Improved Retrievals for Satellite-based Multispectral Infrared Remote Sensing of Volcanic Clouds
Author: Tianxu Yu
Publisher:
Published: 2000
Total Pages:
ISBN-13:
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Improving Infrared-based Precipitation Retrieval Algorithms Using Multi-spectral Satellite Imagery
Author: Nasrin Nasrollahi
Publisher:
Published: 2013
Total Pages: 122
ISBN-13: 9781303603631
DOWNLOAD EBOOKThe Moderate Resolution Imaging Spectro-radiometer (MODIS) instrument aboard the NASA Earth Observing System (EOS) Aqua and Terra platform with 36 spectral bands provides valuable information about cloud microphysical characteristics and therefore precipitation retrievals. Additionally, CloudSat, selected as a NASA Earth Sciences Systems Pathfinder (ESSP) satellite mission, is equipped with a 94 GHz radar that can detect the occurrence of surface rainfall. The CloudSat radar flies in formation with Aqua with only an average of 60 s delay. The availability of surface rain occurrence based on CloudSat observation together with the multi-spectral capabilities of MODIS makes it possible to create a training data set to distinguish false rain areas based on their radiances in satellite precipitation products (e.g. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)). The brightness temperature of 6 MODIS water vapor and infrared channels are used in this study along with surface rain information from CloudSat to train an Artificial Neural Network model for no-rain recognition. The results suggest a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation. The second approach to identifying no-rain regions, developed in this study, is to find the areas covered with non-precipitating clouds. The cloud type data available from CloudSat is used as a target value to train an artificial neural network model to identify non-precipitating clouds such as cirrus and altostratus. Application of the trained model on two case studies investigated in this research, show significant improvements in near real-time PERSIANN rain estimations. In addition, a cloud type classification algorithm was developed to classify clouds into 7 different classes (cumulus (Cu), stratocumulus (Sc), altocumulus (Ac), altostratus (As), nimbostratus (Ns), high cloud and deep convective cloud). The classification model uses a self organizing features map to classify clouds based on multi-spectral MODIS data and CloudSat cloud types. The result of the classification model shows acceptable results for summertime. The winter season cloud classification is challenging due to dominance of low and middle level clouds. A better cloud classification algorithm for wintertime is achievable using active radar data and is beyond the capabilities of currently available remotely sensed multi-spectral information.
Remote Sensing of Volcanic Processes and Risk
Author: Francesca Cigna
Publisher: MDPI
Published: 2021-03-17
Total Pages: 430
ISBN-13: 3036501266
DOWNLOAD EBOOKRemote sensing data and methods are increasingly being implemented in assessments of volcanic processes and risk. This happens thanks to their capability to provide a spectrum of observation and measurement opportunities to accurately sense the dynamics, magnitude, frequency, and impacts of volcanic activity. This book includes research papers on the use of satellite, aerial, and ground-based remote sensing to detect thermal features and anomalies, investigate lava and pyroclastic flows, predict the flow path of lahars, measure gas emissions and plumes, and estimate ground deformation. The multi-disciplinary character of the approaches employed for volcano monitoring and the combination of a variety of sensor types, platforms, and methods that come out from the papers testify to the current scientific and technology trends toward multi-data and multi-sensor monitoring solutions. The added value of the papers lies in the demonstration of how remote sensing can improve our knowledge of volcanoes that pose a threat to local communities; back-analysis and critical revision of recent volcanic eruptions and unrest periods; and improvement of modeling and prediction methods. Therefore, the selected case studies also demonstrate the societal impact that this scientific discipline can potentially have on volcanic hazard and risk management.
Remote Sensing of Volcanoes and Volcanic Processes
Author: D.M. Pyle
Publisher: Geological Society of London
Published: 2014-01-06
Total Pages: 361
ISBN-13: 1862393621
DOWNLOAD EBOOKThis volume focuses on how advances in both remote sensing and modelling can be brought together to improve our understanding of the behaviour of active volcanoes. It includes review papers, papers reporting technical advances and case studies showing how the integration of remote-sensing observations with models can be put to good use.
