https://hdl.handle.net/1721.1/147051 Mon, 06 Apr 2026 20:36:00 GMT 2026-04-06T20:36:00Z http://dspace.mit.edu:80/bitstream/id/81c6464a-4f92-4170-b84f-d6e8858f8bd4/ https://hdl.handle.net/1721.1/147051 https://hdl.handle.net/1721.1/160030 Architecting a decision support system for continuing supervision of commercial in-space servicing Smith, Jacqueline H.; Jah, Moriba; Wood, Danielle The rapid development of in-space servicing technology and other novel space capabilities requires robust and transparent governance frameworks to ensure long-term space sustainability and adherence to international regulations, notably Article VI of the Outer Space Treaty. Article VI requires that signatory states provide continuing supervision over non-governmental space activities, a mandate becoming increasingly more challenging to fulfill due to the accelerating pace of commercial space innovations. In previous work published by the authors, a Systems Architecture Framework analysis investigated the governance of in-space servicing in the U.S. and the corresponding Stakeholder Need misalignments with current authorization and supervision processes. The initial research provided insights into the apparent Need for a Decision Support System addressing the practical challenges faced in the operational supervision of in-space servicing activities. In response, this paper roadmaps the application of the Environment-Vulnerability-Decision-Technology (EVDT) systems engineering framework into the realm of space sustainability challenges, such as for authorization and supervision of commercial in-space servicing. Originally conceived by the Space Enabled research group at MIT’s Media Lab, the EVDT framework has demonstrated its effectiveness in facilitating sustainable development decision-making through analysis of complex socio-environmental-technical systems across various terrestrial applications. Historical uses of EVDT span across aiding flood resilience in Indonesia, promoting mangrove preservation in Brazil, managing invasive plant species in Benin, revitalizing cranberry wetlands in the U.S., analyzing environmental injustice in prison landscapes, and urban planning strategies during the pandemic. Most recently, the inaugural adaptation of the EVDT framework to the space domain shows potential to enhance collision avoidance operation decisions for a Stakeholder within NASA. This paper proposes the expansion of the EVDT framework to broader space sustainability challenges, focusing on continuing supervision as the primary use-case, where this prototype’s capability to model and analyze hypothetical commercial in-space satellite servicing missions under U.S. jurisdiction will demonstrate the potential of EVDT to enhance space situational awareness (SSA) and space domain awareness. These operations are critical for collision prediction and consequence, risk assessment, and the implementation of sustainable operational practices. We introduce the plan for developing the Continuing Supervision EVDT software prototype, using a MATLAB-based method characterized by a modular architecture to facilitate integration and extension of functionality. The paper also introduces terminology, key concepts, objectives, and the use of the Systems Architecture Framework method within the EVDT software development process. The software design enables Stakeholders to custom-build and adapt their models to different space sustainability scenarios, improving code reuse, reducing development time, and simplifying interactions for external users and future space-based EVDT projects. The implementation of this Decision Support System has the potential to influence the authorization and supervision of novel space missions and the evolution of supporting SSA technologies, ultimately contributing to the responsible and sustainable use of the space environment. It helps ensure compliance with international space laws and promotes sustainability by equipping Stakeholders with software toolsets capable of simulating the orbital dynamics of spacecraft through mission phases. The paper also envisions the extensive application of the EVDT framework to an array of other space sustainability challenges, such as environmental sensitivity, debris mitigation, resource utilization, and planetary protection. Ultimately, the expansion of the EVDT framework into the domain of space sustainability will empower policymakers, commercial space operators, and other Stakeholders with an adaptive simulation tool that not only conforms to the current space governance systems but also flexibly shapes to future space policies, encouraging responsible stewardship over the space environment. Sat, 07 Jun 2025 00:00:00 GMT https://hdl.handle.net/1721.1/160030 2025-06-07T00:00:00Z https://hdl.handle.net/1721.1/159377 Preliminary analysis of in-space servicing governance and the challenge of continuing supervision Smith, Jacqueline H.; Jah, Moriba; Wood, Danielle The emergence and proliferation