It is commonly said that the global environment structure is formed from the atmosphere, hydrosphere, geosphere, and biosphere, which are natural environment systems. In addition to this, we add another system “livingsphere” which is an artificial system, but holds strong relations between the daily lives of humans and the natural systems. It would then be appropriate to consider the global environment structure with the idea that natural systems and the artificial one are interconnected. We propose using fluorescence as a common parameter to understand the interconnection. Since a large variety of substances exhibit their own unique auto-fluorescence spectrum more or less if they are irradiated by light, they are good targets for fluorescence lidars. Lidar observation results about substances moving freely among the systems might offer information about the interconnection of each type of environment system. In this presentation, we show several experiments done using the fluorescence lidar we have developed for observing aerosol in the atmosphere, lake/river water quality in the hydrosphere, vegetation growth status in the biosphere, and pre-observing ground surface substances in the geosphere and waste substances of daily necessities in the livingsphere. We also describe a fluorescence database which is an EEM (Excitation-Emission-Matrix) of substances found elsewhere in the systems, and discuss an adaptation of the database to the atmospheric aerosols observation done by the fluorescence lidar.
{"title":"A fluorescence lidar for seamlessly connecting individual observations of the global environmental systems","authors":"Y. Saito, T. Tomida, K. Shiraishi","doi":"10.1117/12.2324428","DOIUrl":"https://doi.org/10.1117/12.2324428","url":null,"abstract":"It is commonly said that the global environment structure is formed from the atmosphere, hydrosphere, geosphere, and biosphere, which are natural environment systems. In addition to this, we add another system “livingsphere” which is an artificial system, but holds strong relations between the daily lives of humans and the natural systems. It would then be appropriate to consider the global environment structure with the idea that natural systems and the artificial one are interconnected. We propose using fluorescence as a common parameter to understand the interconnection. Since a large variety of substances exhibit their own unique auto-fluorescence spectrum more or less if they are irradiated by light, they are good targets for fluorescence lidars. Lidar observation results about substances moving freely among the systems might offer information about the interconnection of each type of environment system. In this presentation, we show several experiments done using the fluorescence lidar we have developed for observing aerosol in the atmosphere, lake/river water quality in the hydrosphere, vegetation growth status in the biosphere, and pre-observing ground surface substances in the geosphere and waste substances of daily necessities in the livingsphere. We also describe a fluorescence database which is an EEM (Excitation-Emission-Matrix) of substances found elsewhere in the systems, and discuss an adaptation of the database to the atmospheric aerosols observation done by the fluorescence lidar.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"20 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131472438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
MODIS chlorophyll-a concentration (chla), sea surface temperature (SST), and photosynthetically active radiation (PAR) were used to perform a geographically weighted regression (GWR) analysis within a 150-km buffer of the Brazilian coast. The correlation was between chla as the regressed variable and SST or PAR as the predictors. Both a GWR and a Bayesian GWR (BGWR) were used for evaluating the variables. Colored matrices were plotted for displaying beta values, significance, residuals, and t-statistics. Coefficients of determination (R2) were computed for all months. Also, the ratio of the GWR beta estimates and the 95% confidence interval BGWR estimates was computed. Results showed overall better R2 for SST than for PAR regression but also better beta estimates for PAR than for SST in relation to BGWR beta significance range. Northern regions of the Brazilian coast exhibited lower statistical significance. July had lowest GWR beta values and best significance, January highest beta values and worst significance, and April and October highly variable results.
