Using a collaborative information and communications technology for development (ICT4D) process, we are developing open-source applications to map diverse landscapes and seascapes.
This project is funded by the Australian Centre for International Agricultural Research (ACIAR) and is a collaboration between stakeholders in Fiji, Tonga, Australia, and New Zealand.
In Pacific Island Countries, the environmental resources that support livelihoods are distributed across landscapes in a mix of spatial patterns. Capturing this spatial detail in landscape use is important to inform landscape management that is sensitive to these livelihood dependencies.
This research is using a collaborative software development methodology (ICT4D) to:
Map landscapes with mobile GIS.
Server-side apps and databases to sync data collected on mobile devices.
Use dashboards to analyse and visualise landscape data collected in-the-field.
Use satellite images and machine learning to monitor inter-annual landscape dynamics.
Understanding links between livelihoods, landscapes, and environmental stressors in Pacific Island Countries.Livelihoods and Landscapes
Examples of how geospatial applications developed through this project are being used in Fiji and Tonga.Use Cases
We develop training materials and deliver workshops to build the capacity of landscape stakeholders to use GIS applications to collect geospatial data and support landscape decision making and management.
All training materials and tutorials used in these workshops are freely available online.
We have run training sessions and workshops with officials from government ministries, NGOs, and other landscape stakeholders. Workshops covered the following tools and topics.
using Google Earth Engine, Sentinel-2 data, and machine learning to generate land cover maps
using QField to collect geospatial data in the field and map agricultural and forest landscapesQField tutorials
using spatial dashboards to process and visualise data collected in the field using mobile GISmap.landscape dashboard
Datasets and publications generated through this project will be posted to the Pacific Data Hub.
All software developed through this project will be published to our GitHub organisation page.