Integrating indigenous knowledge and state-of-the-art Earth observation solutions for the Sendai framework implementation

PurposeIndigenous peoples represent one of the most vulnerable groups and need access as well as hands-on experience in the use of emerging Earth observations (EO)-based DRR solutions at the community level, while balancing this learning with traditional indigenous knowledge (IK). However, complicating any engagement between EO and IK is the reality that IKs are diverse and dynamic, with location-specific relevance and accuracy. Additionally, the COVID-19 pandemic caused complex risks and cascading effects for which the world was not prepared. Thus, there is a need to examine the lessons learned and motivate emerging EO-based innovations and demonstrations related to DRR and climate change adaptation.Design/methodology/approachHence, this study aims to undertake an in-depth assessment of IK related to DRR covering relevant UN instruments and provides state-of-the-art of opportunities presented by EO-based tools and solutions.FindingsThe overall research strategy was designed to integrate key components of IK for DRR in a coherent and logical way, with those offered by the EO technology developers and providers. There are several EO tools accessible that are relevant to integrate IK and complement DRR. The study examined and identified challenges and barriers to implement workable and replicable EO solutions in pursuit of resilience.Originality/valueThe key findings of this study will help create a balanced approach by acknowledging the importance of IK for DRR with co-development, co-creation and use of culturally relevant EO data and tools for sustainable innovation, capacity building and youth empowerment. The technological inequalities appear to be growing, and it would be challenging to meet the Sendai Framework indicators.

Geospatial, earth observations and statistical data integration in the Cortés department, Honduras

Proper territorial data management is critical for territorial planning projects, research, innovation, and the appropriate follow-up to act for the well-being of populations. A multidisciplinary team of professionals established a pilot project named Cortes Data Hub (Centro de Datos de Cortés). It presents several dashboards that show official statistics on the energy sector, mapping the region's energy demand, data on COVID-19 cases and vaccination rates by municipality or department, and a project using Google Earth that combines post-Eta and Iota observations and a social media campaign for disaster awareness and for the promotion of activities to develop tourism in the San Manuel Municipality. This pilot project shows the importance to observe and monitor various key environmental, health, and socioeconomic data. This will help improve initiatives for local development, disaster prevention and control, and the promotion of the One Health approach. The challenges to overcome are the quality and timing of data. Training more academics, government teams, and decision-makers in the use of new tools for data integration with earth observations are important for the Cortés department's development. © 2022 IEEE.

Towards a New MAX-DOAS Measurement Site in the Po Valley: NO2 Total VCDs

Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments are used worldwide to retrieve pollutant information from visible (VIS) and ultra-violet (UV) diffuse solar spectra. A similar instrument, able to meet the Fiducial Reference Measurements for DOAS (FRM4DOAS) standard requirements, is not yet present in the Po Valley (Italy), one of the most polluted regions in Europe. Our purpose is to close this gap exploiting the SkySpec-2D, a FRM4DOAS-compliant MAX-DOAS instrument bought by the Italian research institute CNR-ISAC in May 2021. As a first step, SkySpec-2D was involved in two measurement campaigns to assess its performance: the first one in August 2021 in Bologna where TROPOGAS, a research-grade custom-built MAX-DOAS instrument is located;the second one in September 2021 at the BAQUNIN facility at La Sapienza University (Rome) near the Pandora#117 instrument. Both campaigns revealed a good quality of SkySpec-2D measurements. Indeed, good agreement was found with TROPOGAS (correlation 0.77), Pandora#117 (correlation 0.9) and satellite (TROPOMI and OMI) measurements. Having assessed its performance, the SkySpec-2D was permanently moved to the “Giorgio Fea” observatory in San Petro Capofiume, located in the middle of the Po Valley, where it has been continuously acquiring zenith and off-axis diffuse solar spectra from the 1 October 2021. Nowadays, its MAX-DOAS measurements are routinely provided to the FRM4DOAS team with the purpose to be soon included in the FRM4DOAS validation network.