{"title":"Geostatistical approach for meteo-oceanographic variables evaluation at the Brazilian coast","authors":"Diogo J. Amore, M. Kampel, R. Frouin","doi":"10.1117/12.2500574","DOIUrl":"https://doi.org/10.1117/12.2500574","url":null,"abstract":"MODIS chlorophyll-a concentration (chla), sea surface temperature (SST), and photosynthetically active radiation (PAR) were used to perform a geographically weighted regression (GWR) analysis within a 150-km buffer of the Brazilian coast. The correlation was between chla as the regressed variable and SST or PAR as the predictors. Both a GWR and a Bayesian GWR (BGWR) were used for evaluating the variables. Colored matrices were plotted for displaying beta values, significance, residuals, and t-statistics. Coefficients of determination (R2) were computed for all months. Also, the ratio of the GWR beta estimates and the 95% confidence interval BGWR estimates was computed. Results showed overall better R2 for SST than for PAR regression but also better beta estimates for PAR than for SST in relation to BGWR beta significance range. Northern regions of the Brazilian coast exhibited lower statistical significance. July had lowest GWR beta values and best significance, January highest beta values and worst significance, and April and October highly variable results.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127906647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Algorithms to retrieve ocean color from space, deterministic or statistical, often use a simplified water reflectance model, specified by a few parameters (e.g., chlorophyll concentration, backscattering and absorption coefficients at a given wavelength). The model, however, may not be representative of the worldwide ocean conditions, since many variables affecting reflectance are fixed at some average values. In this context, the semi-analytical model of Park and Ruddick (2005), PR05, used in the spectral matching POLYMER algorithm (Steinmetz et al., 2011), is examined in terms of its ability to represent properly water reflectance. The PR05 model depends on chlorophyll-a concentration, a parameter specifying the contribution of algal and non-algal particles to the backscattering coefficient, and a parameter allowing different absorption coefficients for dissolved organic matter. Model estimates at MODIS wavelengths, obtained for a representative set of Case 1 and Case 2 waters, are compared with Hydrolight calculations that include fluorescence and Raman scattering and AERONET-OC measurements. The accuracy of retrieving inherent optical properties (IOPs) using the reconstructed reflectance is also evaluated. The model parameters that give the best fit with the simulated data are determined. Agreement is generally good between the two- or three-parameter model results and Hydrolight/AERONETOC values, even in optically complex waters, with discrepancies much smaller than typical atmospheric correction errors. Significant differences exist in some cases, but having a more intricate model (i.e., using more parameters) might not guarantee convergence of the inversion scheme. The trade-off is between efficiency/robustness and accuracy. Significant errors are observed when using the model estimates to retrieve IOPs. Importantly, the model parameters that best fit the input data, in particular chlorophyll-a concentration, may not represent adequately actual values. The reconstructed water reflectance, not the retrieved model parameters, should be used in bio-optical algorithms.
{"title":"Adequacy of semi-analytical water reflectance models in ocean-color remote sensing","authors":"Jing Tan, R. Frouin, D. Ramon, F. Steinmetz","doi":"10.1117/12.2501677","DOIUrl":"https://doi.org/10.1117/12.2501677","url":null,"abstract":"Algorithms to retrieve ocean color from space, deterministic or statistical, often use a simplified water reflectance model, specified by a few parameters (e.g., chlorophyll concentration, backscattering and absorption coefficients at a given wavelength). The model, however, may not be representative of the worldwide ocean conditions, since many variables affecting reflectance are fixed at some average values. In this context, the semi-analytical model of Park and Ruddick (2005), PR05, used in the spectral matching POLYMER algorithm (Steinmetz et al., 2011), is examined in terms of its ability to represent properly water reflectance. The PR05 model depends on chlorophyll-a concentration, a parameter specifying the contribution of algal and non-algal particles to the backscattering coefficient, and a parameter allowing different absorption coefficients for dissolved organic matter. Model estimates at MODIS wavelengths, obtained for a representative set of Case 1 and Case 2 waters, are compared with Hydrolight calculations that include fluorescence and Raman scattering and AERONET-OC measurements. The accuracy of retrieving inherent optical properties (IOPs) using the reconstructed reflectance is also evaluated. The model parameters that give the best fit with the simulated data are determined. Agreement is generally good between the two- or three-parameter model results and Hydrolight/AERONETOC values, even in optically complex waters, with discrepancies much smaller than typical atmospheric correction errors. Significant differences exist in some cases, but having a more intricate model (i.e., using more parameters) might not guarantee convergence of the inversion scheme. The trade-off is between efficiency/robustness and accuracy. Significant errors are observed when using the model estimates to retrieve IOPs. Importantly, the model parameters that best fit the input data, in particular chlorophyll-a concentration, may not represent adequately actual values. The reconstructed water reflectance, not the retrieved model parameters, should be used in bio-optical algorithms.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124181398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenjing Zhao, Zhenyu Liu, Shuibo Hu, Haibin Ye, Zhuangming Zhao
Remote-sensing of ocean colour has an advantage over any other biological data source for monitoring long-term global changes in phytoplankton biomass, due to its spatial and temporal sampling capabilities. Chlorophyll-a concentration (Chl-a) provide a proxy for phytoplankton biomass. The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat8 satellite, which is a potential tool for ocean color radiometry because it includes narrow band, high signal-to-noise ratios (SNRs) and the addition of a band centered at 443 nm, has competitive advantage in phytoplankton pigment Chl-a estimation compare with previous Landsat instruments. The aim of this work was to evaluate the performance of the standard NASA algorithm OC3 type for Landsat-8 OLI in determining Chl-a concentrations in both turbid estuary and clear open sea waters of the north South China Sea, in which the empirical coefficients were tuned by using field data and used 443-, 561-, and 655nm bands instead of 443-, 482 and 561nm bands. The standard OC3-based algorithm for OLI performed well in the Southeast continental shelf of Hainan Island (HNI). While empirical algorithm should be developed in the Pearl River estuary (PRE), and the comparisons between estimated and in situ measured Chl-a produced R2 reaching 0.88 and APD <30%. Furthermore, we assessed Chl-a products by conducting cross-validation with concurrent MODIS-Aqua and NPP VIIRS data, which demonstrate good consistency and minor deviation in HNI waters, while demonstrate good consistency but large deviation in the PRE waters. Our findings demonstrate the potential of high resolution OLI Chl-a products to study short-lasting events and capture fine-scale features in the marine environment in different cases waters. The OLI Chl-a products using standard OC3-based algorithm performed well in the case I waters, while regional algorithm should be developed basing on large field data in the estuary waters.
