BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-2024//talk//XGBABQ BEGIN:VTIMEZONE TZID:-03 BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:-03 TZOFFSETFROM:-0300 TZOFFSETTO:-0300 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-2024-XGBABQ@talks.staging.osgeo.org DTSTART;TZID=-03:20241206T163000 DTEND;TZID=-03:20241206T170000 DESCRIPTION:The lack of an integrated understanding of the connections betw een extreme weather events\, environmental degradation\, socioeconomic dis parities\, and their impacts on infectious disease outbreaks heightens the risk of disease spread. This issue is particularly critical in Latin Amer ica and the Caribbean (LAC) region\, where vulnerable communities have bee n more frequently affected by these events. The HARMONIZE project goal is to create digital toolkits that stakeholders in climate change hotspots ca n use to combine data about the environment\, climate and health cost-effe ctively to monitor and send out alerts about a set of diseases that are af fected by its effect.\n\nThis talk will give an overview of the Earth Obse rvation Data Cube tuned for Health Response Systems (EODCtHRS)\, an HARMON IZE Project component. The EODCtHRS presents a technical-scientific propos al termed HARMONIZE Instance composed of back/front-end solutions develope d using free and open-source software for integration and interoperability between specific sets of health\, environmental and climate data and the digital infrastructure of the Brazil Data Cube (BDC) project of the Nation al Institute for Space Research (INPE). \n\nThe development of this propos al was divided into four working streams\, Drone\, Health\, Climate\, and Data Science Environment modules. Furthermore\, we developed a custom vers ion of the web platform for data visualization and analysis of these sourc es based on BDC Explorer 3.0 (https://brazildatacube.dpi.inpe.br/portal/ex plore)\, which presents improved capabilities for discovering\, visualizin g\, and downloading data cubes from remote sensing images (https://brazild atacube.dpi.inpe.br/harmonize/dev/portal/explore). An Harmonize Instance A LPHA Version has been generated.\n\nThe core background of this platform i s the SpatioTemporal Asset Catalog (STAC) specification which defines a wa y to store and search data using spatial and temporal operations. The STAC enables the harmonization of data from different sources and maintains in teroperability between all system parts. The solution utilizes a suite of technologies from Python and R environments in addition to PostgreSQL/Pos tGIS and GeoServer needed to store and publish data collections.\n\nBelow we present a brief description of each working stream:\n\nModule 1 - Drone image: The main goal of drone image integration in the context of EODCtHR S is to provide a data infrastructure that meets the demands of health sur veillance\, especially in areas considered hotspots of climate change. Con sequently\, we started exploring the integration of the images generated b y fieldwork campaigns in some locations of Pará State. The processing of these images is based on auxiliary information (course angle and flight he ight) and EXIF and TIFF metadata tags to support the conversion of the raw images into Cloud Optimized GeoTIFF (COG) files ideal for integration wit h STAC specification implemented by BDC infrastructure. Besides that\, mos aics were created using the OpenDroneMap application. The Alpha version o f these data collections (scenes/mosaics) has been published as layers wit h GeoServer and associated metadata available in STAC catalogs.\n\nModule 2 - Health data: This module integrates health data for the EODCtHRS\, inc luding information from different stakeholders\, mainly Fiocruz's Health I nformation Laboratory (LIS) and the InfoDengue initiative. Both projects p roduce health indicators\, considering the impacts of environmental and cl imate change on the Brazilian population. The module also covers the devel opment of two main packages.\n\nThe first\, called EODCtHRS Health Indicat or Processing (EHIPR)\, was developed in Python to obtain health indicator s from CSV and Parquet files\, aggregate them spatially and temporally\, s patialize them and accommodate them on the HARMONIZE platform . Second\, c alled EODCtHRS Data PUblisher (EDPU)\, is a package developed in Python to publish the HARMONIZE datasets as a layer in GeoServer and its metadata i n STAC Catalog to make available at the HARMONIZE Explorer. All sources of data (drone images\, climate and health indicators) used the EDPU package to publish the ALPHA version of collections produced in the context of th e HARMONIZE project. \n\nModule 3 - Climate data: This module integrates c limatological data for EODCtHRS\, enabling direct query execution via acce ss interfaces\, and eliminating the need for data transfer. Within the pro ject's scope\, we consider products produced by Fiocruz team from the Cope rnicus Climate Change Service (C3S)\, which the European Centre implements for Medium-Range Weather Forecasts (ECMWF) ERA5-Land reanalysis dataset a nd available by the Center for Weather Forecasting and Climate Studies (CP TEC/INPE): SAMeT and MERGE.\n \nThis module developed the EODCtHRS R Clima te Processing Package (rclimpr) to generate climate indicators. The rclimp r uses scripts to extract indicators like temperature and precipitation fr om netCDF files through spatial and temporal aggregations (epidemiological weeks and months). It outputs raster files in COG format and vector forma ts like GeoJSON and Shapefile\, providing suitable data formats for analys is and visualization.\n\nModule 4 - The Geospatial Data Science Environmen t (BDC-Lab) aims to provide a set of geospatial data analysis tools integr ated with BDC data\, avoiding the necessity to download large amounts of E arth Observation data and allowing researchers to produce deep analysis us ing tools such as RStudio\, QGIS\, Metview\, VSCode and Jupyter Notebooks with several R and Python geospatial libraries pre-installed. Currently\, it is in an experimental phase\, where some users are testing its function alities and providing feedback for its improvement. \n\nThis talk proposal presents an overview of a software environment developed to harmonize Ear th observation\, environmental\, climate\, and health data aiming to provi de ways to visualize\, analyze\, monitor\, and alert for spreading disease s in climate change hotspots in LAC region. The development of the HARMONI ZE Instance has demonstrated the utility of geoservices and technologies\, with standard infrastructure and protocols\, as an effective way to harmo nize different data formats from diverse data sources in the health contex t.\n\nThe HARMONIZE project is financed by the Wellcome Trust (https://wel lcome.org) grant number 224694/Z/21/Z\, through the Foundation for Scient ific and Technological Development In Health (FIOTEC) ID Project: ICICT-0 02-FEX-22 and coordinated by Prof. Rachel Lowe leader of the Global Health Resilience Team in the Earth Sciences Department from Barcelona Supercom puting Center (BSC). DTSTAMP:20260428T053608Z LOCATION:Room IV SUMMARY:Integrating Earth Observation Data for Enhanced Health Response Sys tems: The EODCtHRS component of HARMONIZE Project - Karine Ferreira\, Marc os Lima Rodrigues\, Adeline Marinho Maciel\, Miguel Monteiro\, Gabriel San sigolo\, Yuri Domaradzki Moreira Nunes\, Ana Claudia Rorato Vitor\, Luana Becker da Luz\, Rachel Lowe URL:https://talks.staging.osgeo.org/foss4g-2024/talk/XGBABQ/ END:VEVENT END:VCALENDAR