A Geospatial Artificial Intelligence and satellite-based earth observation cognitive system in response to COVID-19.

The pandemic emergency caused by the spread of COVID-19 has stressed the importance of promptly identifying new epidemic clusters and patterns, to ensure the implementation of local risk containment measures and provide the needed healthcare to the population. In this framework, artificial intelligence, GIS, geospatial analysis and space assets can play a crucial role. Social media analytics can be used to trigger Earth Observation (EO) satellite acquisitions over potential new areas of human aggregation. Similarly, EO satellites can be used jointly with social media analytics to systematically monitor well-known areas of aggregation (green urban areas, public markets, etc.). The information that can be obtained from the Earth Cognitive System 4 COVID-19 (ECO4CO) are both predictive, aiming to identify possible new clusters of outbreaks, and at the same time supervisorial, by monitoring infrastructures (i.e. traffic jams, parking lots) or specific categories (i.e. teenagers, doctors, teachers, etc.). In this perspective, the technologies described in this paper will allow us to detect critical areas where individuals can be involved in risky aggregation clusters. The ECO4CO data lake will be integrated with ad hoc data obtained by health care structures to understand trends and dynamics, to assess criticalities with respect to medical response and supplies, and to test possibilities useful to tackle potential future emergencies. The System will also provide geographical information on the spread of the infection which will allow an appropriate context-specific public health response to the epidemic. This project has been co-funded by the European Space Agency under its Business Applications programme.

Earth System's Gatekeeping of "One Health" Approach to Manage Climate-Sensitive Infectious Diseases.

Global response to climate-sensitive infectious diseases has been uncertain and slow. The understanding of the underlying vulnerabilities which forms part of changes created by forces within the Earth system has never before been critical until the coronavirus disease 2019, "COVID-19" pandemic with the initial developmental phase linked to weather elements and climate change. Hence, the heightened interest in climate-sensitive infectious diseases and GeoHealth, evident in the renewed calls for "One Health" approach to disease management. "One Health" explains the commonality of human and animal medicine, and links to the bio-geophysical environment, yet are at crossroads with how forces within the Earth system shape etiologies, incidences, and transmission dynamics of infectious diseases. Hence, the paper explores how these forces, which are multistage and driven by climate change impacts on ecosystems affect emerging infectious diseases, leading to the question "what drive the drivers of diseases?" Three questions that challenge broad theories of Earth system science on boundaries and connectivity emerged to guide study designs to further interrogating disease surveillance and health early warning systems. This is because, climate change (a) drives prevailing biological health hazards as part of forces within the Earth system, (b) shifts disease control services of ecosystems and functioning to effectively regulate disease incidence, and (c) modifies pathogen-species hosts relationships. Hence, the need to rethink pluralistic concepts of climate-sensitive diseases in their infection and management from a GeoHealth perspective, which "One Health" potentially conveys, and to also maintain ecosystem health.

Air and Water Quality Improvement during COVID-19 Lockdown

COVID-19 pandemic forced many countries to adopt lockdown measures, temporarily closing factories, diminish maritime traffic and reducing the mobility of people in the cities. Analysis from the Tropospheric Monitoring Instrument (TROPOMI) and Ocean and Land Colour Instrument (OLCI) on board Europe's Sentinel-5P, 3A/B respectively, for the first wave of the COVID-19, have shown a substantial improvement in air and water quality. More specifically, since COVID-19 lockdown until the end April, Lisbon and Porto were at their lowest PM10 levels of about 20% and a drop of 33% in 2 years, while Madrid had a significant drop since lockdown with vales significantly below 2018 levels but still close to 2019 levels. In terms of NO2 levels, Lisbon had an historical minimum of the last 2 years, dropping more than 40% during most of April 2020. Finally, Madrid had 2-year lowest level of more than 30% since lockdown. Concerning the water quality in the Portuguese coastal waters, it was verified an increase in water transparency since confinement started until May, accordingly to the Total Suspended Matter (TSM) indicator. From February to March, March to April and April to May there was a reduction in TSM levels of 17%, 37% and 53% respectively.

