Improving Forest Inventory and Analysis

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Improving Forest Inventory and Analysis Patrick Wong…not a forester.

Improving Forest Inventory and Analysis

---------------------------------What is Forest Inventory?

Answer: for GIS…start with a base map + forest polygon/attributes; or …a practise in thematic mapping; a gigantic learned photo interpretation and feature transferring/plotting exercise…

Thematic mapping – plotting special features on base maps Universal obstacle – base maps are: absent; old; …or sub-standard?

Air Photo 101

Photo Control

Pre-marked control point

P.U.G. [post-marked] image point

Map feature point

Stereoscopic Photo Interpretation

“Frame Camera” (FC) Scale = f/H-h, or f/subject distance Result: Displacement

Photogrammetry 101 : “Frame Camera” Short focal length

Long Focal Length

Flying Height/Air Base (H/B) = focal length/image base (f/b) or B/H = b/f

Mapping

Inventory Mapping – the Old-fashioned Way 1. Field reconnaissance …dead-reckoning air/ground calls. 2. Stereoscopic studies of aerial photos …maximum magnification ~3.5X 3. Annotating/inking polygons/features onto contact print …using rapid-o-graph pen 4. Approximate tree height and other measurements …using step-wedges, parallax bar, dot grids… 5. Approximate polygon transfers onto base maps …using Kail Plotter, epidiascope, zoom transfer-scope, camera lucida… 6. 2D digitizing of map manuscript …using CAD systems 7. Geo-processing 2D CAD files …Result: 2D GIS…at best

In 1957, Analytical Photogrammetry happened… a “frame” became the “bundle”

Film plane Lens

Perspective centre (X0 Y0 Z0)

Image space (x’ y’)

Terrain

Terrain space (X Y)

“Frame Camera” κ (kappa)

φ (phi)

P

What caused image parallax?

ω (omega)

“Frame Camera” (FC)

What is “modern” geo-referencing? (-x, y)

Geo-referencing

(-x, -y)

Fiducial Marks

=

Interior Orientation Optical Principal Point (0,0)

(x, y)

+

Exterior Orientation [X0, Y0, Z0; κ, φ, ω]

(x, -y)

…then, in 1992 ISPRS Congress, digital photogrammetry erupted…

Digital Photogrammetry products of

I.S.M. International Systemap Corp. Vancouver ∙ Canada

SysImage Digital Orthophoto System 1991 Digital image Analytical Photogrammetry DiAP System…DiAP Σ 1992 DiAP–Viewer, or DiAP Δ 1999

a Photogrammetric Workstation …the inside The Restitution System

– equations; no space rods, guide rails, cams…

The Stereo Viewing System

– monitor/LCD eyewear; no prisms, lenses, mirrors…

The Input System

– scroll-mouse; or 3D mouse, hand-wheels/foot-disc…

The Output System

– CAD systems; no pantographs, co-ordinatographs…

The Graphic User Interface (GUI)

– Windows OS; no command lines, keypads…

…the results Replicated all instruments still in used Eliminated all secretarial support Automated many repetitive tasks Eliminated stereo plotter “calibration” Eliminated the “afternoon shift” Reduced office rent Unconfined to “dungeons” Destroyed industry strategic balance Upset established “authorities”

…then in 2005, PurVIEW proclaimed…

what’s in PurVIEW? Restitution Stereo Viewing Input Output GUI

bypassed, using geo-referenced imagery 1,680 x 1,050 @ 120Hz…or higher scroll-mouse via Virtual-Z ™ Geodatabase-direct ArcMap

