Coastal Online Analysis and Synthesis Tool 2.0 (COAST)

The Coastal Online Assessment and Synthesis Tool (COAST) 3D geobrowser has been developed to integrate disparate coastal datasets from NASA and other sources into a desktop tool that provides new data visualization and analysis capabilities for coastal researchers, managers, and residents. It is built upon the widely used NASA-developed open source World Wind geobrowser from NASA Ames (Patrick Hogan et al.) .Net and C# version is used for development. It is leveraged off of World Wind community shared code samples and COAST 2.0 enhancement direction is based on Coastal science community feedback and needs assessment (GOMA). The main objective is to empower the user to bring more user-meaningful data into multi-layered, multi-temporal spatial context

Image processing for smart browsing of ocean colour data products and subsequent incorporation into a multi-modal sensing framework

Ocean colour is defined as the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments and coloured dissolved organic material and so water colour can provide valuable information on coastal ecosystems. The ‘Ocean Colour project’ collects data from various satellites (e.g. MERIS, MODIS) and makes this data available online. One method of searching the Ocean Colour project data is to visually browse level 1 and level 2 data. Users can search via location (regions), time and data type. They are presented with images which cover chlorophyll, quasi-true colour and sea surface temperature (11 μ) and links to the source data. However it is often preferable for users to search such a complex and large dataset by event and analyse the distribution of colour in an image before examination of the source data. This will allow users to browse and search ocean colour data more efficiently and to include this information more seamlessly into a framework that incorporates sensor information from a variety of modalities. This paper presents a system for more efficient management and analysis of ocean colour data and suggests how this information can be incorporated into a multi-modal sensing framework for a smarter, more adaptive environmental sensor network

Coastal On-line Assessment and Synthesis Tool 2.0

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest

Supporting metropolitan Venice coastline climate adaptation. A multi-vulnerability and exposure assessment approach

Urban planning for adaptation to climate change privileges the construction of cognitive frameworks developed through the use of new spatial technologies and open-source databases. The significant and most highly innovative aspect concerns how resilience to CC under conditions of vulnerability and risk is defined, monitored and assessed. Based on these premises, this paper aims to explore a new methodology of climate vulnerability, exposure and risk analysis through multicriteria assessment techniques by activating a case study in the coastal municipality of Jesolo (Italy). Taking into consideration three main weather-climate impacts (Urban Flooding, Coastal Flooding and Urban Heat Island) the methodology searches for the best geo-referenced data that can best describe the recognizing impact of the cumulative impact condition through testing a GIS-based multi-attribute exploratory procedure. Intersectoral and multilevel vulnerability conditions at different spatial scales are configured. The analysis methodology continues using open source data (from Open Street Map) to construct local exposure information layers. Exposure combined with spatial vulnerability conditions allows the generation of multi-hazard mapping. Experimentation with multi-hazard climate-oriented spatial assessment can guide planning and public decision-making in new policy domains and target mitigation and adaptation actions in land planning, management and regulation practices. Finally, the proposed methodology can activate stakeholder engagement processes within municipalities to discuss the actual perceived risk and begin a collaborative journey with citizens to identify best practices and solutions to adopt in the areas indicated by the risk mapping

Study on the Spatial Dynamic Change of Tidal Flat in the Pearl River Estuary from 1990 to 2020

This paper Based on GIS and remote sensing analysis methods, it uses multi-source remote sensing data to obtain the coastal mudflat change and land cover/land use change data of the the Pearl River Estuary Bay Area in 1990, 2005 and 2020. This paper studies the temporal and spatial change characteristics of the coastline in the the Pearl River Estuary Bay Area in three periods, the temporal and spatial pattern change of land use, and the relationship between the two, and summarizes their change rule and causes

The responses of evapotranspiration due to changes of LUCC under seawater intrusion in a coastal region

