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OGC STANDARDS AND WEB SERVICES PIPELINE FOR PROCESSING AVALANCHE AND EARTH OBSERVATION OPEN DATA

Francesco Bartoli1,*

1 Geobeyond Srl, Rome, Italy

ABSTRACT: Every avalanche has a place, a shape and a path which can be spatially described. Awareness of avalanche risk combined with the identification of potential affected areas, because of their location, may become relevant for spatial data infrastructures and all geoportals that gather in-formation about safety and risk. Geospatial tools are able to create own maps, process and exploit information from different sources of data such as community-driven dataset like OpenStreetMap, near real-time meteorological sensor networks and satellite earth observation from open access programs like Copernicus and Nasa. Open source toolkit like GeoServer and upstream derived project like GeoAvalanche have evolved the way to exchange and process avalanche data and finally to enhance the quality of the information available on the Web. The use of these tools can publish data with common standards and formats - primarily Canadian Avalanche Association Markup Language (CAAML), a GML profile for avalanche data, and then the plethora of OGC realm - for achieving interoperability across web and mobile clients at largest extent. Moreover the strenghten of cooperation and data harmonization establishes a framework of data-driven geospatial services compliant with OGC standards at local, regional, national and cross-boarder level which turns into an easier dissemination of avalanche warnings for the public through maps in a timely manner. This talk will address data transformation and assimilation for handling national and cross-boarder spatial information related to snow avalanche risk which can be modelled into the INSPIRE fra-mework. The harmonization of CAAML semantics into a package model within Natural Risk Zones theme will be then discussed. Examples of possible implementation of processing algorithms into a pipeline of different sources of data will be presented with a detail architectural insight.

KEYWORDS: caaml, copernicus, satellite, open data, ogc, inspire.

1 INTRODUCTION

The risks caused by insufficient or extreme ac-cumulation of snow and then potential ava-lanches have become very important as demon-strated by the frequency of multiple accidents, the block of transport infrastructures and the limited availability of water resources for agricul-tural irrigation and energy generation. The im-pact that the majority of these unpredictable events have on the population can be signifi-cantly reduced with prevention, the early warn-ing and with a timely and coordinated manage-ment of the phenomenon. In Europe, the existing avalanche warning ser-vices and centres for rapid response are well

organized, nevertheless, they might have a greater impact from a huge use of satellite tech-nology, open data, and real-time communica-tions. Furthermore, the dissemination of the risk can be actually eased by the extensive use of those geospatial technologies which are stand-ards driven. The Open Geospatial Consortium and their standards to the geospatial Web such as Web Mapping Services (WMS) for map visu-alization, Web Feature Service (WFS) and Web Coverage Service (WCS) for vector/raster data exchange and also Web Processing Service (WPS) for geodata processing pipeline are cer-tainly good specifications to follow. This would ensure harmonisation and make information systems and early warnings more effective and interoperable given that they currently suffer from lack of infrastructure and common commu-nication best practices. Earth Observation imagery, in particular, is a great resource with an open access license from Copernicus which leads to a better prevention for risk management and can improve the re-sults from nowcasting and forecasting models

______________________ Corresponding author address: Francesco Bartoli, Geobeyond Srl, Rome, Italy; tel: +39 333 299 7173; fax: +39 074 667 6843; email: [email protected]

Proceedings, International Snow Science Workshop, Innsbruck, Austria, 2018

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allowing to quickly delivering more precise prod-ucts and alerts to the public. In fact, the detec-tion and monitoring of potential risks become a key factor in the response of surveillance sys-tems more often because warning services for snow avalanche have to cover areas not easily accessible and prone to natural or manmade disasters. Data quality of Earth Observation (i.e. Copernicus) can significantly impact to helping to solve major problems about the expected outputs of algorithms. Satellite data as a source of near real-time snowpack stability factors can be a challenge suited to improve the spatial and temporal resolution of the product offered also combined with the availability of different sources of open data. In fact they could be ex-ploited through the services mentioned above into a processing pipeline. On the other hand the avalanche community has already started a well-defined process to build a conceptual schema and a data model for designing the specification to exchange infor-mation. CAAML was born in 2003 from the Ca-nadian Avalanche Association and is an XML grammar language to provide a shared encod-ing structure to exchange snow avalanche relat-ed information over the Internet. This specifica-tion meets at certain point the need to being compliant with the European regulation of the INSPIRE directive where the term interoperabil-ity is used to match the possibility for spatial da-tasets to be combined, and for services to inter-act, without repetitive manual intervention, in such a way that the result is coherent and the added value of the datasets and services is en-hanced. INSPIRE defines also the specific theme Natural Risk Zones where avalanches are identified. As a consequence, data providers across Eu-rope, primarily avalanche warning and civil pro-tection services, have to provide their data com-pliant with the data specifications and build their geoportals with the standards in mind. However it’s not required and probably also not reasona-ble to change the ways their legacy data is modeled, structured and stored because a sort of mapping between the CAAML schema and the INSPIRE schema can be achieved. This in theory applies to other harmonization tasks be-yond INSPIRE thus even to CAAML itself as a target schema.