a product of

I.S.M. International Systemap Corp. Vancouver ∙ Canada

www.myPurVIEW.com

PurVIEW

x

Integration with other system

Geometry of digital photogrammetry

x x

State of the Art…and Technology in Aerial Base Mapping 1952 – 1995…

1992 – present

2006 – present

Mapping Processes

Analogue/Analytical

Digital

Post-digital

Control pre-marking

Field visitation

Field visitation

Control survey

Traversing/levelling

GPS observation

Aerial Imaging

Film imaging

Film imaging + kGPS

- Film processing

Chemical processing

Chemical processing

- Image reproduction

Photo-reproduction

Image Scanning

Aerial Triangulation

PUG/Comparator/Adjustment

Model orientation

Stereo plotter – trial & error

Terrain Modeling

Stereo plotter – mass point

Auto-correlation, RADAR…

Feature Plotting

Stereo plotter – pencil, CAD

Workstation CAD digitizing

Map fair-drawing

Drafting – inking, scribing

Map reproduction

Photo/litho reproduction

Ortho-projection

Optical rectifier/projector

Ortho-mosaic’ing

Controlled cut & paste

Ortho-composite

Complex photo-reproduction

IMU digital Imaging

Workstation – automated

CAD or GIS

Workstation + CAD

RADAR/LiDAR Arc-PurVIEW

Image Server

Workflow in extracting PurVIEW Source Data Traditional Methods

Aerial Imaging

Scanning

Aerial Triangulation

Photogrammetric DEM

Survey Control

Geo-referencing metadata

PurVIEW operation

Orthophoto processing

Other applications

1

“Photogrammetry is finished upon successful orientation of a stereo model …thereafter, only image interpretation and graphic documentation thereof remain… still requiring human experience and imagination…” Frank 2002, before edited by GIM for publication.

…what else is happening? Commercial Remote Sensing Digital aerial cameras Film archives Aerial [LiDAR or RADAR] DEM

pixel from 0.5m, not 60m! pixel from 0.03 ~ 0.6m scanned achieved 1st Order accuracy

Mapping

CAD- or GIS-direct

Orthophoto

digital by-product.

…what will be next? No aerial triangulation No prints & diapositives No manual terrain modeling Mapping via PurVIEW Orthophoto in Image Server

geo-referenced in-camera only image files RADAR or LiDAR showers geodatabase-direct on-the-fly

Workflow Next Method

IMU-Digital LiDAR / RADAR Geo-referenced DEM Imaging PurVIEW operation

Orthophoto processing

Other applications

State of the Art…and Technology in Forest Inventory Mapping

Inventory Mapping

… to 1991

1992 – 1999

1999 – 2004

2005 – now

Analogue

CAD

DiAP-Viewer

PurVIEW

Reconnaissance

Air/Ground Calls

GPS-assisted

Photo Interpretation

Stereoscope

Stereoscope

Polygon Delineation

Contact Print Ink

Contact Print Ink

GPS-direct

GPS-direct

DiAP-Viewer CAD-direct

PurVIEW geodatabasedirect

GPS-guided

Tree Height Measurement

Parallax Bar

Parallax Bar

Polygon transfer to maps

Kail Plotter, etc…

Map post-digitizing

IGDS

Mono-restitution CAD-direct

Field verification

Air/ground Plots

GPS-assisted

GPS-guided

Slope/Elevation/Aspect

Estimation

TIN-derivation

TIN-derivation

Growth/Yield

Speculation

Speculation

Speculation

Other analysis

Speculation

Speculation

Measurable

ArcGIS

Old Mapping Method…

x

Stereoscopic studies of aerial photos Inking polygons/features onto contact print Approximate object height measurements Approximate polygon transfers onto base maps 2D digitizing of map manuscript

Geo-processing the 2D CAD files

x

Old Field Method… Air/ground calls/plots by “dead reckoning”

New Method: Training/Test Sets by GPS

British Columbia Ministry of Forests - Forest Cover [2D] FC-1 Digitized Maps

3D geodatabase-direct

Other issues also resolved: Projection: - ArcGIS converts NAD-27 into NAD-83, Albers… - PurVIEW dynamically projects model control coordinates into mapping coordinates 2D v. 3D: Virtual-Z dynamically converts 2D mapping into 3D Field use: Hardcopy in anaglyph stereo

Forest Cover Mapping – BC MoFR

How does it work?