Impact of COVID-19 on eLearning in the Earth Observation and Geomatics Sector at University Level

The COVID-19 pandemic has a high impact on education at many different levels. In this study, the focus is set on the impact of digital teaching and learning at universities in the field of Earth observation during the COVID-19 pandemic situation. In particular, the use of different digital elements and interaction forms for specific course types is investigated, and their acceptance by both lecturers and students is evaluated. Based on two distinct student and lecturer surveys, the use of specific digital elements and interaction forms is suggested for the different course types, e.g., academic courses could be either performed asynchronously using screencast or synchronously using web meetings, whereas practical tutorials should be performed synchronously with active participation of the students facilitated via web meeting, in order to better assess the student’s progress and difficulties. Additionally, we discuss how further digital elements, such as quizzes, live pools, and chat functions, could be integrated in future hybrid educational designs, mixing face-to-face and online education in order to foster interaction and enhance the educational experience.

COIVD-19 IMPACT MONITORING OF ECONOMIC ACTIVITIES

The COVID-19 pandemic has had substantial impacts on the Earth system and socioeconomic activities. Restrictions aimed at reducing the spread of COVID-19 by limiting human interaction have led to significant reductions in air pollution and CO2 emissions, improvement in water quality, changes in agricultural output, and changes in economic activity for certain industries such as airlines and shipping, among others [1, 2, 3, 4, 5]. Those economic impact assessment related information are made available on the trilateral COVID-19 Earth Observing Dashboard (https://eodashboard.org) [6]. The presented use cases in economic activities make full use of the combined satellites fleet of NASA, ESA and JAXA as well as the expertise of the Earth Observation community. © 2021 IEEE.

USING COPERNICUS SENTINEL MEASUREMENTS TO MONITOR COVID-19 IMPACT ON THE ENVIRONMENT

Since the onset of the COVID-19 pandemic in early 2020, many countries worldwide implemented a series of social distancing and containment measures as an attempt to limit its spread. Those measures have led to a significant slowing down of economic activities, drastic drops in road and air traffic, and strong reductions of industrial activities in nonessential sectors, which in turn affected atmospheric emissions and air quality worldwide. Concentrations of short-lived pollutants, such as nitrogen dioxide, are indicators of changes in economic slowdowns and are comparable to changes in emissions. Nitrogen oxides are mainly produced by human activity and the combustion of (fossil) fuels, such as road traffic, ships, power plants and other industrial facilities. Nitrogen Dioxide can have a significant impact on human health, both directly and indirectly through the formation of ozone and small particles. The Copernicus Sentinel-5P satellite nitrogen dioxide concentrations measurements have been used to investigate COVID-19 impact on air quality from space. Global maps of Copernicus Sentinel-5P tropospheric Nitrogen Dioxide measurements have been included – together with other Sentinel measurements – into an on-line tool (dashboard) to provide investigations/results about changes to the Earth environment caused by the COVID-19 pandemic to the public: race.esa.int. © 2021 IEEE.

JAXA’S EARTH OBSERVATION DATA ANALYSIS ON COVID-19

The COVID-19 pandemic has brought difficulties to our daily lives and caused various changes in socio-economic activities and the natural environment. To monitor and record the changes in socio-economic activities and the environment before and during the COVID-19 pandemic, JAXA has collaborated with NASA and ESA in developing a trilateral dashboard to provide socio-economic activities and natural environmental change information derived from earth observation data. JAXA also has analyzed Earth observation data, for example, ALOS-2, GCOM-C, GOSAT and GOSAT-2 and opened at a special website “JAXA for Earth on COVID-19” in the categories of airports, industry, shipping, agriculture, greenhouse gasses and water quality. © 2021 IEEE.

