, Spain, experimental site (37.16° N, 3.61° W, 680 m a.s.l.) on 27 June 2011. Column-integrated properties are provided by sun- and star-photometry, which allows for a continuous evaluation of the mineral dust optical properties during both day and nighttime. Both the linear estimation and AERONET (Aerosol Robotic Network) inversion algorithms are applied for the retrieval of the column-integrated microphysical particle properties. In addition, vertically resolved microphysical properties are obtained from a multi-wavelength Raman lidar system included in EARLINET (European Aerosol Research Lidar Network), by using both LIRIC (Lidar Radiometer Inversion Code) algorithm during daytime and an algorithm applied to the Raman measurements based on the regularization technique during nighttime. LIRIC retrievals reveal the presence of dust layers between 3 and 5 km a.s.l. with volume concentrations of the coarse spheroid mode up to 60 µm3 cm−3. The combined use of the regularization and LIRIC methods reveals the night-to-day evolution of the vertical structure of the mineral dust microphysical properties and offers complementary information to that from column-integrated variables retrieved from passive remote sensing. Additionally, lidar depolarization profiles and LIRIC retrieved volume concentration are compared with aircraft in situ measurements. This study presents for the first time a comparison of the total volume concentration retrieved with LIRIC with independent in situ measurements, obtaining agreement within the estimated uncertainties for both methods and quite good agreement for the vertical distribution of the aerosol layers. Regarding the depolarization, the first published data set of the CAS-POL for polarization ratios is presented here and qualitatively compared with the lidar technique.

Ground-based Remote Sensing of Cirrus Clouds

Cirrus ◽  
2002 ◽  
Author(s):  
Kenneth Sassen ◽  
Gerald Mace
Keyword(s):  
Remote Sensing ◽  
Multispectral Imaging ◽  
Cirrus Clouds ◽  
Radiative Energy ◽  
Radiation Balance ◽  
Cirrus Cloud ◽  
Microphysical Properties ◽  
Research Aircraft ◽  
Cloud Modeling

Cirrus clouds have only recently been recognized as having a significant influence on weather and climate through their impact on the radiative energy budget of the atmosphere. In addition, the unique difficulties presented by the study of cirrus put them on the “back burner” of atmospheric research for much of the twentieth century. Foremost, because they inhabit the frigid upper troposphere, their inaccessibility has hampered intensive research. Other factors have included a lack of in situ instrumentation to effectively sample the clouds and environment, and basic uncertainties in the underlying physics of ice cloud formation, growth, and maintenance. Cloud systems that produced precipitation, severe weather, or hazards to aviation were deemed more worthy of research support until the mid- 1980s. Beginning at this time, however, major field research programs such as the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE; Cox et al. 1987), International Cirrus Experiment (ICE; Raschke et al. 1990), Experimental Cloud Lidar Pilot Study (ECLIPS; Platt et al. 1994), and the Atmospheric Radiation Measurement (ARM) Program (Stokes and Schwartz 1994) have concentrated on cirrus cloud research, relying heavily on ground-based remote sensing observations combined with research aircraft. What has caused this change in research emphasis is an appreciation for the potentially significant role that cirrus play in maintaining the radiation balance of the earth-atmosphere system (Liou 1986). As climate change issues were treated more seriously, it was recognized that the effects, or feedbacks, of extensive high-level ice clouds in response to global warming could be pivotal. This fortunately came at a time when new generations of meteorological instrumentation were becoming available. Beginning in the early 1970s, major advancements were made in the fields of numerical cloud modeling and cloud measurements using aircraft probes, satellite multispectral imaging, and remote sensing with lidar, short-wavelength radar, and radiometers, all greatly facilitating cirrus research. Each of these experimental approaches have their advantages and drawbacks, and it should also be noted that a successful cloud modeling effort relies on field data for establishing boundary conditions and providing case studies for validation. Although the technologies created for in situ aircraft measurements can clearly provide unique knowledge of cirrus cloud thermodynamic and microphysical properties (Dowling and Radke 1990), available probes may suffer from limitations in their response to the wide range of cirrus particles and actually sample a rather small volume of cloud during any mission.

scholarly journals Comparing the cloud vertical structure derived from several methods based on radiosonde profiles and ground-based remote sensing measurements

2014 ◽  
Vol 7 (8) ◽  
pp. 2757-2773 ◽  
Author(s):  
M. Costa-Surós ◽  
J. Calbó ◽  
J. A. González ◽  
C. N. Long
Keyword(s):  
Remote Sensing ◽  
Vertical Structure ◽  
Cloud Layer ◽  
Cloud Base ◽  
Low Resolution ◽  
Telecommunication System ◽  
Perfect Agreement ◽  
Data Set ◽  
Global Telecommunication System ◽  
The Impact

Abstract. The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64%; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41%. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67% (plus 25% of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

scholarly journals Retrieving Total and Inorganic Suspended Sediments in Amazon Floodplain Lakes: A Multisensor Approach

