Use of geospatial technologies in New Zealand’s plantationforestry sector – a decade of change

Abstract

Background: Geospatial technologies have emerged as powerful tools for optimising forest management, improving operational precision, and supporting data-driven decision-making. This study aims to understand the technologies adopted by the New Zealand plantation forest industry and identify any barriers to the uptake of geospatial tools. This is the third such study, following comparable surveys in 2013 and 2018.

Methods: An online survey was sent to 29 organisations in New Zealand’s forestry sector. Topics included organisation demographics, data acquisition, positioning technology, remote sensing technologies, software, and Artificial Intelligence (AI). Specifically, the survey focused on five remote sensing technologies: aerial photography, aerial videography, multispectral imagery, hyperspectral imagery, and LiDAR. Each section contained questions relating to the acquisition and application of the remote sensing technology and the software used for data processing. Questions were included to ascertain barriers to adoption. To identify changes in technology usage and uptake, results were compared to the 2013 and 2018 studies.

Results: Twenty-seven of the 29 queried organisations responded, resulting in a 93% response rate. Responding organisations managed 1,283,000 hectares (74% of New Zealand’s plantation forest estate), with estate sizes ranging from about 7,000 to 200,000 hectares. Data acquisition from online portals included aerial imagery (100%), property ownership data (96%), and elevation data (89%), primarily from the Land Information New Zealand (LINZ) Data Service. Global Navigation Satellite Systems (GNSS) technology was universally employed. All respondents acquired aerial photography. In addition, 67% acquired multispectral imagery, 4% acquired hyperspectral imagery, and 93% acquired LiDAR data. The AI topic was surveyed for the first time and the technology was used by 30% of respondents when working with geospatial data. The main barrier to using remotely sensed data was the lack of perceived benefits, while the primary barrier to AI adoption was a lack of staff knowledge and training. Except for hyperspectral imagery, all remote sensing technologies saw increased uptake since 2013. LiDAR experienced the largest growth, with uptake increasing from 17% in 2013 to 93% in 2023. ArcGIS remains the primary tool for geospatial analysis, used by 96% of respondents. Notably, the use of open-source software such as QGIS increased by 31% over the past decade.

Conclusions: This study demonstrated an overall increase in the usage of geospatial technology in the forestry sector. To promote further uptake, it is important not only to increase exposure to available tools and provide training, particularly on emerging technologies such as AI, but also to demonstrate the practical and economic value these technologies can offer.