The paper provides a coherent pattern identification analysis of the impacts of coastal land use and land cover (LULC) on evapotranspiration (ET) under the impact of seawater intrusion. The study applied the Landsat satellite data to characterize the LULC at Laizhou Bay, Shandong Province, China. Then, the ET and heat fluxes were estimated using the surface energy balance algorithm for land model with two-time phase thermal infrared band images and regional surface parameters. This allowed for the eventual linkage of seawater intrusion to land use/cover changes (LUCC) and ET variations over time. The case study discussed in this paper carried out a coastal landscape dynamics assessment using multi-source and multi-sensor remote sensing technologies. The results are: (1) due to its distance from the sea, the vegetation index (modified soil-adjusted vegetation index, MSAVI) gradually increases with the gradual increase of land use grade (Uindex); (2) there are a variety of types of relational patterns between parameters (LST, G(n), MSAVI, and Uindex) and ET (positive, negative, and no relationship); and (3) seawater intrusion significantly affected the spatial pattern of LUCC, which evidently affected the spatial distribution of ET. The spatial distribution pattern and change characteristics of ET were formed by double driving forces of seawater intrusion and LUCC under the background effects of regional climate.The paper provides a coherent pattern identification analysis of the impacts of coastal land use and land cover (LULC) on evapotranspiration (ET) under the impact of seawater intrusion. The study applied the Landsat satellite data to characterize the LULC at Laizhou Bay, Shandong Province, China. Then, the ET and heat fluxes were estimated using the surface energy balance algorithm for land model with two-time phase thermal infrared band images and regional surface parameters. This allowed for the eventual linkage of seawater intrusion to land use/cover changes (LUCC) and ET variations over time. The case study discussed in this paper carried out a coastal landscape dynamics assessment using multi-source and multi-sensor remote sensing technologies. The results are: (1) due to its distance from the sea, the vegetation index (modified soil-adjusted vegetation index, MSAVI) gradually increases with the gradual increase of land use grade (Uindex); (2) there are a variety of types of relational patterns between parameters (LST, G(n), MSAVI, and Uindex) and ET (positive, negative, and no relationship); and (3) seawater intrusion significantly affected the spatial pattern of LUCC, which evidently affected the spatial distribution of ET. The spatial distribution pattern and change characteristics of ET were formed by double driving forces of seawater intrusion and LUCC under the background effects of regional climate

Selecting coastal hotspots to storm impacts at the regional scale: a Coastal Risk Assessment Framework

Managing coastal risk at the regional scale requires a prioritization of resources along the shoreline. A transparent and rigorous risk assessment should inform managers and stakeholders in their choices. This requires advances in modelling assessment (e.g., consideration of source and pathway conditions to define the probability of occurrence, nonlinear dynamics of the physical processes, better recognition of systemic impacts and non-economic losses) and open-source tools facilitating stakeholders’ engagement in the process. This paper discusses how the Coastal Risk Assessment Framework (CRAF) has been developed as part of the Resilience Increasing Strategies for Coasts Toolkit (RISC-KIT). The framework provides two levels of analysis. A coastal index approach is first recommended to narrow down the risk analysis to a reduced number of sectors which are subsequently geographically grouped into potential hotspots. For the second level of analysis an integrated modelling approach improves the regional risk assessment of the identified hotspots by increasing the spatial resolution of the hazard modelling by using innovative process-based multi-hazard models, by including generic vulnerability indicators in the impact assessment, and by calculating regional systemic impact indicators. A multi-criteria analysis of these indicators is performed to rank the hotspots and support the stakeholders in their selection. The CRAF has been applied and validated on ten European case studies with only small deviation to areas already recognised as high risk. The flexibility of the framework is essential to adapt the assessment to the specific region characteristics. The involvement of stakeholders is crucial not only to select the hotpots and validate the results, but also to support the collection of information and the valuation of assets at risk. As such, the CRAF permits a comprehensive and systemic risk analysis of the regional coast in order to identify and to select higher risk areas. Yet efforts still need to be amplified in the data collection process, in particular for socio-economic and environmental impacts

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Developing a conceptual model of marine farming in New Zealand

Survey and Geographic Information System (GIS) data analysis describes the relative influence of biophysical and human variables on site choices made by marine farmers in New Zealand. Community conflicts have grown in importance in determining farm location and different government planning strategies leave distinct signature patterns. Recent legislation empowers local governments to choose among three strategies for future regional aquaculture development. This paper suggests each strategy could result in different spatial outcomes. Simulation modelling of the type described here can provide a better understanding of farmer responses to management approaches and the range of futures that could result from planning choices made today