of In-space Servicing, Assembly, and Manufacturing (ISAM) technology holds far-reaching implications, particularly considering the current era of rapid advancements in space technology, escalating commercialization of space activities, and novel utilization of the space domain including in cislunar space. This paper presents the preliminary findings of a multi-year research study undertaking a comprehensive analysis of commercial in-space servicing governance employing the Systems Architecture Framework (SAF) methodology. The focal points of investigation for this study are on understanding the various dimensions that shape the policy and regulation of the commercial in-space servicing ecosystem, encompassing environmental factors and sociopolitical considerations, from the perspective of U.S. Government Stakeholders. Governance of commercial in-space servicing is a complex system in the sense that it is composed of interacting components whose collective behavior and properties emerge from the relationships between these entities. Through the use of SAF, the analysis of this complex socio-environmental-technical system spans these elements: understanding system Context, analyzing Stakeholders and their Needs and Objectives, identifying system Forms and Functions, proposing new Forms and Functions, and Monitor and Evaluate the system. From the SAF analysis, several major findings and recommendations emerge. First, shortcomings currently exist in achieving meaningful continuing supervision by the Stakeholders of commercial in-space servicing activities. Article VI of the Outer Space Treaty of 1967 mandates the continuing supervision of all non-governmental space activities by the authorizing nation yet lacks a clear definition for the term continuing supervision. Based on analysis from SAF, this paper introduces tools for addressing ambiguity by providing an interpretation of continuing supervision that can be applied into the operational environment, metrics for evaluating the outcomes, and technical challenges and recommendations for continuing supervision in cislunar. This paper also introduces a recommendation for a Decision Support System (DSS) for aiding U.S. Government Stakeholders in authorizing and supervising commercial in-space servicing activity based on findings from expert interviews. The authors propose that the Environment-Vulnerability-Decision-Technology (EVDT) systems engineering framework developed by the Space Enabled Research Group offers a promising methodology for developing such a DSS as future work. The framework allows system designers to confirm they are addressing Stakeholder Needs identified via the Systems Architecture Framework and combining a variety of sources of information to shape policy. Notably, the EVDT framework has been previously demonstrated as a tool for decision-making in space traffic management applications for a U.S. Stakeholder. Future work of this research study will investigate prototyping a new space-based EVDT model for specific use-cases and exploring a sensitivity analysis of the space environment to certain in-space servicing activities. Ultimately, this research lays a robust foundation for a deeper understanding of the current and future U.S. governance of commercial in-space servicing, resonating with the ongoing discourse concerning the long-term sustainability, mission authorization, and continuing supervision of novel space activities. The insights derived from this multi-year analysis contribute valuable guidance for policymakers, industry leaders, and academic researchers, offering a Stakeholder-focused perspective informing strategic decisions with socio-environmental-technical implications at the forefront. Sat, 17 May 2025 00:00:00 GMT https://hdl.handle.net/1721.1/159377 2025-05-17T00:00:00Z https://hdl.handle.net/1721.1/147102 The Environment-Vulnerability-Decision-Technology Framework: A Process for Developing Multi-Disciplinary Decision Support Systems for Sustainable Development Applications Sun, 18 Sep 2022 00:00:00 GMT https://hdl.handle.net/1721.1/147102 2022-09-18T00:00:00Z https://hdl.handle.net/1721.1/146601 Systems engineering applied to urban planning and development: A review and research agenda Reid, Jack; Wood, Danielle Mon, 19 Sep 2022 00:00:00 GMT https://hdl.handle.net/1721.1/146601 2022-09-19T00:00:00Z https://hdl.handle.net/1721.1/146403 Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability Gaikwad, Snehalkumar `Neil'; Iyer, Shankar; Lunga, Dalton; Yabe, Takahiro; Liang, Xiaofan; Ananthabhotla, Bhavani; Behari, Nikhil; Guggilam, Sreelekha; Chi, Guanghua Sun, 14 Aug 2022 00:00:00 GMT https://hdl.handle.net/1721.1/146403 2022-08-14T00:00:00Z https://hdl.handle.net/1721.1/145948 Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning Gaikwad, Snehalkumar 'Neil'; Lunga, Dalton; Iyer, Shankar; Bondi, Elizabeth Sat, 14 Aug 2021 00:00:00 GMT https://hdl.handle.net/1721.1/145948 2021-08-14T00:00:00Z https://hdl.handle.net/1721.1/135540.2 