Development of Satellite Remote Sensing Techniques for Quantifying Volcanic Ash Cloud Properties
Author:
Publisher:
Published: 2014
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKNovel new approaches to automatically detect and characterize volcanic ash using satellite data are presented. The Spectrally Enhanced Cloud Objects (SECO) ash detection algorithm, combines radiative transfer theory, Bayesian methods, and image processing/computer vision concepts to identify volcanic ash clouds in satellite data with skill that is generally comparable to a human expert, especially with respect to false alarm rate. The SECO method is globally applicable and can be applied to virtually any low earth orbit or geostationary satellite sensor. The new ash detection approach was quantitatively proven to be significantly more skillful than traditional pixel based approaches, including the commonly used "split-window" technique. The performance of the SECO approach is extremely promising and well suited for a variety of new and improved applications. A new approach to retrieve volcanic ash cloud properties from infrared satellite measurements was also developed. The algorithm utilizes an optimal estimation framework to retrieve ash cloud height, mass loading, and effective particle radius. Optimal estimation allows uncertainties in the measurements and forward model to be taken into account and uncertainty estimates for each of the retrieved parameters to be determined. Background atmospheric water vapor, surface temperature, and surface emissivity are explicitly accounted for on a pixel-by-pixel basis, so the algorithm is globally applicable. In addition, the ash cloud retrieval algorithm is unique because it allows the cloud temperature/height to be a free parameter. Volcanic ash clouds are a major aviation hazard. Fine-grained ash from explosive eruptions can be transported long distances (>1000 km) from the source volcano by atmospheric winds, severely disrupting aviation operations. Volcanic ash clouds are complex and the background environment in which they reside can be as well. Thus, sophisticated satellite remote sensing techniques for extracting ash cloud properties are needed to increase the timeliness and accuracy of volcanic ash advisories and forecasts. As demonstrated using the 2008 eruption of Kasatochi volcano in Alaska, the new theoretical ash remote sensing framework is well suited for advanced applications such as automated volcanic ash cloud alerting and constraining model forecasts of volcanic ash dispersion and removal.
Atmospheric Particles Retrieval Using Satellite Remote Sensing
Author: Yingxin Gu
Publisher:
Published: 2004
Total Pages: 156
ISBN-13:
DOWNLOAD EBOOKThe GOES-R Series
Author: Steven J. Goodman
Publisher: Elsevier
Published: 2019-10-05
Total Pages: 306
ISBN-13: 0128143282
DOWNLOAD EBOOKThe GOES-R Series: A New Generation of Geostationary Environmental Satellites introduces the reader to the most significant advance in weather technology in a generation. The world’s new constellation of geostationary operational environmental satellites (GOES) are in the midst of a drastic revolution with their greatly improved capabilities that provide orders of magnitude improvements in spatial, temporal and spectral resolution. Never before have routine observations been possible over such a wide area. Imagine satellite images over the full disk every 10 or 15 minutes and monitoring of severe storms, cyclones, fires and volcanic eruptions on the scale of minutes. Introduces the GOES-R Series, with chapters on each of its new products Provides an overview of how to read new satellite images Includes full-color images and online animations that demonstrate the power of this new technology
Thermal Remote Sensing of Active Volcanoes
Author: Andrew Harris
Publisher: Cambridge University Press
Published: 2013-04-18
Total Pages: 739
ISBN-13: 052185945X
DOWNLOAD EBOOKA comprehensive manual exploring radiometry methodologies and principles used with satellite-, radiometer- and thermal-camera data, for academic researchers and graduate students.
American Doctoral Dissertations
Author:
Publisher:
Published: 2000
Total Pages: 816
ISBN-13:
DOWNLOAD EBOOKRemote Sensing of Clouds and Precipitation
Author: Constantin Andronache
Publisher: Springer
Published: 2018-02-21
Total Pages: 288
ISBN-13: 3319725831
DOWNLOAD EBOOKThis book presents current applications of remote sensing techniques for clouds and precipitation for the benefit of students, educators, and scientists. It covers ground-based systems such as weather radars and spaceborne instruments on satellites. Measurements and modeling of precipitation are at the core of weather forecasting, and long-term observations of the cloud system are vital to improving atmospheric models and climate projections. The first section of the book focuses on the use of ground-based weather radars to observe and measure precipitation and to detect and forecast storms, thunderstorms, and tornadoes. It also discusses the observation of clouds using ground-based millimeter radar. The second part of the book concentrates on spaceborne remote sensing of clouds and precipitation. It includes cases from the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) mission, using satellite radars to observe precipitation systems. Then, the focus is on global cloud observations from the ClaudSat, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), including a perspective on the Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) satellite. It also addresses global atmospheric water vapor profiling for clear and cloudy conditions using microwave observations. The final part of this volume provides a perspective into advances in cloud modeling using remote sensing observations.