Software & Hardware

…or Anaglyph Viewing

x

Supported imagery any

frame-by-frame or line-by-line digital/digitized imagery with Interior/Exterior Orientation parameters in various file formats or RPC

Scanned film imagery

RC, RMK, LMK…

Digital Frame Cameras

UCD, UCXP; DMC; RMKD

Digital Aerial Scanners

ADS 40/50/80…

Space-borne imagery

Ikonos, Cartosat, GeoEye…

Supported DEM: LiDAR, RADAR, Photogrammetric LiDAR

10m Photogrammetric

RADAR

Bare-earth view – USA

Virtual raised relief map or imagery

Source Data Direct Read

• • • • • • • • • • • • • • • • • • • • • • • • • • •

begin model 1924 left_photo: 1924 right_photo:1925 atmospheric_flag: off earth_curve_flag: off left_lens_flag: on right_lens_flag: on RO_parametersL: 0 0 302.922 0 0 0 RO_parametersR: 87.21076105757685 -2.940220899132825 302.4904826401843 -0.6699756189427558 0.6436907917340337 0.1415827980869817 RO_num_iters: 3 RO_num_DOF: 12 RO_sum_red: 12.00000066089669 RO_apost_std_dev: 4.742505457690576 RO_obs: 19192449 1 0 -9.216800693402989e-005 -0.002734271138771133 8.551566415345879e-005 0.002738851744873322 -0.9749844831867812 0.9749844831867813 0.9749844831867811 0.9749844831867812 5.476006353762177 0.3483692236982312 RO_obs: 19192428 1 0 0.0002328277081160169 0.007098046778593414 -0.0002014343900262903 -0.007113466448173839 2.430296506541687 2.430296506541687 -2.430296506541687 -2.430296506541687 14.21814656572591 0.3885515790451946 RO_obs: 19192418 1 0 1.526978272194305e-005 0.0004708773369041355 -1.279666230225846e-005 -0.000471878137023175 0.1586137835047162 0.1586137835047162 -0.1586137835047163 -0.1586137835047163 0.9431731595821653 0.3942913542599571 RO_obs: 18182468 1 0 -0.0001278557566773672 -0.004002488104144476 0.0001025353575472848 0.004011595491733687 -1.583340632770566 1.583340632770566 1.583340632770566 1.583340632770566 8.017394585975994 0.2814665688993043 RO_obs: 18182488 1 0 3.621915965691522e-005 0.001124260080160922 -2.978500497034786e-005 -0.001126718539415711 0.3912660151180373 0.3912660151180372 -0.3912660151180372 -0.3912660151180372 2.251946112929718 0.370116273140884 RO_obs: 19192549 1 0 -7.417047265638079e-005 -0.002205626436423284 6.819548481762894e-005 0.002202307449033387 -0.7848074916366772 0.784807491636677 0.7848074916366771 0.7848074916366771 4.410232329980433 0.3481735119741868 RO_obs: 19192528 1 0 2.318306448730062e-006 7.041224682025476e-005 -2.018723176533091e-006 -7.030655590539735e-005 0.02432269248579993 0.02432269248579992 -0.02432269248579993 -0.02432269248579993 0.140785621661132 0.3718737492347906 RO_obs: 19192518 1 0 0.0001441297830182669 0.004468916590124374 -0.0001184916148850902 -0.004463047898119873 1.609075668395108 1.609075668395108 -1.609075668395108 -1.609075668395109 8.935824506887602 0.3469080003654929 RO_obs: 18182568 1 0 -3.865958942755112e-005 -0.001210894256457925 3.085146708600071e-005 0.001209731224089844 -0.498020155814113 0.4980201558141131 0.498020155814113 0.498020155814113 2.421623320017948 0.2612633349476267 RO_obs: 18182588 1 0 -9.299892924718622e-005 -0.002861291820779107 7.823516087257402e-005 0.002859779070693429 -0.9274633070482584 0.9274633070482585 0.9274633070482585 0.9274633070482586 5.723632872474744 0.4200850171890429 RO_obs: 20202418 1 0 0.0001002102831521049 0.00284826593292838 -0.0001025394345719465 -0.002854702639955032 1.18394128580688 1.18394128580688 -1.18394128580688 -1.18394128580688 5.706571474303379 0.2617731727522797 RO_obs: 19192468 1 0 -0.0001182674082637609 -0.003405971557833327 0.0001175743411503378 0.003411873342722822 -1.158263440837804 1.158263440837804 1.158263440837804 1.158263440837803 6.821922780184937 0.3827278586812221 RO_obs: 19192488 1 0 -2.913310644684703e-005 -0.0008326614879674102 2.944278982253082e-005 0.0008340579248123766 -0.2893054143417714 0.2893054143417714 0.2893054143417714 0.2893054143417714 1.667748403255347 0.3691405513991309 RO_obs: 19192568 1 0 7.038386289217967e-005 0.002032762568693572 -6.930041020500175e-005 -0.002029570345026974 0.6994051380068653 0.6994051380068653 -0.6994051380068654 -0.6994051380068654 4.064733742577483 0.3769388515383017

