Associate Professor Hone Morris

Our research will synthesize a Te Ao Maori landscape classification that can be directly integrated with existing geographical information systems (GIS). We will produce the first indigenous peoples, or Maori metric based Landscape Classification for New Zealand. Despite Maori expert elicitation, or interpretation, of landscape features being well recognised, coherent representation and display of this knowledge is significantly underdeveloped. Data of this kind is still treated as anecdotal or qualitative and, as a result, lacks impact in environmental management and decision-making. In stark contrast, the underlying descriptors and datasets used to classify NZ's environment for decision-making are all displayed in advanced GIS systems utilising cutting edge technology (e.g. geology (Qmap), soils (SMap), bio-diversity (Landcover Database/LENZ), and land use/capability (NZ Land Resource Inventory)). Many of the fundamental methods used to create these datasets are based on frameworks and criteria created through quasi-quantitative methods with no inclusion or recognition of matauranga Maori. This will be achieved through three components: 1. Development of Maori landscape classification criteria based on matauranga Maori, tikanga, kaitiakitanga and tohu taiao from leading Maori academics and Iwi partners 2. Generation of the first Maori Landscape Classification GIS (MLC-GIS) and database using new IT, GIS, remote sensing techniques and mathematical methods to visualise landscapes based on the developed criteria 3. Application of the MLC-GIS alongside existing environmental databases in new catchment management strategies Our research will use the Manawatu catchment to develop the protocols required to extend the proposed Maori Landscape Classification GIS to the whole of NZ. Globally this will be the first time such a dataset will be created. Additionally, new geospatial visualisation methods will be developed that will have significant impact.