2 TOOLKITS

2.1 GeoServer and GeoAvalanche

GeoServer is the reference implementation of OGC for Web Feature Service (WFS), Web Mapping Service (WMS), Web Coverage Ser-vice (WCS) and also supports OGC Web Pro-cessing Service (WPS). WFSs are of particular

interest for data interoperability because, unlike a portrayal service such as WMS, they allow directly querying the underlying data. GeoServer is a powerful geospatial engine able to aggregate different datastores at a single point and to let them be republished as cascad-ed Web Services from distributed sources in-cluding also remote WFS. As the support for GML 3.2.1 is already developed, GeoServer can comply with the INSPIRE Directive that requires to issue WFS services in accordance with the above-mentioned GML version. GeoAvalanche server is built upon GeoServer and equipped with its plugin for supporting third-party GML application schemas. This latter functionality allows to serving complex snow avalanche features encoded by CAAML. The project is developed under GNU General Public License v3. The feature types which currently can be supported from CAAML are the following:

– Avalanche incident information– Avalanche activity comments– Avalanche observations– Avalanche bulletins– Avalanche closures– Observations on the field– Snowpack structure comments– Snow profile observations– Weather observations

The latest version 5.0 consists of 9 schema files structurally organized as follows:

Figure 1: Schema file structure of CAAML ver-sion 5.0

Since the nature of CAAML strictly derives from GML, it was designed with the same flexibility. Actually, this recent version borrows the concept of profile from GML, which allows dealing with a logical limitation of the elements relevant to a specific application while keeping the ability to be validated against the overall CAAML stand-ard.


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Currently a profile suitable among the EAWS agencies for their CAAML-scoped avalanche bulletins has been defined. This specific schema file is currently maintained at this location http://caaml.org/Schemas/V5.0/Profiles/BulletinEAWS/CAAMLv5_BulletinEAWS.xsdFigure 2 shows how a bulletin element has to be semantically expressed in the European profile.

Figure 2: XML schema definition for CAAML bulletin type asserted in the EAWS profile

As a result, the GeoAvalanche server would be able to manage the exchange of any profiled elements and, hence, to achieve interoperability at different levels (regional/national/european). GeoAvalanche deployments also include a spa-tial DBMS, such as PostGIS, to supplement GIS functionalities for CAAML complex features and, therefore, they become together a good fit for all those features that you might expect from a Spatial Data Infrastructure. The GeoAvalanche component within a CAAML data infrastructure plays a key role because it manages both read and write opera-tions regardless of the database schema used to store such data. It can perform WFS filter queries and also acts according to OGC WFS-T transactional specification because each single service is conformed to the same CAAML appli-cation schema. On the other hand, its service-oriented architec-ture allows exploiting lightweight format like GeoJSON for consuming data from mobile, cus-tom-client and any third-party system. A straight-forward request for bulletins can be expressed as follows:

http://localhost:8080/geoavalanche/avy/ows?servi-ce=WFS&version=1.0.0&request=GetFeature&typeName=avy:bulletins&outputFormat=json

and further refined in order to filter out appropri-ate macro-zones through a CQL syntax like cql_filter=(res=’Monte Rosa”).The server offers a wide flexibility in building a nationwide network of regional office deploy-

ments. In fact, once the national authorities de-cide to leverage regional offices to using CAAML, it can play a key role in setting up a new prospect of data-driven services. The visu-alization capabilities are however possible thanks to the maturity of GeoAvalanche that of-fers default out-of-the-box capabilities to display maps via WMS standard implementation and, hence, that leads to easily deliver thematic maps of their nowcasting and forecasting prod-ucts.

Figure 3: Proposal for a European snow ava-lanche Spatial Data Infrastructure

Environmental risk management is a major scope issued by INSPIRE directive. The theme “Natural Risk Zones” asserted in the Annex III identifies all atmospheric, meteorological, hydro-logic, geological and wildfire phenomena that, because of their location, severity, and frequen-cy, have the potential to seriously affect popula-tion. Specifically, it defines particular areas with sig-nificant snow cover combined with steep slopes – amplified by snowdrifts – that are prone to in-fluence the occurrence of avalanches and snow slides. In this context, the investigations and the under-lying purposes mainly concern the provision of a suitable SDI. This would give the opportunity to interoperate with systems aimed at regulating the land use and the resource management in areas under certain restrictions and linked to such risk, and would provide a web mapping of those areas susceptible to snow slides by dividing them into zones according to different risk classes. A first example of geographical feature – as tool mostly known by the public – is the bulletin that is issued according to the avalanche danger scale whose risk levels are now commonly ac-cepted and universally recognized by all organi-zations. This standardization conceives a refer-ence to the mapping of those areas at risk, and


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allows representing thematic maps with a unique legend that can be understood across Europe.