Vida Decision Support System: An International, Collaborative Project for COVID-19 Management with Integrated Modeling

The Vida Decision Support System (Vida) is an application of the Environment-Vulnerability-Decision-Technology (EVDT) integrated modeling framework specifically aimed at COVID-19 impact and response analysis. The development of Vida has been an international collaboration involving multidisciplinary teams of academics, government officials (including public health, economics, environmental, and demographic data collection officials), and others from six states: Angola, Brazil, Chile, Indonesia, Mexico, and the United States. These collaborators have been involved with the identification of decision support needs, the surfacing and creation of relevant data products, and the evaluation of prototypes, with the vision of creating an openly available online platform that integrates earth observation instruments (Landsat, VIIRs, Planet Lab's PlanetScope, NASA's Socioeconomic Data and Applications Center, etc.) with in-situ data sources (COVID-19 case data, local demographic data, policy histories, mobile device-based mobility indices, etc.). Vida both visualizes historical data of relevance to decision-makers and simulates possible future scenarios. The modeling techniques used include system dynamics for public health, EO-based change detection and machine learning for environmental analysis, and discrete-event simulation of policy changes and impacts. In addition to the direct object of this collaboration (the development of Vida), collaborators have also benefited from sharing individual COVID-19-related insights with the network and from considering COVID-19 response in a more integrated fashion. This work outlines the Vida Decision Support System concept and the EVDT framework on which it is based. The international team is using Vida to evaluate the outcomes in several large cities regarding COVID cases, environmental changes, economic changes and policy decisions. It provides an overview of the overlapping and diverging needs and data sources of each of the collaborating teams, as well as how each of those teams have contributed to the development of Vida. The current state of the Vida prototypes and plans for future development will be presented. Additionally, this work will discuss the lessons learned from this development process and their relevance to other integrated applications. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.

Mitigating the impacts of pandemics on the supply chain using Earth Observation Data

With sudden changes in demand for certain goods, strict border control, and movement restrictions, pandemics can cause an immense disruption of the supply chain especially as it pertains to sustenance goods and job security. The most important recommendations on how this disruption can be mitigated by applying Remote Sensing have been outlined. Earth Observation (EO) and ground data can be used to mitigate the effects of pandemics on the interconnected global and local supply chain;with the COVID-19 pandemic as a case study. The scope of effects by COVID-19 includes issues in the supply chain, operational logistics, and goods production. EO data can be used to track goods like foods, medical kits, hand sanitizers, etc. which in turn aids the reallocation of high-demand goods to areas with limited supply. Satellite-based communication channels will be useful for more remote areas. The supply chain deals with adequate production, the food security issues faced by a significant part of the world's population, can be tackled with an integrated approach. An integrated application of Remote Sensing, (IoT), and Machine Learning is proposed for food security. EO can be used for agricultural monitoring using GNSS coupled with available tools to assess and predict produce status. This is useful in disaster management during restrictions of pandemics;machine learning models can be deployed in conjunction with IoT systems to help with farm monitoring watering of crops using weather data, environment monitoring and fertilizer requirement reminders, and triggering of risk management protocols during disasters. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.

Lessons Learned in the Implementation of a Training Knowledge Management System for the SERVIR Network

The SERVIR program is a unique partnership between NASA, the U.S. Agency for International Development (USAID), focusing on building capacity to use Earth observations for addressing development challenges. In that context, between 2004 and 2020, the program delivered approximately 365 trainings to almost 10,000 professionals. More recently, between November 2020 and August 2021, the SERVIR network executed some 55 training events addressing SERVIR’s 4 priority thematic areas, and roughly a quarter of SERVIR trainings overall have focused on themes related to Ecological Forecasting. Due to the ongoing COVID-19 pandemic, almost four-fifths of recent training events have been virtual, with the remainder being in-person under limited circumstances. The large number of training events delivered represents both an opportunity and a challenge in terms of knowledge management. While the training materials developed can later be reused in other parts of the SERVIR network, prior to recently, the lack of a central repository for those materials has prevented wider dissemination and use. The recently developed Training Knowledge Management System (TKMS) is now becoming an integral part of the SERVIR Capacity Building Framework, supporting the exchange of resources and methods for conducting training activities across the network. This presentation focuses on the structure of this system, as well as on the anticipated benefits for the User Communities for Earth Observations of Terrestrial Systems.