The large footprint of small-scale artisanal gold mining in Ghana Barenblitt, Abigail; Payton, Amanda; Lagomasino, David; Fatoyinbo, Lola; Asare, Kofi; Aidoo, Kenneth; Pigott, Hugo; Som, Charles Kofi; Smeets, Laurent; Seidu, Omar; Wood, Danielle Renee Gold mining has played a significant role in Ghana's economy for centuries. Regulation of this industry has varied over time and while industrial mining is prevalent in the country, the expansion of artisanal mining, or Galamsey has escalated in recent years. Many of these artisanal mines are not only harmful to human health due to the use of Mercury (Hg) in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal gold mines in Ghana from 2005 to 2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007 to 2017. A combination of machine learning and change detection algorithms were used to calculate different land cover conversions and the timing of conversion annually. Within the study area of southwestern Ghana, our results indicate that approximately 47,000 ha (⨦2218 ha) of vegetation were converted to mining at an average rate of ~2600 ha yr-1. The results indicate that a high percentage (~50%) of this mining occurred between 2014 and 2017. Around 700 ha of this mining occurred within protected areas as mapped by the World Database of Protected Areas. In addition to deforestation, increased artisanal mining activity in recent years has the potential to affect human health, access to drinking water resources and food security. This work expands upon limited research into the spatial footprint of Galamsey in Ghana, complements mapping efforts by local geographers, and will support efforts by the government of Ghana to monitor deforestation caused by artisanal mining. Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/1721.1/135540.2 2021-01-01T00:00:00Z https://hdl.handle.net/1721.1/138106.2 Vida Decision Support System: An International, Collaborative Project for COVID-19 Management with Integrated Modeling Reid, Jack B.; Lombardo, Seamus; Turner, Katlyn; Zheng, Maggie; Wood, Danielle R. 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. Fri, 01 Oct 2021 00:00:00 GMT https://hdl.handle.net/1721.1/138106.2 2021-10-01T00:00:00Z https://hdl.handle.net/1721.1/132918 Inclusive Design of Earth Observation Decision Support Systems for Environmental Governance: A Case Study of Lake Nokoué Ovienmhada, Ufuoma; Mouftaou, Fohla; Wood, Danielle Renee Earth Observation (EO) data can enhance understanding of human-environmental systems for the creation of climate data services, or Decision Support Systems (DSS), to improve monitoring, prediction and mitigation of climate harm. However, EO data is not always incorporated into the workflow for decision-makers for a multitude of reasons including awareness, accessibility and collaboration models. The purpose of this study is to demonstrate a collaborative model that addresses historical power imbalances between communities. This paper highlights a case study of a climate harm mitigation DSS collaboration between the Space Enabled Research Group at the MIT Media Lab and Green Keeper Africa (GKA), an enterprise located in Benin. GKA addresses the management of an invasive plant species that threatens ecosystem health and economic activities on Lake Nokoué. They do this through a social entrepreneurship business model that aims to advance both economic empowerment and environmental health. In demonstrating a Space Enabled-GKA collaboration model that advances GKA's business aims, this study first considers several popular service and technology design methods and offer critiques of each method in terms of their ability to address inclusivity in complex systems. These critiques lead to the selection of the Systems Architecture Framework (SAF) as the technology design method for the case study. In the remainder of the paper, the SAF is applied to the case study to demonstrate how the framework coproduces knowledge that would inform a DSS with Earth Observation data. The paper offers several practical considerations and values related to epistemology, data collection, prioritization and methodology for performing inclusive design of climate data services. Wed, 01 Sep 2021 00:00:00 GMT https://hdl.handle.net/1721.1/132918 2021-09-01T00:00:00Z https://hdl.handle.net/1721.1/131218 Using earth observation data to inform community management of invasive plants and traditional fishing practices on Lake Nokoué in Benin Ovienmhada, Ufuoma; Fatoyinbo, T; Lagomasino, D; Mouftaou, F; Ashcroft, E; Lombardo, Seamus(Seamus Joseph Holt); Wood, Danielle The research explores an Earth Observation (EO) application with the enterprise Green Keeper Africa (GKA) based in Cotonou, Benin, that addresses the management of an invasive plant species that threatens economic activities such as fishing, transportation and irrigation. GKA pays local community members to harvest the water hyacinth and transform it into a product that absorbs oil-based waste. The