3 EXAMPLES

INSPIRE is a specification limited to european countries hence the example takes into account a specific CAAML profile (EAWS Bulletin) for avalanche bulletin which has been developed for avalanche services under the umbrella of EAWS. GeoAvalanche has already the capabilities to publish WFS of vector datasets which describe a bulletin as an instance of the GML application schema of that CAAML profile. This means that a mapping instance is required to align such service outputs to the schema of Natural Risk Zone theme. Hale is an open source tool that can be used for establishing rules for trasforma-tions between the CAAML schema and the tar-get one. A basic trasformation has been developed with few simple assumptions and the rename of the required properties like in the figure:

Figure 4. Mapping of CAAML EAWS Bulletin to INSPIRE Risk Zones The simplest rules are:

– A RiskZone is a Bulletin – dangerRatings is renamed to leve-

lOfRisk – DangerRating is renamed to LevelOrIn-

tensity – locRef is renamed to location – validTime is renamed to validityPeriod

The transformation can be also performed onli-ne through a web service and deployed as Do-wnload Services and Transformation Services INSPIRE compliant. The transformation func-tionality can be encapsulated in the Download Service. In this case, the user directly requests the Download Service. The Download Service performs the transformation and responds with the transformed data. Another powerful use case to exploit OGC stan-dards is to achieve a pile of microservices in the form of WPS implementation. A WPS offers the capability to run a process over the Web by pro-

viding input data, which can optionally have a spatial component or not, and getting the output as a result. Processing can be cascaded into a pipeline to execute complex algorithms and can be called also by web mapping clients to visuali-ze the final result on a map. The processes are usually integrated into a catalog so that they can be discovered and crawled for actionable tasks. Possible examples are endless but the most desirable could be: - Aggregate adjacent pixels, which can have the same value to extract statistics; - Combine values of the same pixel from various sources (elevation, exposure, aspect, snow pack) in order to generate advanced calculation of the risk; - Combine processes into complex workflow to perform whole algorithms of the models used by forecasters for their use cases (Hazard Zoning, Forecasting, Alerting).

Figure 5. Web Processing Service for the deliv-ery of snow satellite data pipeline The GeoAvalanche server is equipped with a series of WPS analysis: terrain avalanche expo-sure analysis, snow pack analysis and land use reclassification. They can perform the algorithm of the risk on the fly from input shapes, which can be geographical points as well as lines. The expected output is a buffered shape (segmented for lines) of the inputs with the associated risk index.

The algorithm used is based on the formula from Renner and deployed as the workflow in the figure:


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Figure 6. GeoAvalanche pipeline for avalanche risk insight

The analysis of terrain avalanche exposure is based on the EU-DEM Pan-European elevation reference products. The grid of the EU-DEM datasets is being extracted for a calculated crop and different algorithms are being performed for the derivation of terrain analysis parameters (e.g., slope, aspect, curvature of the terrain). These outputs are further elaborated into an algorithm for the calculation of the terrain-based avalanche risk and the final result of this analy-sis is a feature (vector data) with a static index of the risk for the input shape from an OGC WPS web service. The result is also normalized with a reclassification that takes into account the land use coverage from Copernicus. EU-DEM is the Pan-European elevation reference datasets developed in the frame of Copernicus Prepara-tory Action 2009-2012 and is fully in line with the Copernicus data and information policy regula-tion, full, open and free access. The time-series analysis of snow pack is based on the Cryoland Pan-European and regional Snow/Ice products which are generated from optical and active (radar, SAR) and passive mi-crowave (MW) satellite imagery. The time-series of Daily Fractional Snow Cover from Optical Satellite Data covering the Alps and Multi-temporal Wet Snow Covered Area from Radar Data over the Alps datasets are being extracted for selected pixels of the calculated crop and an algorithm for the derivation of snow pack stabil-ity trend in a time window of the last three days is being performed. The final result of this analy-sis is a snow pack index of the trend for the in-put shape. Cryoland is the Pan-European and regional snow/ice datasets developed in the frame of Copernicus Snow and Land Ice Service 2011-2015. The underlying Daily Fractional Snow Cover from Optical Satellite Data covering the Alps and Multi-temporal Wet Snow Covered Area from Radar Data over the Alps datasets are available online from the Cryoland GeoPor-tal and can be downloaded for free according to the Copernicus Data Access Policies. The prod-uct is also described with standard-compliant OGC metadata and is delivered as Dataset-Series through a Earth Observation Web Cover-age Server (EO-WCS) which is maintained by ESA.

5 REFERENCES

Renner, k., AVALANCHE RISK - Terrain susceptibility, 2015 GIS in Water Resources

Hale, https://github.com/halestudio/hale Bartoli, F., GeoAvalanche - spatial data infrastructure

for avalanche awareness warning, Geobeyond

Srl, Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska


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