“Frame Camera”

Z(I DMC

Vexcel UCD

Leica ADS-40/50/80 (AS)

[Ir, B, G, R, P] Backward [Ir, B, G, R, P1, P2] Nadir

[P] Forward

Leica ADS-40/50/80 (AS)

Leica ADS-40(52)

Space-borne Imagery Rational Polynomial Coefficient (RPC)

IKONOS

AND, finally… coordinate transformation on-the-fly ●



Source Data Shopping

Available meta-data Quality Geo-referencing

X0, Y0, Z0 κ, φ, ω

kGPS or IMU ~15cm

1~1.5 GSD, if @ 10cm

via IMU ± ½ arc-min.

1 part in 10,800 of 90°

via AT DEM

RADAR

±1m

LiDAR

±15cm

Photogrammetric

± 1% “grad” from 10,000m from 1,000m

1 part in 10,000 of 90° 1 part per 10,000 1 part per 6,600

1st-Order

1 per 6,000

2nd-Order

1 per 4,800

Heterogeneous Integration by default (Geo-referencing AT metadata) ESRI Business Partner products: BAE SOCET SET, Inpho Match-AT (also resold by DAT/EM) PCI; Non- ESRI–compatible photogrammetric workstations: § KLT-Atlas, § Boeing/Autometric SoftPlotter. Leica/ERDAS/Intergraph: § LPS-Orima: outputs proprietary binary files, also SOCET SET files § Intergraph ImageStation (ISAT)…now a Leica sister company.

Typical Frame Camera stereo-model meta-data file • • • • • • • • • • • • • • • • • • • • • • • • • • •