{"title":"High-resolution chlorophyll-a ocean color products estimation in turbid estuary and clear open sea waters of the north South China Sea with Landsat-8 OLI","authors":"Wenjing Zhao, Zhenyu Liu, Shuibo Hu, Haibin Ye, Zhuangming Zhao","doi":"10.1117/12.2326773","DOIUrl":"https://doi.org/10.1117/12.2326773","url":null,"abstract":"Remote-sensing of ocean colour has an advantage over any other biological data source for monitoring long-term global changes in phytoplankton biomass, due to its spatial and temporal sampling capabilities. Chlorophyll-a concentration (Chl-a) provide a proxy for phytoplankton biomass. The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat8 satellite, which is a potential tool for ocean color radiometry because it includes narrow band, high signal-to-noise ratios (SNRs) and the addition of a band centered at 443 nm, has competitive advantage in phytoplankton pigment Chl-a estimation compare with previous Landsat instruments. The aim of this work was to evaluate the performance of the standard NASA algorithm OC3 type for Landsat-8 OLI in determining Chl-a concentrations in both turbid estuary and clear open sea waters of the north South China Sea, in which the empirical coefficients were tuned by using field data and used 443-, 561-, and 655nm bands instead of 443-, 482 and 561nm bands. The standard OC3-based algorithm for OLI performed well in the Southeast continental shelf of Hainan Island (HNI). While empirical algorithm should be developed in the Pearl River estuary (PRE), and the comparisons between estimated and in situ measured Chl-a produced R2 reaching 0.88 and APD <30%. Furthermore, we assessed Chl-a products by conducting cross-validation with concurrent MODIS-Aqua and NPP VIIRS data, which demonstrate good consistency and minor deviation in HNI waters, while demonstrate good consistency but large deviation in the PRE waters. Our findings demonstrate the potential of high resolution OLI Chl-a products to study short-lasting events and capture fine-scale features in the marine environment in different cases waters. The OLI Chl-a products using standard OC3-based algorithm performed well in the case I waters, while regional algorithm should be developed basing on large field data in the estuary waters.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126565748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Light Detection And Ranging (LiDAR) is an important branch of remote sensing (RS) technology, and its hardware and software in practical applications are getting more and more mature. Now, it is time for the community to think about its future, and a potential way of further pushing forward LiDAR RS technical progress, no doubt, is to develop its nextgeneration systems and approaches. Hyperspectral LiDAR is such a representative case, which, theoretically, is designed to synchronously collect the spectral and range information of objects. This advantage can inherently handle the errors caused when fusing those corresponding hypespectral images and point clouds in the traditional routines of 4D mapping, and hence, has attracted numerous attention on developing its prototype systems. With the performance enhancements of such prototype systems, more efforts need to be deployed onto pushing these prototypes to practical applications. In the case of the hyperspectral LiDAR prototype system developed by the Finnish Geospatial Research Institute, this study examined its applicability for investigating the intraday 3D variations of tree biophysics and biochemistry. The collected point clouds proved to be able to characterize the biophysical variation of trees in terms of laser point-represented tree geometrical centre. For the aspect of biochemical characterization, the hyperspectral LiDAR was validated through the retrievals of the 3D distributions of the fractions of photosynthetically active radiation (FAPARs), crown chlorophyll concentrations, and crown nitrogen concentrations, and the intraday biochemical variations were characterized by their day-and-night differences. The tests showed that hyperspectral LiDAR will be a kind of technology of high potentials for mapping biophysics and biochemistry and their dynamics.
