Technical Session - November 8, 2012 Integrating Multisource Data AVI, LiDAR, Multisource and Multi-date Digital Photography Derek Fisher & John Nash 1
Traditional (Hardcopy) Inventory Softcopy Inventory 4-Band Digital Photography Leaf-Off Photography LiDAR Data Retrofitting Attributes Field Calibration Closing Remarks Hardcopy Prints Often Black and White Scales 1:20,000 to 1:30,000 Most often Leaf-on Conventional (film) Aerial Photography Capture Stand Delineation Orthophoto Transfer Digitizing Field Calibration Interpretation Keypunching Quality Control (QC) Geo-database 2
Computer Datem/Purveiw 3D Viewer Conventional (film) or Digital Aerial Photography Capture Stand Delineation Field Calibration ArcMap MicroStation QC Interpretation (QC) Microsoft Access Geo-database form Orthophoto Transfer Keypunching Digitizing Quality Control (QC) Geo-database (QC) The Softcopy process has revolutionized how we do inventories and is the single most important inventory advancement made over the last ten years. The computerized 3-d component of softcopy has been around for along time. However, it s only been through the recent advancement of computer power that we have been able to use the technology in a productive way. Everything else I am going to show you as advancements in Forest Inventories is possible mainly because of the Softcopy process. 3
Higher resolution scales (detailed inventories can be done more cost effectively) Real time quality control Enables the integration of other useful digital technologies (e.g. LiDAR, earlier inventories etc.) Facilitates production of seamless inventories mc12sw10 759 Township Boundary mc12sw10 456 Polygon Boundary 220 mc12sw10 110 mc12sw10 Production considerations using traditional inventory methods required that polygons be numbered (assigned unique Stand-IDs) according to legal (township) boundaries; with polygons having the same attributes but different stand identification numbers. 4
mc12sw10 110 Softcopy now allows inventories to be numbered exclusively within FMA boundaries Digital aerial photography is the latest technological advancement that has impacted inventories. Computer Datem/Purveiw 3D Viewer Aerial Triangulation (AT) Scanning Conventional (film) Digital 5
Allows us to capture multi-spectral photography (RGB and IR) and load it into softcopy in a more cost-effective way. Digital photography provides as good if not better resolution than conventional and there is potential it will provide far better resolution in the future. Although not fully realized at this time, we should start seeing the direct cost of digital photo-acquisition go down once aerial-photography companies have covered the capital cost of digital cameras and mastered the new technology. 4-Band imagery (RGB-IR)enables better tree species identification and soil-moisture detection. 6
Leaf-off photography enables us to identify conifer tree species that would otherwise be invisible due to the covering properties of deciduous tree species 7
AVI Call: md18aw10 / No Understory 8
Leaf-Off photography is not new of course but its use in the past (using traditional inventory methods) has been limited because of the trade off were, although we can see the conifer, we cannot see the deciduous adequately to assign an accurate crown closure. Thus, in mixedwoods we often had to fly both leafon and leaf-off photography for the same area in order to capture both coniferous and deciduous trees adequately, an often very expensive endeavor and so done on a very limited scale. From a forest management perspective, this had left us in a bit of quandary trying to properly manage for both coniferous and deciduous interest in the province. Softcopy now allows us to use leaf-off photography exclusively. Because we now have greater amplification capabilities with our imagery we are now able to obtain accurate estimates of deciduous cover in leaf-off conditions. 9
Deciduous Crowns Within the last five years the forest industry has seen LiDAR data go from a buzz word to a fully integrated information source used in operational planning and forest inventories. Specific to Forest inventories, LiDAR data provides very accurate and consistent Stand Height and Crown Closure information. 10
We have used LiDAR data in inventories in four ways: 1.Stand delineation 2.Height and crown closure estimation 3.Ecosite interpretation 4.Quality Control 25m C Aw8Sw2 11
NOTE: Each Color represents a distinct height class (meters) Original call: 25m C Aw8Sw2 23m C Aw8Sw2 28m C Aw8Sw2 12
13
We can create algorithms for LiDAR data that calculate stand height and crown closure. Compare the LiDAR derived values with interpreted values. Comparisons that are extremely different are examined for interpreter errors. This can be done in real-time (during interpretation) or after interpretation is complete. 14
With the advent of softcopy we realized the opportunity to retrofit previous inventories instead of starting from scratch. Retrofitting is the act of re-interpreting the previous delineation. Thus, only disturbance line-work is updated. Line-work in non disturbed areas are untouched and only the stand attributes are recollected. This has two clear benefits: 1. Time (cost) savings 2. Improved attribute accuracy Our first attempts at retrofitting were done in tw0 FMU s in the province. RESULT Cart before the Hoarse The original line-work was done hardcopy: using photo-prints and orthophoto transfer. The ability to zoom at different scales in softcopy meant that we could now define stand boundaries at higher resolutions. Thus, when we loaded the original hardcopy line-work into softcopy there were obvious offsets with the stand boundaries that we could not ignore. In addition, we had LiDAR data that we wished to use to provide better delineation around stand height. 15
NOTE: the original AVI (blue polylines) have been retained as a reference 16
Stand Height (is now more accurate) Before LiDAR interpreted heights were more variable Interpreted Height Range After LiDAR interpreted heights are more consistently accurate Interpreted Height Range 17
Crown Closure: we can now go to 10% cover classes with more confidence than before Crown Closure Class Labels Crown closure Crown closure (% class) Database Numeric Label Database (AVI)Character label 10 6-19% 1 A 20 20-29% 2 A 30 30-39% 3 A 40 40-49% 4 B 50 50-59% 5 B 60 60-69% 6 C 70 70-79% 7 C 80 80-89% 8 D 90 90-100% 9 D Vegetation species identification 18
Understorey: We can now identify and attribute understory trees with more confidence. Also better interpret more than one understory layer Moisture Regime: we can estimated higher resolution moisture regimes with more confidence Moisture Regime Ecosite Moisture class Moisture Regime AVI Moisture Very Xeric 1 Dry d Xeric 2 Dry d Subxeric 3 Dry d Submesic 4 Mesic m Mesic 5 Mesic m Subhygric 6 Mesic m Hygric 7 Wet w Subhydric 8 Wet w Hydric 9 Aquatic a AVI 2.1.1 Database Character label 19
Density (Stems/Ha): We can provide reasonable estimates of density, which we couldn t even image before. Stand Origin: is one important AVI attribute that has not seen any significant improvement from these new technologies 20
The new technologies should not be used to replace field calibration. Photography is still the primary source of interpretation and all photography, whether conventional or digital, are affected by capture-date, time of day, temperature and atmospheric conditions. Thus, colour, tonal and texture expression will vary from flight to flight. Interpreters still need to have real ground truth information to provide confidence with what is seen in the photography. From a technological standpoint, AVI has seen a revolution over the last 10 years. The refinement of the softcopy process has been the single most important advancement. LiDAR data, colour-ir and leaf-off photography have significantly improved our interpretation accuracy with many AVI attributes. Digital photography has the potential to increase photoresolution and/or decrease the cost of photo-acquisition. Once the first population of softcopy inventories are completed we will be able start thinking about retrofits, potentially further decreasing the cost of inventories. Field calibration is still vital to the AVI process. 21