Remote Sensing of the Oceans

This book covers different topics in the framework of remote sensing of the oceans. Latest research advancements and brand-new studies are presented that address the exploitation of remote sensing instruments and simulation tools to improve the understanding of ocean processes and enable cutting-edge applications with the aim of preserving the ocean environment and supporting the blue economy. Hence, this book provides a reference framework for state-of-the-art remote sensing methods that deal with the generation of added-value products and the geophysical information retrieval in related fields, including: Oil spill detection and discrimination; Analysis of tropical cyclones and sea echoes; Shoreline and aquaculture area extraction; Monitoring coastal marine litter and moving vessels; Processing of SAR, HF radar and UAV measurements

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

CIRA annual report FY 2016/2017

Reporting period April 1, 2016-March 31, 2017

Climatology of Rainfall Distribution and Asymmetries of Tropical Cyclones: A Global Perspective

Estimating the magnitude of tropical cyclone (TC) rainfall at different landfalling states is an important aspect of the TC forecast that directly affects the level of response from emergency managers in coastal areas. This research analyses the spatial distribution of the rainfall magnitude in tropical cyclones (TCs) at different stages over global oceans. The research’s central hypothesis is that TC rainfall exhibits distinct features in the long-term satellite dataset due to the evolution of the spatial distribution, radial variation, and asymmetries at the stages before, during, and after landfall. The resulting patterns are analyzed through a statistical approach that takes advantage of a 20-year global satellite database of rainfall retrievals from the TRMM/GPM constellation, with the aim to achieve two main objectives: 1) The first objective was to explore the global trends of TC rainfall rates using observational evidence provided by a satellite-based climatology. Results indicate there is an increasing trend in the global average TC rainfall rate of about 1.3% per year, with a more pronounced trend in the northern hemisphere than in the southern hemisphere. 2) The second objective was to examine the spatial distribution of the magnitude and axisymmetric intensity profiles of rainfall over the six TC-prone basins. The obtained differences were quantitatively investigated in terms of geographic location, sub-regions within the storm, and TC intensities. Results indicate that major hurricanes in the Atlantic basin exhibit heavier inner-core rainfall rates than those in any other basins, and this difference is highly correlated to specific environmental conditions. Overall, with the achievement of the above-described objectives, this document identifies and summarizes the dominant factors that control rainfall distribution in global TCs, mainly focused on the differences during landfilling processes

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Remote Sensing Monitoring of Land Surface Temperature (LST)

This book is a collection of recent developments, methodologies, calibration and validation techniques, and applications of thermal remote sensing data and derived products from UAV-based, aerial, and satellite remote sensing. A set of 15 papers written by a total of 70 authors was selected for this book. The published papers cover a wide range of topics, which can be classified in five groups: algorithms, calibration and validation techniques, improvements in long-term consistency in satellite LST, downscaling of LST, and LST applications and land surface emissivity research

CIRA annual report FY 2015/2016

Reporting period April 1, 2015-March 31, 2016

Semantic location extraction from crowdsourced data

Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction