|Paper title||Web-based applications to visualize and query time series of lake water quality maps for SIMILE project|
|Form of presentation||Poster|
Remote sensing-based products are widely used for scientific research and synoptical monitoring of water resources. The use of satellite-based products provides a less costly and time-consuming alternative to traditional in-situ measurements. The conservation of water resources poses a challenge on multiple levels, including local institutions, authorities, and communities. Therefore, the monitoring of water resources, in addition to provide a scientific output, should devote its efforts also to the publication and sharing of the results. Therefore, communication, coordination, and publishing of data are essential for preserving the water ecosystems.
This work presents the design and implementation of two components of the IT infrastructure for supporting the monitoring of lake water resources in the Insubric area for SIMILE ("Integrated monitoring system for knowledge, protection and valorisation of the subalpine lakes and their ecosystems"; Brovelli et al., 2019) Italy-Switzerland Interreg project. SIMILE monitoring system benefits from various geospatial data sources such as remote sensing, in-situ high-frequency sensors, and citizen science. The infrastructure uses and benefits from Free and Open-Source Software (FOSS), open data and open standards, facilitating the possibility of reuse for other applications.
The designed applications aim at enhancing the decision-making process by providing access to remote-sensing based lake water quality parameters maps produced under the project for Lakes Maggiore, Como and Lugano. The satellite monitoring system for SIMILE considers estimating different water quality parameters (WQP) using optical sensors. The analysed water quality parameters maps include the concentration of Chlorophyll-a (CHL-a), Total Suspended Matter and Lake Surface Water Temperature (LSWT). Each product is delivered with a specific spatial and temporal resolution depending on the sensor used for the monitored parameter. The WQPs maps production frequency is affected by factors such as the revisit time of the sensor over the study area and the cloud coverage. CHL and TSM are monitored with the ESA Sentinel-3A/B OLCI (Ocean and Land Colour Instrument) whose spectral bands include the visible and infrared portions of the spectrum. LSWT is monitored using the NASA Landsat 8 TIRS (Thermal Infrared Sensor). Sentinel-3 A/B offers a daily revisit time over the study area with a resolution of 300m, which, on average, allows for the production of CHL-a and TSM maps weekly. Landsat-8 satellite provides a higher spatial resolution of 30m, but with a revisit time of 16 days, then, on average, allows for the production of LSWT maps monthly.
The archiving and sharing of the WQPs maps are of interest to the SIMILE project. In particular, the project promotes the publication of the data as time series to monitor the evolution of the different WQP maps. WQP maps can support the assessment of various processes taking place inside the aquatic ecosystems, for example, the eutrophication level in a water body from CHL-a. Sediment concentration, which can be deduced from TSM maps can influence the penetration of light, ecological productivity, and habitat quality, and can harm aquatic life. LSWT maps allow exploring lake dynamics processes such as sedimentation, concentration of nutrients and the presence of aquatic life, but also the temporal variability of temperature due to climate change (Lieberherr et al, 2018).
Two web applications have been designed aiming at simplifying the data-sharing process and allowing for the interactive visualization of the WQPs maps. The first one is built on GeoNode, to upload, edit, manage and publish the WQP maps. GeoNode is an open-source Geospatial Content Management System that eases the data-sharing procedures. The second one, is a WebGIS application that aims at providing a user-friendly environment to explore the different WQPs maps. The WebGIS benefits from OGC standards, such as the Web Mapping Service (WMS), to retrieve and display the maps published on the GeoNode application. The publication of the datasets through OGC standards is possible thanks to the GeoServer instance working on the back-end of the GeoNode project.
SIMILE WebGIS goal is favouring the visualization and query of lakes WQP as time series. For this reason, it was possible to exploit the raster data format support available into the data-sharing platform. Indeed, GeoNode permits the upload of raster data in GeoTIFF format, taking advantage of the data storage system implemented by GeoServer. Note that GeoServer provides additional multidimensional raster data support (such as image mosaics and NetCDF), which enables the storage of the collection of datasets with a time attribute. Nonetheless, GeoNode does not support the multidimensional raster data formats, and using them would imply the need of direct interaction with the remote server hosting GeoServer. The interaction with the remote server represents a barrier to the data sharing workflow (due to additional File Transfer Protocols to send the data to the server). The GeoTIFF format does not provide a time attribute. In order to overcome this limitation and allow the management of time series, a naming convention has been introduced and the timestamp is provided in the layer name. Next, for matching layer typologies, it was possible to build groups of layers by extracting unique dates values. The constructed layers groups used the collection event of "LayerGroups" for the "Layer" object in OpenLayers Library. Thus, the time series visualization for WQP in the WebGIS was possible while maintaining GeoNode as a suitable tool for the publication of raster data.
Therefore, the WQP maps are provided with a naming convention which describe the sensor used for the acquisition, the product typology, the coordinate reference system of the map, and the timestamp of the image acquisition, in order to facilitate the integration of maps in the database and the metadata compilation. An example of the naming convention is “S3A_CHL_IT_20190415T093540”. Here, the file name contains information corresponding to the coordinate reference system (“IT”, WGS84 – UTM32N), the sensor involved in the acquisition of the imagery (“S3A”, ESA Sentinel3A-OLCI), the product’s typology (“CHL”, Chlorophyll-a), and the timestamp of the retrieval of the imagery (“20190415T093540”, April 15, 2019, at 09:35:40), all separated by an underscore. The application has been designed to let web client users display the layers in time, taking advantage of the map timestamp. Moreover, the naming convention supported the styling of the layers and the metadata preparation and display.
The web-based application implemented in this work provides a mechanism for sharing and monitoring water quality parameters maps. The infrastructure implements two different applications focusing on two different audiences. First, the collaborative data-sharing platform (GeoNode) that targets the map producers allowed to upload and manage the lake water quality maps (following the naming convention for the products). Second, the WebGIS aims at becoming an open application for the exploration of the products uploaded into the GeoNode platform. The WebGIS provides an interactive application to display the lake water quality products as time series in a user-friendly environment. The components inside the WebGIS provide users to control the visibility of the layers, query maps in time, explore the layers metadata and customize the base map background. Data accessibility for water quality parameters enables the monitoring and assessment of the water bodies health. Moreover, the monitoring of the water resources is mandatory for guaranteeing the livelihood of the nearby communities depending on its consumption and quality.
Brovelli, M. A., Cannata, M., & Rogora, M. (2019). SIMILE, A GEOSPATIAL ENABLER OF THE MONITORING OF SUSTAINABLE DEVELOPMENT GOAL 6 (ENSURE AVAILABILITY AND SUSTAINABILITY OF WATER FOR ALL). ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4/W20, 3–10. https://doi.org/10.5194/isprs-archives-XLII-4-W20-3-2019
Lieberherr, G.; Wunderle, S. Lake Surface Water Temperature Derived from 35 Years of AVHRR Sensor Data for European Lakes. Remote Sens. 2018, 10, 990. https://doi.org/10.3390/rs10070990