2019 ◽  
Vol 11 (15) ◽  
pp. 1744 ◽  
Author(s):  
Daniel Maciel ◽  
Evlyn Novo ◽  
Lino Sander de Carvalho ◽  
Cláudio Barbosa ◽  
Rogério Flores Júnior ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Correction ◽  
Suspended Sediments ◽  
Floodplain Lakes ◽  
Empirical Modeling ◽  
Landsat 8 ◽  
Amazon Floodplain ◽  
The Impact ◽  
Sentinel 2

Remote sensing imagery are fundamental to increasing the knowledge about sediment dynamics in the middle-lower Amazon floodplains. Moreover, they can help to understand both how climate change and how land use and land cover changes impact the sediment exchange between the Amazon River and floodplain lakes in this important and complex ecosystem. This study investigates the suitability of Landsat-8 and Sentinel-2 spectral characteristics in retrieving total (TSS) and inorganic (TSI) suspended sediments on a set of Amazon floodplain lakes in the middle-lower Amazon basin using in situ Remote Sensing Reflectance (Rrs) measurements to simulate Landsat 8/OLI (Operational Land Imager) and Sentinel 2/MSI (Multispectral Instrument) bands and to calibrate/validate several TSS and TSI empirical algorithms. The calibration was based on the Monte Carlo Simulation carried out for the following datasets: (1) All-Dataset, consisting of all the data acquired during four field campaigns at five lakes spread over the lower Amazon floodplain (n = 94); (2) Campaign-Dataset including samples acquired in a specific hydrograph phase (season) in all lakes. As sample size varied from one season to the other, n varied from 18 to 31; (3) Lake-Dataset including samples acquired in all seasons at a given lake with n also varying from 17 to 67 for each lake. The calibrated models were, then, applied to OLI and MSI scenes acquired in August 2017. The performance of three atmospheric correction algorithms was also assessed for both OLI (6S, ACOLITE, and L8SR) and MSI (6S, ACOLITE, and Sen2Cor) images. The impact of glint correction on atmosphere-corrected image performance was assessed against in situ glint-corrected Rrs measurements. After glint correction, the L8SR and 6S atmospheric correction performed better with the OLI and MSI sensors, respectively (Mean Absolute Percentage Error (MAPE) = 16.68% and 14.38%) considering the entire set of bands. However, for a given single band, different methods have different performances. The validated TSI and TSS satellite estimates showed that both in situ TSI and TSS algorithms provided reliable estimates, having the best results for the green OLI band (561 nm) and MSI red-edge band (705 nm) (MAPE < 21%). Moreover, the findings indicate that the OLI and MSI models provided similar errors, which support the use of both sensors as a virtual constellation for the TSS and TSI estimate over an Amazon floodplain. These results demonstrate the applicability of the calibration/validation techniques developed for the empirical modeling of suspended sediments in lower Amazon floodplain lakes using medium-resolution sensors.

scholarly journals Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France)

2017 ◽  
Vol 21 (11) ◽  
pp. 5693-5708 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Tiphaine Tallec ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

Atmospheric satellite-based and in situ surface observations on summertime trace gases (CO, CO2, CH4) over the metropolitan area of Bucharest

2020 ◽  
Author(s):  
Marius-Paul Corbu ◽  
Andreea Calcan ◽  
Ioana Vizireanu ◽  
Denisa Elena Moaca ◽  
Robert-Valentin Chiritescu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Metropolitan Area ◽  
Financial Support ◽  
Trace Gases ◽  
Air Pollutant ◽  
Data Set ◽  
Air Mass ◽  
Synoptic Conditions

