An open-source mobile geospatial platform for agricultural landscape mapping: a case study of wall-to-wall farm systems mapping in tonga

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences(2022)

引用 0|浏览5
暂无评分
摘要
Abstract. Pacific Island Countries (PICs) such as Tonga rely on services provided by agricultural landscapes to support livelihoods, economic activity, and food security. At the same time these landscapes face numerous pressures and risks from factors such as environmental, climate, and market changes. Accurate, spatially explicit, and timely datasets on agricultural systems is required for an array of land and agricultural management tasks. Here, the development of an open-source ICT system providing geospatial tools for landscape monitoring, developed in collaboration between geospatial researchers and Tonga’s Ministry of Agriculture, Food, and Forests (MAFF), is presented. The agile and iterative ICT for Development (ICT4D) framework used to elicit MAFF’s requirements for the ICT system is presented alongside the system architecture and case studies demonstrating its impact. A key goal of the ICT4D development process was to develop an ICT system to support MAFF from transitioning from infrequent, paper-based farm surveys to coordinated, large-team, spatially explicit digital surveying augmented by tools for analysis and reporting. The mature system architecture which includes QField and QFieldCloud, and new open-source geospatial components for spatial visualisation, analysis, and reporting is presented. Case studies where the mature tool was used by MAFF’s are presented and include: (1) how a large survey team captured spatial data for >11,000 farms for country-wide farm monitoring; and (2) how the tool informed MAFF’s landscape decision making including recovery efforts after the 2022 Hunga Tonga–Hunga Ha’apai volcano explosion. The success of the tool demonstrates the importance of stakeholder engagement and the great potential for open-source geospatial tools for landscape management and disaster response in PICs.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要