Visualisation

The ability to see spatial data in its native context is essential for that data to be appreciated whether by the scientific community, policy and decision-makers or the general public. Recently, the accessibility of 4D and n‐dimensional data has dramatically changed. Without having to install an application, this spatial data can now be experienced via any web browser on mobile devices or desktop computers.

By simply updating the app on your server, the latest version of your application is now immediately available to your entire user‐community. Unlike other virtual globes such as Google Earth, NASA World Wind offers something else very special, full control over your ability to customize the interface with any interactive features or functionalities you might need. You decide how the data is accessed and experienced, and by who. This allows you to provide maximum value to the information for your user community.

The long-standing version (since 2006) of NASA World Wind is written in Java. This version of World Wind is well established and thoroughly tested. This World Wind Java version is used to address highly complex solutions, given any number of scenarios and data types. Two relevant cases will be presented. One case deals with Voluntary Geographic Data collected using Open Data Kit (ODK), which can be considered as a citizen science type application. This application is titled Policrowd2.0 and provides tools for customizing visualization, mashing up with additional features and transacting with ODK connected servers. The second case is a dynamic social media data viewer implementing Call Detailed Records (CDR) for telecommunication networks, and used for visually sensing the environment at the regional level. Telephone calls, SMSs, tweets and other internet exchanges can be visualize in their temporal evolution, comparing different days, analyzing the data as a whole or evaluating the details for just a few cells.

The latest version of NASA World Wind (WebWorldWind) has made it possible for a whole new suite of applications for managing and sharing spatial data. Apps built with this web version are as ideal for immediate social media type activity as to more sophisticated urban infrastructure management such as climate research, disaster response and all types of navigation, from personal directions to industrial supply chain, to aeronautics and satellite tracking.

For this presentation, we will display the current state-of-the-art for virtual globe technology by demonstrating several applications using NASA WebWorldWind. This version of NASA WorldWind opens up exciting new possibilities for virtual globe applications. As  WorldWind Java, WebWorldWind is modular componentry for easy development of unique virtual globe applications experienced via a web page. WebWorldWind is an application component, not an app in itself. It is written in JavaScript and provides the ‘real world’ geographic context for spatial data and information visualization, providing a rich set of shapes and graphics primitives WebWorldWind also provides platform independence and accommodates any number of data types including: GeoTIFF, KML, Collada, NITF, PNG, Shapefile, GeoRSS, RPF, JPEG'(+2k), GML, DWG, VPF, GeoJSON, DTED, NMEA, et al.

Web WorldWind runs on any platform via a browser, i.e., Internet Explorer, Firefox, Chrome and Safari. Features include, 3D virtual globe, 2D map with multiple projection choices (Mercator, Polar, UPS, Equirectangular), imagery and elevation import, extensible, data retrieval (via REST, WMS, WCS, WFS, Bing, User Defined), Placenames, KML import, Shapefile import, decluttering, measurement, accurate line-of‐sight, subsurface visualization, and more.

Earth Observation satellites continuously observe the annual and inter-annual dynamics of the Earth’s vegetation phenology - an important variable characterizing plant traits and indicating environmental change. As a key Essential Biodiversity Variable metrics like the start and duration of the growing period provide valuable information to environmental experts, scientists and citizens.

Satellite data on environmental change are freely available on global level and are integrated in the open data initiative of the European Commission and the Group on Earth Observation (GEO). The MySeasons mobile App is part of the MyGEOSS project on innovative apps in environmental and social domains and addresses the mobile integration of optical satellite time series data for vegetation phenology monitoring. Users are invited to browse a 15 years global archive of satellite data – derived from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) onboard TERRA/AQUA for individual phenological monitoring purposes. Global MODIS time series data with a temporal resolution of 16 days are acquired using the application programming interface of the Google Earth Engine.

MySeasons also integrates crowed sourcing of phenological observations by the individual user. Both - crowed sourced observations by the citizen scientists and satellite-derived phenological metrics can be analysed and collected to increase the understanding on global environmental change.

Users of MySeasons make use and support the land and climate change observation services of the European Union’s Earth monitoring programme Copernicus. The mobile application allows using time series of the Enhanced Vegetation Index (EVI) for analyzing the start, length and end of the growing season, and long term vegetation trend analyses. Phenological metrics are automatically derived using the TIMESAT software. With the app users can participate in building and establishing an in-situ database for phenological information and compare their individual observations with satellite measurements. The user can explore thematic maps related to phenology and have access to a 15 year time series of global vegetation dynamics.

This paper aims to present a new concept of using mobile information technologies to connect state-of-the-art satellite time series techniques and terrestrial phenological observation approaches within a citizen observation tool. The integration of in-situ and earth observation measurements for vegetation monitoring and the knowledge transfer of using operational satellite observations in the MySeasons for a broad range of users app project will be presented.

There are more and more data being measured by different Earth Observation satellites around the world. Ever-increasing amounts of these data are made publicly available free of charge, presenting new challenges and opportunities for their visualization. Data and metadata need to be presented to the public in an engaging way and the final visualization needs to be both appealing and interactive.

In this project we focus on density maps displaying the earth coverage built from data taken by different missions and sensors over time. This allows mission managers, stakeholders and the general public to have a punctual overview of how and which different earth observation missions are providing useful information to scientific communities for the different areas of our planet. In this context, it is also important to understand changes over time. We must allow users to “play” with such information along the time dimension to see how the focus areas of earth observations evolve over months and years. Users must be able to see the changes in coverage, both for a single mission and for combinations of multiple active missions. This implies the need for displaying aggregated data in different levels of detail allowing users to easily move from a global perspective to regional and local details.