{"title":"From prototype system to practical application of hyperspectral LiDAR: Investigation of the intraday 3D variations of tree biophysics and biochemistry","authors":"Yi Lin, Miao Jiang","doi":"10.1117/12.2324250","DOIUrl":"https://doi.org/10.1117/12.2324250","url":null,"abstract":"Light Detection And Ranging (LiDAR) is an important branch of remote sensing (RS) technology, and its hardware and software in practical applications are getting more and more mature. Now, it is time for the community to think about its future, and a potential way of further pushing forward LiDAR RS technical progress, no doubt, is to develop its nextgeneration systems and approaches. Hyperspectral LiDAR is such a representative case, which, theoretically, is designed to synchronously collect the spectral and range information of objects. This advantage can inherently handle the errors caused when fusing those corresponding hypespectral images and point clouds in the traditional routines of 4D mapping, and hence, has attracted numerous attention on developing its prototype systems. With the performance enhancements of such prototype systems, more efforts need to be deployed onto pushing these prototypes to practical applications. In the case of the hyperspectral LiDAR prototype system developed by the Finnish Geospatial Research Institute, this study examined its applicability for investigating the intraday 3D variations of tree biophysics and biochemistry. The collected point clouds proved to be able to characterize the biophysical variation of trees in terms of laser point-represented tree geometrical centre. For the aspect of biochemical characterization, the hyperspectral LiDAR was validated through the retrievals of the 3D distributions of the fractions of photosynthetically active radiation (FAPARs), crown chlorophyll concentrations, and crown nitrogen concentrations, and the intraday biochemical variations were characterized by their day-and-night differences. The tests showed that hyperspectral LiDAR will be a kind of technology of high potentials for mapping biophysics and biochemistry and their dynamics.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132966843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrian Diaz Fortich, Victor Dominguez, Yonghua Wu, M. Arend, D. V. Vladutescu, B. Gross, F. Moshary
Attainment of National Ambient Air Quality Standard-NAAQS for exposure limits to air pollutants is of great concern to State and Local agencies and communities in the United State because of potential health impacts. This is particularly important and challenging in urban areas because of high population densities and complex terrain. Exceedances of NAAQS requires states to develop implementation plans to address them and as such, studying the horizontal and vertical distribution and mixing of pollutants is key to understanding their transport and evolution. In this study, vertical and scanning horizontal lidar measurements together with in situ observations from particulate matter and trace gas analyzers from state air quality networks are used to shed light on mechanisms that impact movement of aerosol, including emissions from power generating stations at periods of high electricity demand.
{"title":"Lidar application to monitoring emissions and transport of particulate pollution in urban environments with high temporal and spatial resolution","authors":"Adrian Diaz Fortich, Victor Dominguez, Yonghua Wu, M. Arend, D. V. Vladutescu, B. Gross, F. Moshary","doi":"10.1117/12.2324848","DOIUrl":"https://doi.org/10.1117/12.2324848","url":null,"abstract":"Attainment of National Ambient Air Quality Standard-NAAQS for exposure limits to air pollutants is of great concern to State and Local agencies and communities in the United State because of potential health impacts. This is particularly important and challenging in urban areas because of high population densities and complex terrain. Exceedances of NAAQS requires states to develop implementation plans to address them and as such, studying the horizontal and vertical distribution and mixing of pollutants is key to understanding their transport and evolution. In this study, vertical and scanning horizontal lidar measurements together with in situ observations from particulate matter and trace gas analyzers from state air quality networks are used to shed light on mechanisms that impact movement of aerosol, including emissions from power generating stations at periods of high electricity demand.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123884470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Frouin, Jing Tan, D. Ramon, B. Franz, H. Murakami
The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) in Lagrange-1 (L1) orbit provides observations of the Earth’s surface lit by the Sun at a cadence of 13 to 22 images/day and optical resolution of 16 km in 10 spectral bands from 317 to 780 nm. The EPIC data collected in the bands centered on 443, 551, and 680 nm are used to estimate daily mean photosynthetically available radiation (PAR) reaching the surface of the global, ice-free oceans. The solar irradiance reaching the surface is obtained by subtracting from the extraterrestrial irradiance (known), the irradiance reflected to space (estimated from the EPIC measurements), while taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished, i.e., the methodology is adapted to the relatively large EPIC pixels. A first daily mean EPIC PAR imagery is generated. Comparison with estimates from sensors in polar and geostationary orbits, namely MODIS and AHI, shows good agreement, with coefficients of determination of 0.79 and 0.92 and RMS differences of 8.2 and 5.7 E/m2/d, respectively, but overestimation by 1.08 E/m2/d (MODIS) and 3.44 E/m2/d (AHI). The advantages of using observations from L1 orbit are: 1) the daily cycle of cloudiness is well described (unlike from polar orbit) and 2) spatial resolution is not significantly degraded at high latitudes (unlike from geostationary orbit). The methodology can be easily extended to estimate ultraviolet (UV) surface irradiance using the spectral bands centered on 317, 325, 340, and 388 nm, all the more as ozone content, a key variable controlling atmospheric transmittance, is retrieved from the measurements.