A MULTI-AGENCY COVID-19 DASHBOARD WITH SATELLITE AIR QUALITY DATA

After the initial COVID-19 lockdown in China during February 2020, NASA and ESA pollution monitoring satellite instruments quickly detected significant decreases in NO2 over the Wuhan region. This change was attributed to reductions in fossil fuel combustion from motor vehicles and industrial activity. The same phenomenon, the satellite measured reduction of NO2, happened next in northern Italy, and then in New York City as the coronavirus spread to these areas. Satellite remote sensing of NO2 has been a useful tool to document changes in fossil fuel combustion and associated economic activity as various countries or regions have implemented lockdowns as a means to try to contain the spread of the virus. In April 2020, ESA reached out to NASA and JAXA and suggested working together to construct an Earth Observing (EO) Dashboard to provide the public with information on the changes occurring within the environment due to the pandemic that are observable from satellites. Satellite air quality data - specifically, tropospheric NO2 - was one of the primary Earth observations provided by this tri-agency COVID-19 satellite data dashboard. © 2021 IEEE.

THE COVID-19 EARTH OBSERVATION DASHBOARD: A NASA-ESA-JAXA COLLABORATIVE PRODUCT

The measures to contain the Covid-19 pandemic have had worldwide impacts on our environment, societies and economies. The 'COVID-19 Earth Observation Dashboard' (https://eodashboard.org) jointly developed by ESA, NASA and JAXA, combines a wealth of data from the tri-agencies' Earth-observing satellites to monitor the worldwide impacts of COVID-19. Developed in an Open Science framework, the dashboard is openly available to users worldwide and allows to track changes in air and water quality, climate, economic activity and agriculture. © 2021 IEEE.

CURRENT STATUS AND FUTURE PERSPECTIVES OF THE PRISMA MISSION AT THE TURN OF ONE YEAR IN OPERATIONAL USAGE

PRISMA, in orbit since March the 22nd 2019, opened the user access in spring 2020. After one year, many hundreds of users have gained the capability to program new acquisitions or download image products from the online archive containing more than 67k datasets, under a quasi-open & free data policy and licensing scheme. During this time frame and despite the COVID-19 related difficulties, PRISMA performed normal operations delivering not only nominal verified quality data to users but establishing collaborations with other space agencies, in order to enable and support synergies with other hyperspectral missions. This paper describes the mission and the results achieved in this first period of full operational usage. © 2021 IEEE.

RAPID ACTION ON COVID-19 AND EARTH OBSERVATION: AN INITTIATIVE FOR SOCIETAL INFORMATION ENABLED BY COPERNICUS SENTINELS DATA

This paper introduces the Rapid Action for Coronavirus and Earth Observation, a joint ESA-EC initiative to showcase applications of Earth Observation data derived from the Copernicus Sentinels and Third Party Missions to generate timely information with societal interest on the changes observed during the coronavirus pandemic lockdown and post lockdown periods on the European economy, agriculture, air quality, water quality and land. All indicators are based on Sentinel data and derived by capitalizing on EO Platforms and advanced Artificial Intelligence as a key enabler and accelerator of information discovery. Pioneering flexible and rapid development and deployment of the dashboard within EuroDataCube, the https://race.esa.int product is a fully Open Source solution developed using state-of-the-art technologies in an Open Science framework. Through coding competitions and coaching of citizen contributions, innovative community indicators were integrated using an Agile and Design Thinking Product Development Methodology. © 2021 IEEE