Earth coverage density maps will be created on the fly by interacting with some of the main ESA data and metadata sources, including the Sentinel Hub for Copernicus data and the FedEO federated catalogue for other ESA and Third-Party missions. An application using such maps intended for smartphones and tablets will be developed, to take advantage of the ease of use of such devices and to allow understanding by both expert and non expert stakeholders. As the tendency for scientific dissemination is to leverage more and more on apps for mobile devices we also believe that implementing the application for mobile environments will increase its visibility and impact. The application is built on top of open source technologies like WebWorldWind and will be provided as Open Source. Density maps will be displayed over a 3D globe providing means for full interaction: panning, zooming, etc. Users will be able to select single or multiple missions: in the latter case density maps will be presented using 3D shapes allowing to easily understand both the aggregated amount of observation done by the different missions and the detail of data provided by the single mission. Future evolutions of the application will provide additional viewpoints by including the possibility to filter the visualization through different criteria such as, for example, the typologies of services which make use of the actual data.

The use of synthetic aperture radar (SAR) data in applications is today still limited due to the lack of appropriate, end-user oriented data representation and information extraction algorithms that are repeatable and transparent in terms of free parameters to be set. In fact, some of the issues to be faced in representing and extracting semantic from such data are:

Grayscale displaying: humans usually deal with color images, which lead to a fast searching and comprehension of data;

Speckle: SAR images are corrupted by noise due to random combination of sub-resolution backscattering contributions. This phenomenon prevents the correct interpretation of data and is also a source of distortions of the information content; 

Geometrical distortions: SAR side-looking geometry induces geometrical distortions such as layover, foreshortening and shadowing which alter the appearance of features in detected images;

Image pdf: SAR images are characterized by an exponential pdf, which prevents their displaying on a linear scale;

Radiometric distortions: dealing with multitemporal data, radiometric calibration is mandatory for a correct evaluation of the scene dynamics.

The role of SAR community should be to mitigate these problems, getting data closer to the end-user community. In this paper, we present a new framework for model-based color representation of multitemporal SAR data, whose products have the characteristics of interpretability and manageability necessary to be attractive for the end-user community. The objective is to lower the expertise required to manage and interpret SAR products. This should get SAR data closer to end-users and make them able to interpret correctly images and perform basic operation on data only using colors, which is the common practice to interact with data acquired in the visible spectrum.

The proposed processing consists of three stages: i) a pre-processing phase aimed at geometrical/temporal/radiometric calibration, ii) a decomposition of the image information on a proper base and iii) a fusion of the three channels. The proposed framework has been designed in order to satisfy the requirements of reproducibility, automation and adaptability and is characterized by two branches providing two categories of products we named as Level-1α and Level-1β.

These product have a different rationale. In fact, Level-1α products are bi-temporal, i.e. built using two intensity images and their interferometric coherence. Therefore, they are particularly oriented toward change detection applications (see Figure 1 of the extended abstract). Level-1β products aim at providing synthetic information about a time-series since their bands are constituted by temporal variability indicators. Therefore, in this case the objective is to identify features based on their characteristic dynamics. The main characteristic of these products is that the association color-object is stable for variation of the scene and of the climatic condition, given a proper selection of the time series and of the images involved in the RGB composite.

Both Level-1α and Level-1β products are extremely versatile and can be exploited in several applications such as water bodies extraction, flooding mapping, classification and urban areas mapping.

References

[1] D. Amitrano, G. Di Martino, A. Iodice, D. Riccio, and G. Ruello, “A New Framework for SAR Multitemporal Data RGB Representation: Rationale and Products,” IEEE Trans. Geosci. Remote Sens., vol. 53, no. 1, pp. 117–133, 2015.

[2] D. Amitrano, F. Cecinati, G. Di Martino, A. Iodice, D. Riccio, and G. Ruello, “Sentinel-1 Multitemporal SAR Products,” in IEEE Geoscience and Remote Sensing Symposium, 2015.

The Persistent Scatterer Interferometry (PSI) is a widely used technology that tackles the study of ground motion using Synthetic Aperture Radar (SAR) data. PSI results consist on a series of scatterers over each SAR frame, which can range from 50*50 to 250*250 km2. This kind of processing is performed with a stack of images (dates). Monitoring and historical studies can cover from 20 dates up to hundreds, with a common spatial resolution starting at 3 metres, results provide millions of measurements with their associated quality values and temporal series. In summary, the visualization and analysis of PSI results become unbearable for existing GIS applications. A solution to this problem can be working on small subsets of the area of interest, although global analysis is compromised, and increases the difficulty to conduct spatio-temporal analysis.

A web application has been designed and developed, to ease the exploitation of PSI results online, including the fast visualization of large amounts of data, spatio-temporal filtering toolbars, animated time series and cross-sections on the fly, statistical analysis, layers management and export capabilities with high-resolution base maps.

The application is based on the lastest web technologies, using Python and NodeJS for the backend and HTML5, CSS3 and AngularJS. The use of non-relational databases for storing data allows the application to be flexible, compatible with different data sources, and with the necessary scalability to handle the continuous incremental nature of data, existing in PSI monitoring. While GeoJSON is used for storing data, the application accepts different formats by making use of GDAL libraries.

This paper shows the functionalities and architecture of the WebGIS application developed by Altamira Information over the PSI results over the city of Barcelona, for the years 2008-2010 and with TerraSAR-X Stripmap and 3-meter spatial resolution. The different deliveries, parameters, and filtering toolbars are explored, together with the demonstration of intensive data exploitation, including the cross-section application based on custom algorithms, information sharing mechanisms among users of the interface, and export data in shapefile, kmz, and png for map generation.

As it can be seen, the technology presented can be adapted to numerous sources of remote sensing data, filling the gap between existing technologies: traditional GIS but also web mapping services, and remote sensing user needs.