EO application is an online observatory and decision support tool that utilizes satellite, aerial and ground data to map the location of the water hyacinth and a fish farming practice known as “acadja” over time, providing valuable information for government, private and public users. The acadja analysis is relevant due to the adverse effects on water quality that the practice results in. This paper is a follow up on the work presented in the 2019 contribution to IAC session B1.5 by the authors. New research in this paper includes (i) improved and validated remote sensing algorithms for monitoring water hyacinth extent, (ii) trend analysis and forecasting of water hyacinth growth with other environmental data sets, (iii) improved and validated remote sensing algorithms for identifying and quantifying acadja and (iv) analysis of water quality parameters describing the coastal ecosystem. Wed, 01 Jan 2020 00:00:00 GMT https://hdl.handle.net/1721.1/131218 2020-01-01T00:00:00Z https://hdl.handle.net/1721.1/129598 Interactive Model for Assessing Mangrove Health, Ecosystem Services, Policy Consequences, and Satellite Design in Rio de Janeiro Using Earth Observation Data Reida, Jack B.; Wood, Danielle There is an increasing need for tools to translate Earth Observation (EO) data into societally rele- vant metrics to inform human decision-making. To address this need, we present a multi-disciplinary, interactive modeling framework to advance ecological forecasting and policymaking using EO data. This framework will integrate four model components into one tool: Earth Science, Social Impact, Human Behavior and Satellite Design. The capabilities provided by this framework will improve the management of EO and socioeconomic data in a format usable by non-experts, while harnessing cloud computing, machine learning, economic analysis, complex systems modeling, and model-based systems engineering. This paper presents a prototype that demonstrates the viability of the framework via a case study: the mangrove forests in the Guaratiba area of Rio de Janeiro. These mangroves are vulnerable due to urbanization and rising sea levels. They provide a variety of ecosystem services, including serving as a mechanism for carbon sequestration, supporting subsistence shing, preventing coastal erosion, and attracting an ecotourism industry. The case study of mangrove and community health in Rio de Janeiro demonstrates all four model components. The Earth Science Model builds upon work by NASA biospheric scientists to use EO data, cloud computing and machine learning to track mangrove extent, health, and vulnerability over time for a 600 km2 area, as well as work by the Espa co research group at the Universidade Federal do Rio de Janeiro on the local mangrove ecosystem. To create the Human Decision Making model, we have partnered with Instituto Pereira Passos (the data science o ce of the Rio de Janeiro municipal government) to understand the policy history and socioeconomic factors. To build the Social Impact model, we are collaborating with ecosystem services economists to explain how policies impact mangrove health and how mangroves impact socioeconomic wellbeing. The Satellite Design Model accounts for the types of data collection used by policy makers since 1985. Through such collaborations, we are able to build an integrated, interactive model that policymakers can use to assess mangrove health, ecosystem services value, and policy consequences. The model helps answer such questions as: (a) What is the state of the mangroves over time? (b) How are human communities impacting the mangroves? (c) what is the value of the mangrove ecosystem services to human communities? and (d) what policies can improve human and mangrove outcomes? This case study is demonstrative of the viability of a similar approach for ecosystems around the world. Thu, 01 Oct 2020 00:00:00 GMT https://hdl.handle.net/1721.1/129598 2020-10-01T00:00:00Z https://hdl.handle.net/1721.1/128378 Decision Support Model and Visualization for Assessing Environmental Phenomena, Ecosystem Services, Policy Consequences, and Satellite Design Using Earth Observation Data Reid, Jack Burnett; Wood, Danielle Renee Mon, 02 Nov 2020 00:00:00 GMT https://hdl.handle.net/1721.1/128378 2020-11-02T00:00:00Z https://hdl.handle.net/1721.1/127489 Earth observation technology applied to environmental management : a case study in Benin Ovienmhada, Ufuoma. Coastal ecosystems provide habitats for a wide variety of plant and animal species. They also provide many benefits to humans in the form of transportation, subsistence, and economic opportunity. These benefits are at risk due to both anthropogenic and naturally-occurring environmental harms. Effective management of these environmental harms is important to protect the ecological balance of an ecosystem and the benefits that humans derive from them. Decision Support Systems (DSS) enabled by environmental and socioeconomic data can help inform effective