The past 50 years have seen rapid changes across landscapes, with forests and wetlands alike converted for agricultural use or, conversely, re-afforested due to policy or economic drivers. While official land use maps often exist, they only provide a static, point in time snapshot that quickly becomes dated. This limits their use for agencies responsible for environmental monitoring and protection in near real-time applications.
The recently completed EnviroSatTools project filled this gap by developing a collaborative satellite data workspace with New Zealand regional councils. Over two years, the project consortium led by Dr Rogier Westerhoff of GNS Science developed targeted modules to support regional councils in monitoring processes, including land-use change, wetland and flood plain dynamics. See below to hear Dr Westerhoff discussing the project outcomes with the council’s scientists.
As a collaborative project, importance was placed on data accessibility, processing capacity and ease of data sharing and knowledge. The project adopted Google’s open access cloud-computing platform Google Earth Engine (GEE). The GEE framework stores satellite data in the cloud and creates an environment that allows the joint development of processing routines (scripts) and applications accessed through a web browser.
Indufor’s resource monitoring team, led by Dr Pete Watt, was responsible for developing the forest and land-use change module. Andrew Holdaway, Indufor’s Geospatial Application Developer comments, “when we started developing the applications, we took care to understand how regional council experts would like to interact with satellite data and how best to support its use”.
As an introduction, Indufor developed and released several demonstration applications. The first, a simple satellite image viewer to allow users to view and compare satellite images across landscapes.
Building from this point, Indufor released a land cover tracking application called Stand Tracker. The application analyses satellite images captured every five days in near real-time. Users can query these images over any location or time period to visualise changes in vegetation cover.
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