JEO4C: Just Earth Observation for Conservation
Lead Research Organisation:
University of Manchester
Department Name: Environment, Education and Development
Abstract
Increased use of Earth Observation (EO) in biodiversity conservation comes with exciting opportunities, but also urgent social justice risks. EO data, derived from technologies such as satellites and drones, are becoming ubiquitous in how conservation actions are designed, managed, and monitored. But EO can also be a source of harm to those living in conservation landscapes. Examples include the use of drones to surveil local peoples without their consent, or when flaws and biases in EO datasets and analyses lead to decisions with harmful social consequences.
Understanding of how choices about and using EO can lead to (un)just conservation measures is constrained by several shortfalls in current knowledge. First, social science research on remote sensing in conservation is vastly outweighed by technical methods scholarship. Second, existing scholarship is skewed towards single-site case studies, and does not link choices made earlier in data supply chains (e.g., about data generation) to lived experiences of (in)justice. Third, there is very little research exploring how EO data justice could have different meanings to different people, and therefore of how to develop visions for more just data practices which recognise the values and worldviews of those impacted by data use. Finally, there has been little applied research focused on developing practical responses which can mitigate data injustices and advance socially just data practices.
JEO4C will transform understanding of the risks and benefits of increased use of EO in conservation, through a unique comparative analysis of conservation landscapes in the UK, Spain, Guatemala, and Kenya. Our project will proceed in three phases of revealing, reimagining, and transforming conservation 'datascapes' - the networks of people and organisations, datasets, and decisions which determine the consequences of data use for people living in conserved lands.
Central to our project is a process of co-development. We will work with landscape residents, conservation managers, and others who engage with data (including data generators, analysts, and users outside of case study areas) to explore sources and experiences of data (in)justice in current datascapes and to come up with usable and lasting solutions. To reveal current datascapes, we will use literature reviews, an in-landscape workshop, and a set of key informant interviews to understand who is involved in generating, analysing, and using the EO datasets associated with each case study landscape. To reimagine and transform the datascapes associated with each study landscape, we will work with landscape residents and members of the global conservation EO community to understand the notions of justice determining which aspects of EO use are seen as (un)just. Based on these insights, we will work with landscape residents to define and co-develop a set of outputs for each landscape which can mitigate the injustices identified through the research and advance data practices which support socially just conservation.
To scale up our results in ways which benefit people in conservation landscapes more broadly, we will carry out a comparative analysis of case study findings to understand why different patterns and experiences of data (in)justice emerge in different places. We will also convene a set of cross-landscape engagements, in which those working with and impacted by EO data in different contexts can engage in cross-contextual learning. Our comparative analyses will lead into a large-scale international workshop in which we develop a Just Conservation Datascapes Handbook and set of associated training materials. This international workshop will also act as the inaugural meeting for an ongoing EO Data Justice International Working Group hosted within the Global Land Program partnership. These international-scale outputs will ensure that the impact of this project outlasts the immediate project time horizon.
Understanding of how choices about and using EO can lead to (un)just conservation measures is constrained by several shortfalls in current knowledge. First, social science research on remote sensing in conservation is vastly outweighed by technical methods scholarship. Second, existing scholarship is skewed towards single-site case studies, and does not link choices made earlier in data supply chains (e.g., about data generation) to lived experiences of (in)justice. Third, there is very little research exploring how EO data justice could have different meanings to different people, and therefore of how to develop visions for more just data practices which recognise the values and worldviews of those impacted by data use. Finally, there has been little applied research focused on developing practical responses which can mitigate data injustices and advance socially just data practices.
JEO4C will transform understanding of the risks and benefits of increased use of EO in conservation, through a unique comparative analysis of conservation landscapes in the UK, Spain, Guatemala, and Kenya. Our project will proceed in three phases of revealing, reimagining, and transforming conservation 'datascapes' - the networks of people and organisations, datasets, and decisions which determine the consequences of data use for people living in conserved lands.
Central to our project is a process of co-development. We will work with landscape residents, conservation managers, and others who engage with data (including data generators, analysts, and users outside of case study areas) to explore sources and experiences of data (in)justice in current datascapes and to come up with usable and lasting solutions. To reveal current datascapes, we will use literature reviews, an in-landscape workshop, and a set of key informant interviews to understand who is involved in generating, analysing, and using the EO datasets associated with each case study landscape. To reimagine and transform the datascapes associated with each study landscape, we will work with landscape residents and members of the global conservation EO community to understand the notions of justice determining which aspects of EO use are seen as (un)just. Based on these insights, we will work with landscape residents to define and co-develop a set of outputs for each landscape which can mitigate the injustices identified through the research and advance data practices which support socially just conservation.
To scale up our results in ways which benefit people in conservation landscapes more broadly, we will carry out a comparative analysis of case study findings to understand why different patterns and experiences of data (in)justice emerge in different places. We will also convene a set of cross-landscape engagements, in which those working with and impacted by EO data in different contexts can engage in cross-contextual learning. Our comparative analyses will lead into a large-scale international workshop in which we develop a Just Conservation Datascapes Handbook and set of associated training materials. This international workshop will also act as the inaugural meeting for an ongoing EO Data Justice International Working Group hosted within the Global Land Program partnership. These international-scale outputs will ensure that the impact of this project outlasts the immediate project time horizon.