&lt;p&gt;Although anthropogenic emissions of trace gases have decreased over the last decades in Europe, strong additional reductions are required to reach the goals of the Paris climate agreements. In addition, air pollution is an issue of great concern for the inhabitants of the metropolitan area of Bucharest, as the local air quality is often poor. The rapid development of the city, increased traffic volume from a mixed vehicle fleet (different technologies and fuels), and other factors are strong contributors of emissions of greenhouse gases and air pollutants in Bucharest.&lt;/p&gt;&lt;p&gt;The goal of this research was the assessment of CO, CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; concentrations in Bucharest, identification of potential emissions hotspots and their causes (anthropogenic or natural/biogenic, local or distant) and determination of the background values.&lt;/p&gt;&lt;p&gt;Measurements were performed in summer 2019 in four districts of Bucharest covering about two thirds of the metropolitan area during the Romanian Methane Emissions from Oil&amp;gas (ROMEO) campaign with high resolution (1 sec). These data sets were complemented with satellite observations of CO and CH&lt;sub&gt;4&lt;/sub&gt; from Copernicus Sentinel-5P at a resolution of 7 km&lt;sup&gt;2&lt;/sup&gt;.&lt;/p&gt;&lt;p&gt;Hourly meteorological data, temperature, relative humidity, wind speed and direction, and atmospheric pressure were added to the air pollutant data set because synoptic conditions can strongly influence the levels of pollution. Air mass origins were investigated by computing backward air mass trajectories using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model for 72 hours back.&lt;/p&gt;&lt;p&gt;Points of high concentrations of CO, CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; near the surface were identified which are, most likely, linked to local anthropogenic activities in the nearby surroundings. We identified a variation of concentrations of CO from 0.01 to 101 ppm, of CO&lt;sub&gt;2&lt;/sub&gt; from 388 to 6556 ppm, and of CH&lt;sub&gt;4&lt;/sub&gt; from 1.89 to 246 ppm, while background levels are as follows: 0.071&amp;#177;0.042 ppm CO, 392.68&amp;#177;3.01 ppm CO&lt;sub&gt;2&lt;/sub&gt;, and 1.93&amp;#177;0.016 ppm CH&lt;sub&gt;4&lt;/sub&gt;.&lt;/p&gt;&lt;p&gt;Results of our study provide an up to date quantitative image of CO, CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; hotspots in the Bucharest area, which is important for modeling air quality and may also help to improve the relationships between column integrated air pollution data with in situ ground observations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgement:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;This research is supported by ROMEO project, developed under UNEP&amp;#8217;s financial support PCA/CCAC/UU/DTIE19-EN652. Partial financial support from UB198/Int project is also acknowledged.&lt;/p&gt;&lt;p&gt;The authors acknowledge the free use of tropospheric CO and CH&lt;sub&gt;4&lt;/sub&gt; column data from TROPOMI (Sentinel-5P) sensor from https://s5phub.copernicus.eu and the NOAA Air Resources Laboratory for the provision of the HYSPLIT transport model available at READY website https://www.ready.noaa.gov&lt;/p&gt;&lt;p&gt;Special thanks to all INCAS technical staff for their support in performing the campaigns.&lt;/p&gt;

scholarly journals Information – based uncertainty decomposition in dual channel microwave remote sensing of soil moisture

2020 ◽  
Author(s):  
Bonan Li ◽  
Stephen P. Good
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Mutual Information ◽  
Microwave Remote Sensing ◽  
Reference Network ◽  
Brightness Temperatures ◽  
Dual Channel ◽  
The Us ◽  
In Situ Observations

Abstract. NASA's Soil Moisture Active-Passive (SMAP) mission characterizes global spatiotemporal patterns in surface soil moisture using dual L-band microwave retrievals of horizontal, TBh, and vertical, TBv, polarized microwave brightness temperatures through a modeled relationship between vegetation opacity and surface scattering albedo (i.e. tau-omega model). Although this model has been validated against in situ soil moisture measurements across sparse validations sites, there is lack of systematic characterization of where and why SMAP estimates deviate from the in situ observations. Here, soil moisture observations from the US Climate Reference Network are used within a mutual information framework to decompose the overall retrieval uncertainty from SMAPs Modified Dual Channel Algorithm (MDCA) into random uncertainty derived from raw data itself and model uncertainty derived from the model’s inherent structure. The results shown that, on average, 12 % of the uncertainty in SMAP soil moisture estimates is caused by the loss of information in the MDCA model itself while the remainder is induced by inadequacy of TBh and TBv observations. We find the fraction of algorithm induced uncertainty is negatively correlated (pearson r of −0.48) with correlations between in-situ observations and MDCA estimates. A decomposition of mutual information between TBh, TBv and MDCA soil moisture shows that on average 55 % of the mutual information is redundantly shared by TBh and TBv, while the information provided uniquely from both TBh and TBv is 15 %. The fraction of information redundantly provided by TBh and TBv was found to be tightly correlated (pearson r = −0.7) to how well the MDCA output correlated to in situ observations. Thus, MDCA overall quality improves as TBh and TBv provide more redundant information for the MDCA. This suggests the informational redundancy between these remotely sensed observations can be used as independent metric to assess the overall quality of algorithms using these data streams. This study provides a baseline approach that can also be applied to evaluate other remote sensing models and understand informational loss as satellite retrievals are translated to end user products.

scholarly journals Social Media Applied to Tourism and Hospitality

2020 ◽  
pp. 270-294 ◽  
Author(s):  
Luís Pacheco ◽  
Fernando Moreira
Keyword(s):  
Social Media ◽  
Metropolitan Area ◽  
Secondary Data ◽  
Social Knowledge ◽  
Data Set ◽  
Consumer Reviews ◽  
Social Media Tools ◽  
Tourism And Hospitality ◽  
Online Travel ◽  
The Impact

Online hotel reviews, ratings, or opinions have gained importance with the growth of social media tools. The objective of this chapter is to study the impact of specific satisfaction attributes on overall satisfaction. It is used a secondary data set obtained from three of the most influential online travel platforms, being analyzed the guests' average ratings for around 130 hotel units, distributed by four quality segments, located in the Porto metropolitan area. The application of this methodology to a large sample of Portuguese hotels has not been done before, been that the main contribution of this study. It is evidenced that the different platforms, while all incorporating consumer reviews as primary social knowledge, are distinct from each other on some aspects. The three platforms present roughly the same supply of hotels, albeit presenting some differences in terms of volume of data. In terms of specific attributes, with the exception of “service,” the three platforms present significant differences that may reflect the different user bases on these platforms.

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