begin model 1924 left_photo: 1924 right_photo: 1925 atmospheric_flag: off earth_curve_flag: off left_lens_flag: on right_lens_flag: on RO_parametersL: 0 0 302.922 0 0 0 RO_parametersR: 87.21076105757685 -2.940220899132825 302.4904826401843 -0.6699756189427558 0.6436907917340337 0.1415827980869817 RO_num_iters: 3 RO_num_DOF: 12 RO_sum_red: 12.00000066089669 RO_apost_std_dev: 4.742505457690576 RO_obs: 19192449 1 0 -9.216800693402989e-005 -0.002734271138771133 8.551566415345879e-005 0.002738851744873322 -0.9749844831867812 0.9749844831867813 0.9749844831867811 0.9749844831867812 5.476006353762177 0.3483692236982312 RO_obs: 19192428 1 0 0.0002328277081160169 0.007098046778593414 -0.0002014343900262903 -0.007113466448173839 2.430296506541687 2.430296506541687 -2.430296506541687 -2.430296506541687 14.21814656572591 0.3885515790451946 RO_obs: 19192418 1 0 1.526978272194305e-005 0.0004708773369041355 -1.279666230225846e-005 -0.000471878137023175 0.1586137835047162 0.1586137835047162 -0.1586137835047163 -0.1586137835047163 0.9431731595821653 0.3942913542599571 RO_obs: 18182468 1 0 -0.0001278557566773672 -0.004002488104144476 0.0001025353575472848 0.004011595491733687 -1.583340632770566 1.583340632770566 1.583340632770566 1.583340632770566 8.017394585975994 0.2814665688993043 RO_obs: 18182488 1 0 3.621915965691522e-005 0.001124260080160922 -2.978500497034786e-005 -0.001126718539415711 0.3912660151180373 0.3912660151180372 -0.3912660151180372 -0.3912660151180372 2.251946112929718 0.370116273140884 RO_obs: 19192549 1 0 -7.417047265638079e-005 -0.002205626436423284 6.819548481762894e-005 0.002202307449033387 -0.7848074916366772 0.784807491636677 0.7848074916366771 0.7848074916366771 4.410232329980433 0.3481735119741868 RO_obs: 19192528 1 0 2.318306448730062e-006 7.041224682025476e-005 -2.018723176533091e-006 -7.030655590539735e-005 0.02432269248579993 0.02432269248579992 -0.02432269248579993 -0.02432269248579993 0.140785621661132 0.3718737492347906 RO_obs: 19192518 1 0 0.0001441297830182669 0.004468916590124374 -0.0001184916148850902 -0.004463047898119873 1.609075668395108 1.609075668395108 -1.609075668395108 -1.609075668395109 8.935824506887602 0.3469080003654929 RO_obs: 18182568 1 0 -3.865958942755112e-005 -0.001210894256457925 3.085146708600071e-005 0.001209731224089844 -0.498020155814113 0.4980201558141131 0.498020155814113 0.498020155814113 2.421623320017948 0.2612633349476267 RO_obs: 18182588 1 0 -9.299892924718622e-005 -0.002861291820779107 7.823516087257402e-005 0.002859779070693429 -0.9274633070482584 0.9274633070482585 0.9274633070482585 0.9274633070482586 5.723632872474744 0.4200850171890429 RO_obs: 20202418 1 0 0.0001002102831521049 0.00284826593292838 -0.0001025394345719465 -0.002854702639955032 1.18394128580688 1.18394128580688 -1.18394128580688 -1.18394128580688 5.706571474303379 0.2617731727522797 RO_obs: 19192468 1 0 -0.0001182674082637609 -0.003405971557833327 0.0001175743411503378 0.003411873342722822 -1.158263440837804 1.158263440837804 1.158263440837804 1.158263440837803 6.821922780184937 0.3827278586812221 RO_obs: 19192488 1 0 -2.913310644684703e-005 -0.0008326614879674102 2.944278982253082e-005 0.0008340579248123766 -0.2893054143417714 0.2893054143417714 0.2893054143417714 0.2893054143417714 1.667748403255347 0.3691405513991309 RO_obs: 19192568 1 0 7.038386289217967e-005 0.002032762568693572 -6.930041020500175e-005 -0.002029570345026974 0.6994051380068653 0.6994051380068653 -0.6994051380068654 -0.6994051380068654 4.064733742577483 0.3769388515383017