management. However, data cannot always be incorporated into the decision-making workflow for a multitude of reasons from awareness, to interpretability, accessibility and cost. The research outcomes presented in this thesis address processes that (1) enable a stakeholder to set priorities for the design of a DSS and (2) utilize earth observation technologies to enable low cost data collection of parameters relevant to a stakeholder. These processes are studied through a case study on Lake Nokoué in Benin Republic with the stakeholder Green Keeper Africa (GKA), a social enterprise located in Benin. Lake Nokoué faces several challenges with sustainable water management due to an invasive plant species known as the water hyacinth, and anthropogenic pressure from population growth and lake-dependent economic activities. Earth Observation technologies are applied to demonstrate (1) a method for detection and long-term analysis of water hyacinth growth trends, (2) a method for detection of a traditional fish farming practice, (3) a method for long-term water quality sensing and (4) methods for validation of all data results. The results of this thesis show progress towards creating a multi-data stream DSS that can be used by GKA, government, and community members to engage with the Lake in a manner that preserves the lake's health while protecting the ecosystem services of the surrounding human populations. Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, May, 2020; Cataloged from the official PDF of thesis.; Includes bibliographical references (pages 147-153). Wed, 01 Jan 2020 00:00:00 GMT https://hdl.handle.net/1721.1/127489 2020-01-01T00:00:00Z https://hdl.handle.net/1721.1/125741 Monitoring water-related ecosystems with Earth observation data in support of Sustainable Development Goal (SDG) 6 reporting Hakimdavar, Raha; Hubbard, Alfred; Policelli, Frederick; Pickens, Amy; Hansen, Matthew; Fatoyinbo, Temilola; Lagomasino, David; Pahlevan, Nima; Unninayar, Sushel; Kavvada, Argyro; Carroll, Mark; Smith, Brandon; Hurwitz, Margaret; Wood, Danielle Renee; Schollaert Uz, Stephanie Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future. Fri, 01 May 2020 00:00:00 GMT https://hdl.handle.net/1721.1/125741 2020-05-01T00:00:00Z https://hdl.handle.net/1721.1/121527 Combining Social, Environmental and Design Models to Support the Sustainable Development Goals Reid, Jack Burnett; Zeng, Cynthia; Wood, Danielle Renee There are benefits to be gained from combining the strengths of modeling frameworks that capture social, environ- mental and design-based considerations. Many of the impor- tant challenges of the next decade lie at the intersection of the natural environment, human decision making and the design of space technology to inform decision making. There are 17 Sustainable Development Goals outlined by the United Nations through 2030. Several of these Sustainable Development Goals can be addressed by asking: 1) What is happening in the natural environment? 2) How will humans be impacted by what is happening in the natural environment? 3) What decisions are humans making in response to environmental factors and why? and 4) What technology system can be designed to provide high quality information that supports human decision making? The answers to these questions are often interrelated in complex ways; thus it is helpful to use a framework from complex systems to integrate these questions. Within the list of Sustainable De- velopment Goals, several fit the three questions above, including #2 Zero Hunger, #6 Clean Water and Sanitation, #13 Climate Action, #14 Life Below Water, and #15 Life on Land. This paper presents a research agenda to apply environmental modeling, complex systems modeling, and model-based systems engineering to inform the design of space systems in support of the Sustainable Development Goals. This work builds on previous research in the following areas: 1) physics-based en- vironmental modeling; 2) complex systems modeling to simu- late human decision making using agent-based models; and 3) model based systems engineering to inform the architecture of satellites or space-enabled data systems. This paper presents a review of the state of the art, shows examples of how these methods have been combined to inform space system design and presents a future research agenda. As an example, the paper discusses a project related to Sustainable Development Goal #15 to design an earth observation system using space- based and ground-based data collection regarding an invasive plant species in Benin, West Africa. In this example, insights are needed regarding natural variables (i.e. salinity, temperature and turbidity of local waterways), social variables (i.e. economic impact of the invasive plant on local communities), and design variables (i.e. the technical performance of existing imagery satellites and in-situ sensor networks). Fri, 01 Mar 2019 00:00:00 GMT https://hdl.handle.net/1721.1/121527 2019-03-01T00:00:00Z