{"title":"Estimating photosynthetically available radiation at the ocean surface from EPIC/DSCOVR data","authors":"R. Frouin, Jing Tan, D. Ramon, B. Franz, H. Murakami","doi":"10.1117/12.2501675","DOIUrl":"https://doi.org/10.1117/12.2501675","url":null,"abstract":"The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) in Lagrange-1 (L1) orbit provides observations of the Earth’s surface lit by the Sun at a cadence of 13 to 22 images/day and optical resolution of 16 km in 10 spectral bands from 317 to 780 nm. The EPIC data collected in the bands centered on 443, 551, and 680 nm are used to estimate daily mean photosynthetically available radiation (PAR) reaching the surface of the global, ice-free oceans. The solar irradiance reaching the surface is obtained by subtracting from the extraterrestrial irradiance (known), the irradiance reflected to space (estimated from the EPIC measurements), while taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished, i.e., the methodology is adapted to the relatively large EPIC pixels. A first daily mean EPIC PAR imagery is generated. Comparison with estimates from sensors in polar and geostationary orbits, namely MODIS and AHI, shows good agreement, with coefficients of determination of 0.79 and 0.92 and RMS differences of 8.2 and 5.7 E/m2/d, respectively, but overestimation by 1.08 E/m2/d (MODIS) and 3.44 E/m2/d (AHI). The advantages of using observations from L1 orbit are: 1) the daily cycle of cloudiness is well described (unlike from polar orbit) and 2) spatial resolution is not significantly degraded at high latitudes (unlike from geostationary orbit). The methodology can be easily extended to estimate ultraviolet (UV) surface irradiance using the spectral bands centered on 317, 325, 340, and 388 nm, all the more as ozone content, a key variable controlling atmospheric transmittance, is retrieved from the measurements.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124060257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Microwave instrumentation is particularly well suited for implementation on a very small satellite, as the sensor requirements for power, pointing, and spatial resolution (aperture size) can in some cases be accommodated by a nanosatellite platform. The Microsized Microwave Atmospheric Satellite Version 2a (MicroMAS-2a), launched on January 11, 2018 and has demonstrated temperature sounding using channels near 118 GHz and humidity sounding using channels near 183 GHz. A second MicroMAS-2 flight unit (MicroMAS-2b) will be launched in late 2018 as part of ELANA-XX. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA in 2016 as part of the Earth Venture–Instrument (EVI-3) program. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. TROPICS will provide rapid-refresh microwave measurements (median refresh rate of approximately 40 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. TROPICS comprises a constellation of six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 206 GHz that is more sensitive to precipitation-sized ice particles. TROPICS flight hardware development is on track for a 2019 delivery.
