Spatial information is vital to effectively plan for roads, landings and harvesting. Information can be obtained in the form of topographical maps, aerial imagery and bio-physical maps like soils, geology and rainfall. Aerial imagery refers to images taken from any flying object (drone, plane or satellite). Spatial information is obtained from processing data from various sources.
Harvest and road planners have more geospatial information available than ever before. It is a rapidly growing area for both data collection and post-processing. The once common techniques of using non-orthorectified stereo photo pairs and a stereoscope to see a three-dimensional view of the topography are now seldom used.
Aerial imagery, from a source such as Google Maps or GoogleEarth, is now at the simple end of tools that range from proprietary aerial imagery in visible, infrared, or multi-spectral ranges. Such software also gives a 3-D view from various aspects, as well as checks for physical features such as buildings or powerlines.
LiDAR based topographical map with 5 m contour, showing waterways (blue lines), stand boundaries (red lines) and planned landings (green rectangles)Light detection and ranging (LiDAR) is now widespread, and allows high resolution digital terrain maps and 3-D models to be generated at relatively low cost. Satellite imagery can also be used by forestry companies to get regular forest image updates, to measure operational and forest changes in real time. Regional councils also have another source of good information – orthorectified photo coverage.
Most purchased imagery, or that sourced through Land Information New Zealand (LINZ) or regional councils, will be orthorectified, distortion corrected and positioned to a grid system. However, in-house imagery from an unmanned aerial vehicle (UAV), such as a drone, needs to be orthorectified so it can be overlain with other spatial data.
For all geospatial imagery, consideration should be given to the date of acquisition because landscape features change over time. However, planners should also consider historic geospatial data sources like old photos, as these can be an excellent resource and as useful as recent photos. Aerial photographs taken without extensive tree cover can often be sourced for plantation forests that were originally planted on ex-farmland. These generally provide the best indication of visible ground features, such as bluffs, wetlands and suitable river crossings. For example, identifying pre-planting slip locations for areas in the East Coast and Hawkes Bay with extensive post-cyclone Bola erosion. UAVs or drones are also rapidly becoming geospatial data collectors, supporting in-field planning and road inspections.
A topographical map is defined as a map showing natural and/or physical features of a landscape, including altitude contours. Topographical maps at 1:50,000 scale with 20 m contour intervals are freely available to download from NZ Topo Map (www.topomap.co.nz). Many forest owners have produced higher resolution maps of their forests with 5 m contour intervals using aerial imagery and control points, but this is becoming superseded by LiDAR, which can produce maps with 1 m contour intervals. For forest areas without landowner LiDAR, coverage, check with the regional council as many are starting to make larger scale LiDAR data available.
A common database for topographic and other information layers is available from LINZ (www.linz.govt.nz/data/linz-data/elevation-data). It is important to identify how the topographic data was compiled, as the contour details and other map features are only as accurate as the base data from which the map was originally drawn. For example, working with 1:50,000 maps using 20 m contour data is reasonable for the initial feasibility plan, as well as for checking how the overall roading network will work. A final roading plan should be made on 1:5,000 scale maps.
New technologies are rapidly making road design easier and more accurate. Most planners can now modify maps using Geographic Information Systems (GIS) to display the information pertinent for their required map. For example, the map above overlays the planned landing areas with a LiDAR shaded map not only to see the existing road network but also existing slip areas.
The level of LiDAR detail can be incredible, even with full canopy closure. For example, old farm tracks that might not be readily identified on the ground may be clearly visible. If they are on the desired grade, they can often easily be upgraded to a forest road.
The availability of quality terrain data allows the forest engineer to undertake more extensive and useful preliminary planning in the office before heading into the field. LiDAR generated contour data, and GIS road location spatial data, can be uploaded into engineering road design software programmes. This means alternative road routes (and their feasibility for large lengths of road), construction costs, earthworks volumes, and the environmental impact can be assessed rapidly for each option. The final road design can be downloaded into GPS units for field layout. This can potentially lead to the forest road location being pegged out without standard surveying equipment.
This map shows a combination of geospatial elements, including the harvest setting boundaries, the road, waterways, native vegetation and the landing (red dot).Other spatial data is essential to help develop comprehensive plans. These can include the NES-PF ESC (erosion susceptibility classification) and fish spawning layers, property boundaries, hydrology (waterways), ground cover, existing roads, buried services and features such as overhead transmission lines, and archaeological sites. Soil maps are a useful resource as they show soil types and soil properties (soil pH, textures, organic matter, depths of horizons etc). Many soil maps have been published accompanied by a large compendium of soil descriptions and characteristics. The most readily available database is hosted by Landcare Research at smap.landcareresearch.co.nz/. The database is being updated through extensive field work and validation. In some regions there is excellent detail available, other regions are still being worked on and still have very broad basic details.