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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Machine Learning Approach To Retrieving Physical Variables From Remotely Sensed Data, Fazlul Shahriar
Machine Learning Approach To Retrieving Physical Variables From Remotely Sensed Data, Fazlul Shahriar
Dissertations, Theses, and Capstone Projects
Scientists from all over the world make use of remotely sensed data from hundreds of satellites to better understand the Earth. However, physical measurements from an instrument is sometimes missing either because the instrument hasn't been launched yet or the design of the instrument omitted a particular spectral band. Measurements received from the instrument may also be corrupt due to malfunction in the detectors on the instrument. Fortunately, there are machine learning techniques to estimate the missing or corrupt data. Using these techniques we can make use of the available data to its full potential.
We present work on four …
Machine Learning Algorithms For Automated Satellite Snow And Sea Ice Detection, George Bonev
Machine Learning Algorithms For Automated Satellite Snow And Sea Ice Detection, George Bonev
Dissertations, Theses, and Capstone Projects
The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research.
In response to these challenges, …
A Comparison Of Modis/Viirs Cloud Masks Over Ice-Bearing River: On Achieving Consistent Cloud Masking And Improved River Ice Mapping, Simon Kraatz, Reza Khanbilvardi, Peter Romanov
A Comparison Of Modis/Viirs Cloud Masks Over Ice-Bearing River: On Achieving Consistent Cloud Masking And Improved River Ice Mapping, Simon Kraatz, Reza Khanbilvardi, Peter Romanov
Publications and Research
The capability of frequently and accurately monitoring ice on rivers is important, since it may be possible to timely identify ice accumulations corresponding to ice jams. Ice jams are dam-like structures formed from arrested ice floes, and may cause rapid flooding. To inform on this potential hazard, the CREST River Ice Observing System (CRIOS) produces ice cover maps based on MODIS and VIIRS overpass data at several locations, including the Susquehanna River. CRIOS uses the respective platform’s automatically produced cloud masks to discriminate ice/snow covered grid cells from clouds. However, since cloud masks are produced using each instrument’s data, and …
Improved Viirs And Modis Sst Imagery, Irina Gladkova, Alexander Ignatov, Fazlul Shahriar, Yury Kihai, Don Hillger, Boris Petrenko
Improved Viirs And Modis Sst Imagery, Irina Gladkova, Alexander Ignatov, Fazlul Shahriar, Yury Kihai, Don Hillger, Boris Petrenko
Publications and Research
Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) radiometers, flown onboard Terra/Aqua and Suomi National Polar-orbiting Partnership (S-NPP)/Joint Polar Satellite System (JPSS) satellites, are capable of providing superior sea surface temperature (SST) imagery. However, the swath data of these multi-detector sensors are subject to several artifacts including bow-tie distortions and striping, and require special pre-processing steps. VIIRS additionally does two irreversible data reduction steps onboard: pixel aggregation (to reduce resolution changes across the swath) and pixel deletion, which complicate both bow-tie correction and destriping. While destriping was addressed elsewhere, this paper describes an algorithm, adopted in …
Separation Of Soil Evaporation And Vegetation Transpiration By Modis Data For Central And Northern China, Tingting Li, Jinhui Jeanne Huang
Separation Of Soil Evaporation And Vegetation Transpiration By Modis Data For Central And Northern China, Tingting Li, Jinhui Jeanne Huang
International Conference on Hydroinformatics
Evapotranspiration(ET) plays a crucial role in the hydrologic system. To estimate evapotranspiration quantitatively in a large scale, remote sensing data has been used in a number of models and shows its applicability in the estimation of evapotranspiration. In this paper, evapotranspiration for central and northern China was derived from MODIS data. In arid and semi-arid regions, soil evaporation can be considered as the minimum water requirement for bare area, while evapotranspiration can be considered as the minimum water demand for the area covered by vegetation. Hence the separation of soil evaporation and vegetation transpiration is valuable for efficient water resources …
Snowmelt Modelling Of Dhauliganga River Using Snowmelt Runoff Model, Dhyan Singh Arya, Amar Kant Gautam, Asmita Ramkrishna Murumkar
Snowmelt Modelling Of Dhauliganga River Using Snowmelt Runoff Model, Dhyan Singh Arya, Amar Kant Gautam, Asmita Ramkrishna Murumkar
International Conference on Hydroinformatics
Snowmelt modeling was attempted in this study using Snowmelt Runoff Model to simulate streamflow in Tamak Lata Catchment located in the Indian Himalayas. The daily snow cover data was generated using the depletion curves prepared using snow cover information obtained from MODIS remote sensing images during May 2009 to August 2012. Discharge, temperature and rainfall data observed at Tamak Lata during May 2009 to August 2012 were used for calibration and validation of the model. The characteristics of snow cover in the basin shows that the accumulation of snow at higher altitude starts from the second week of October and …
Performance Evaluation Of Smos Soil Moisture Retrieval Parameters For Hydrological Application, Prashant K. Srivastava, Dawei Han, Miguel A. Rico-Ramirez, Peggy O'Neil, Tanvir Islam, Manika Gupta
Performance Evaluation Of Smos Soil Moisture Retrieval Parameters For Hydrological Application, Prashant K. Srivastava, Dawei Han, Miguel A. Rico-Ramirez, Peggy O'Neil, Tanvir Islam, Manika Gupta
International Conference on Hydroinformatics
Microwave remote sensing has high potential for soil moisture retrieval. However, the efficient retrieval of soil moisture depends on optimally choosing the soil moisture retrieval parameters. In this study first the initial evaluation of SMOS L2 product is performed and then four approaches regarding soil moisture retrieval from SMOS brightness temperature are reported. The radiative transfer equation based tau-omega rationale is used in this study for the soil moisture retrievals. The single channel algorithms (SCA) using H polarisation is implemented with modifications, which includes the effective temperatures simulated from ECMWF (downscaled using WRF-NOAH Land Surface Model (LSM)) and MODIS. The …
Development Of A Ground Based Remote Sensing Approach For Direct Evaluation Of Aerosol-Cloud Interaction, Bomidi Lakshmi Madhavan, Yuzhe He, Yonghua Wu, Barry Gross, Fred Moshary, Samir Ahmed
Development Of A Ground Based Remote Sensing Approach For Direct Evaluation Of Aerosol-Cloud Interaction, Bomidi Lakshmi Madhavan, Yuzhe He, Yonghua Wu, Barry Gross, Fred Moshary, Samir Ahmed
Publications and Research
The possible interaction and modification of cloud properties due to aerosols is one of the most poorly understood mechanisms within climate studies, resulting in the most significant uncertainty as regards radiation budgeting. In this study, we explore direct ground based remote sensing methods to assess the Aerosol-Cloud Indirect Effect directly, as space-borne retrievals are not directly suitable for simultaneous aerosol/cloud retrievals. To illustrate some of these difficulties, a statistical assessment of existing multispectral imagers on geostationary (e.g., GOES)/Moderate Resolution Imaging Spectroradiometer (MODIS) satellite retrievals of the Cloud Droplet Effective Radius (Reff) showed significant biases especially at larger solar zenith angles, …