{"title":"All-weather microwave atmospheric sensing using CubeSats and constellations","authors":"W. Blackwell","doi":"10.1117/12.2324098","DOIUrl":"https://doi.org/10.1117/12.2324098","url":null,"abstract":"Microwave instrumentation is particularly well suited for implementation on a very small satellite, as the sensor requirements for power, pointing, and spatial resolution (aperture size) can in some cases be accommodated by a nanosatellite platform. The Microsized Microwave Atmospheric Satellite Version 2a (MicroMAS-2a), launched on January 11, 2018 and has demonstrated temperature sounding using channels near 118 GHz and humidity sounding using channels near 183 GHz. A second MicroMAS-2 flight unit (MicroMAS-2b) will be launched in late 2018 as part of ELANA-XX. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA in 2016 as part of the Earth Venture–Instrument (EVI-3) program. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. TROPICS will provide rapid-refresh microwave measurements (median refresh rate of approximately 40 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. TROPICS comprises a constellation of six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 206 GHz that is more sensitive to precipitation-sized ice particles. TROPICS flight hardware development is on track for a 2019 delivery.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132551014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrien P. Genoud, R. Basistyy, Gregory M. Williams, Benjamin P. Thomas
Mosquito-borne diseases are a major challenge for Human health as they affect nearly 700 million people every year. Monitoring insects is generally done through trapping methods that are tedious to set up, costly and present scientific biases. Entomological lidars are a potential solution to remotely count and identify mosquito species and gender in realtime. In this contribution, a dual-wavelength polarization sensitive lidar is used in laboratory conditions to retrieve the wingbeat frequency as well as optical properties of flying mosquitoes transiting through the laser beam. From the lidar signals, predictive variables are retrieved and used in a Bayesian classification. This paper focuses on determining the relative importance of the predictive variables used in the classification. Results show a strong dominance of the wingbeat frequency, the impact of predictive variables based on depolarization and backscattering ratios are discussed, showing a significant increase in classification accuracy.
{"title":"Analysis of predictor variables for mosquito species identification from dual-wavelength polarization-sensitive lidar measurements","authors":"Adrien P. Genoud, R. Basistyy, Gregory M. Williams, Benjamin P. Thomas","doi":"10.1117/12.2323432","DOIUrl":"https://doi.org/10.1117/12.2323432","url":null,"abstract":"Mosquito-borne diseases are a major challenge for Human health as they affect nearly 700 million people every year. Monitoring insects is generally done through trapping methods that are tedious to set up, costly and present scientific biases. Entomological lidars are a potential solution to remotely count and identify mosquito species and gender in realtime. In this contribution, a dual-wavelength polarization sensitive lidar is used in laboratory conditions to retrieve the wingbeat frequency as well as optical properties of flying mosquitoes transiting through the laser beam. From the lidar signals, predictive variables are retrieved and used in a Bayesian classification. This paper focuses on determining the relative importance of the predictive variables used in the classification. Results show a strong dominance of the wingbeat frequency, the impact of predictive variables based on depolarization and backscattering ratios are discussed, showing a significant increase in classification accuracy.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130851633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is important to understand the flow of marine debris for environmental research purposes, since marine debris causes extensive damage to coastal environments. Due to its small size, most marine debris in the ocean cannot be confirmed directly, even when a high-spatial-resolution satellite image is used. Thus, to extract candidate pixels containing possible marine debris, pixels with spectra that differ from those of the surrounding ocean are identified. As a first step towards identifying and monitoring marine debris, a method using spectral angle mapper (SAM) algorithm in n-dimensional space corresponding to the satellite spectral bands was previously proposed. In this paper, a method to discriminate marine debris from white-crested waves is proposed using the distance from the origin in an n-dimensional scatter diagram. Moreover, it is also discussed that the relationship between the distance from the coast and the amount of marine debris depends on the locations of the sea currents and neighbouring rivers.
{"title":"Extraction of marine debris in the Sea of Japan using satellite images","authors":"T. Aoyama","doi":"10.1117/12.2324621","DOIUrl":"https://doi.org/10.1117/12.2324621","url":null,"abstract":"It is important to understand the flow of marine debris for environmental research purposes, since marine debris causes extensive damage to coastal environments. Due to its small size, most marine debris in the ocean cannot be confirmed directly, even when a high-spatial-resolution satellite image is used. Thus, to extract candidate pixels containing possible marine debris, pixels with spectra that differ from those of the surrounding ocean are identified. As a first step towards identifying and monitoring marine debris, a method using spectral angle mapper (SAM) algorithm in n-dimensional space corresponding to the satellite spectral bands was previously proposed. In this paper, a method to discriminate marine debris from white-crested waves is proposed using the distance from the origin in an n-dimensional scatter diagram. Moreover, it is also discussed that the relationship between the distance from the coast and the amount of marine debris depends on the locations of the sea currents and neighbouring rivers.","PeriodicalId":370971,"journal":{"name":"Asia-Pacific Remote Sensing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131908410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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