AIR QUALITY IMPROVEMENT DURING COVID-19 PANDEMIC: STUDY OF LAND AND MARITIME POLLUTION

COVID-19 pandemic forced many countries to adopt lockdown measures, temporarily closing factories, diminish maritime traffic and reducing the mobility of people in the cities. Analysis from the Tropospheric Monitoring Instrument (TROPOMI) on board Europe's Sentinel-5P and Copernicus Atmosphere Monitoring Service (CAMS), for the first wave of COVID-19 in 2020, have shown a substantial improvement in air quality. More specifically, since lockdown until the end of April, Lisbon and Porto were at their lowest PM10 levels in 2 years, while Madrid had a significant drop with values considerably below 2018 levels but still close to 2019 values. In terms of NO2 levels, Lisbon had an historical minimum of the last 2 years during most of April 2020 and Madrid had 2-year lowest level since lockdown. Finally, the commercial port of Ponta Delgada (São Miguel, Azores) had a decrease in cruise ship calls during the pandemic, which reduced the number of daily cases with significant NO2 concentrations, comparing to 2019. © 2021 IEEE

Assessing Urban Vulnerability to Flooding: A Framework to Measure Resilience Using Remote Sensing Approaches

Assessing and measuring urban vulnerability resilience is a challenging task if the right type of information is not readily available. In this context, remote sensing and Earth Observation (EO) approaches can help to monitor damages and local conditions before and after extreme weather events, such as flooding. Recently, the increasing availability of Google Street View (GSV) coverage offers additional potential ways to assess the vulnerability and resilience to such events. GSV is available at no cost, is easy to use, and is available for an increasing number of locations. This exploratory research focuses on the use of GSV and EO data to assess exposure, sensitivity, and adaptation to flooding in urban areas in the cities of Belem and Rio Branco in the Amazon region of Brazil. We present a Visual Indicator Framework for Resilience (VIFOR) to measure 45 indicators for these characteristics in 1 km2 sample areas in poor and richer districts in the two cities. The aim was to assess critically the extent to which GSV-derived information could be reliable in measuring the proposed indicators and how this new methodology could be used to measure vulnerability and resilience where official census data and statistics are not readily available. Our results show that variation in vulnerability and resilience between the rich and poor areas in both cities could be demonstrated through calibration of the chosen indicators using GSV-derived data, suggesting that this is a useful, complementary and cost-effective addition to census data and/or recent high resolution EO data. Furthermore, the GSV-linked approach used here may assist users who lack the technical skills to process raw EO data into usable information. The ready availability of insights on the vulnerability and resilience of diverse urban areas by straightforward remote sensing methods such as those developed here with GSV can provide valuable evidence for decisions on critical infrastructure investments in areas with low capacity to cope with flooding.

Is It All the Same? Mapping and Characterizing Deprived Urban Areas Using WorldView-3 Superspectral Imagery. A Case Study in Nairobi, Kenya

In the past two decades, Earth observation (EO) data have been utilized for studying the spatial patterns of urban deprivation. Given the scope of many existing studies, it is still unclear how very-high-resolution EO data can help to improve our understanding of the multidimensionality of deprivation within settlements on a city-wide scale. In this work, we assumed that multiple facets of deprivation are reflected by varying morphological structures within deprived urban areas and can be captured by EO information. We set out by staying on the scale of an entire city, while zooming into each of the deprived areas to investigate deprivation through land cover (LC) variations. To test the generalizability of our workflow, we assembled multiple WorldView-3 datasets (multispectral and shortwave infrared) with varying numbers of bands and image features, allowing us to explore computational efficiency, complexity, and scalability while keeping the model architecture consistent. Our workflow was implemented in the city of Nairobi, Kenya, where more than sixty percent of the city population lives in deprived areas. Our results indicate that detailed LC information that characterizes deprivation can be mapped with an accuracy of over seventy percent by only using RGB-based image features. Including the near-infrared (NIR) band appears to bring significant improvements in the accuracy of all classes. Equally important, we were able to categorize deprived areas into varying profiles manifested through LC variability using a gridded mapping approach. The types of deprivation profiles varied significantly both within and between deprived areas. The results could be informative for practical interventions such as land-use planning policies for urban upgrading programs.