“RPC” • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •

LINE_OFF: +005000.00 pixels SAMP_OFF: +005000.00 pixels LAT_OFF: +24.61560000 degrees LONG_OFF: -101.43730000 degrees HEIGHT_OFF: +2395.000 meters LINE_SCALE: +005001.00 pixels SAMP_SCALE: +005001.00 pixels LAT_SCALE: +00.04600000 degrees LONG_SCALE: +000.05030000 degrees HEIGHT_SCALE: +0747.000 meters LINE_NUM_COEFF_1: +1.030324040486937E-03 LINE_NUM_COEFF_2: +1.806315262669138E-02 LINE_NUM_COEFF_3: -1.019060432009551E+00 LINE_NUM_COEFF_4: +6.648449785992906E-02 LINE_NUM_COEFF_5: -2.331100461592361E-03 LINE_NUM_COEFF_6: +8.769596902043321E-05 LINE_NUM_COEFF_7: +1.375570693342427E-03 LINE_NUM_COEFF_8: -1.468399048346219E-04 LINE_NUM_COEFF_9: +5.703399246782981E-03 LINE_NUM_COEFF_10: -1.226613143284226E-04 LINE_NUM_COEFF_11: +1.577423543808047E-06 LINE_NUM_COEFF_12: -2.490411434190130E-07 LINE_NUM_COEFF_13: -7.062981729517195E-06 LINE_NUM_COEFF_14: -3.135787647537088E-08 LINE_NUM_COEFF_15: -7.790425173363112E-06 LINE_NUM_COEFF_16: +6.380555501522290E-05 LINE_NUM_COEFF_17: -9.836708602583833E-07 LINE_NUM_COEFF_18: +5.021992515463427E-06 LINE_NUM_COEFF_19: -8.448845700616180E-06 LINE_NUM_COEFF_20: +1.015174042812033E-07 LINE_DEN_COEFF_1: +1.000000000000000E+00 LINE_DEN_COEFF_2: +2.212832526975384E-03 LINE_DEN_COEFF_3: -5.599305983296421E-03 LINE_DEN_COEFF_4: -4.312298442342292E-03 LINE_DEN_COEFF_5: +5.655276824407152E-06 LINE_DEN_COEFF_6: -7.782144773107029E-06 LINE_DEN_COEFF_7: +1.330672367505108E-05

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •

LINE_OFF: +005000.00 pixels SAMP_OFF: +005000.00 pixels LAT_OFF: +24.61560000 degrees LONG_OFF: -101.43730000 degrees HEIGHT_OFF: +2395.000 meters LINE_SCALE: +005001.00 pixels SAMP_SCALE: +005001.00 pixels LAT_SCALE: +00.04600000 degrees LONG_SCALE: +000.05030000 degrees HEIGHT_SCALE: +0747.000 meters LINE_NUM_COEFF_1: +9.693771848586271E-04 LINE_NUM_COEFF_2: +1.806486366746527E-02 LINE_NUM_COEFF_3: -1.019049471259863E+00 LINE_NUM_COEFF_4: -2.895807427845248E-02 LINE_NUM_COEFF_5: -4.040764489077493E-03 LINE_NUM_COEFF_6: -1.396053711395637E-04 LINE_NUM_COEFF_7: +1.944843057440099E-03 LINE_NUM_COEFF_8: -1.130125598918517E-04 LINE_NUM_COEFF_9: -5.546782426457077E-03 LINE_NUM_COEFF_10: +6.358293825145087E-05 LINE_NUM_COEFF_11: -1.507533375375395E-07 LINE_NUM_COEFF_12: -7.530457301559698E-07 LINE_NUM_COEFF_13: -4.480681607870567E-05 LINE_NUM_COEFF_14: +2.561572674602523E-07 LINE_NUM_COEFF_15: -4.408171438680323E-07 LINE_NUM_COEFF_16: +1.650436086860782E-05 LINE_NUM_COEFF_17: -1.230472720972256E-06 LINE_NUM_COEFF_18: +4.913216033668152E-06 LINE_NUM_COEFF_19: +1.915693289437321E-06 LINE_NUM_COEFF_20: -4.247006484070904E-08 LINE_DEN_COEFF_1: +1.000000000000000E+00 LINE_DEN_COEFF_2: +4.086220749098909E-03 LINE_DEN_COEFF_3: +5.440554179367067E-03 LINE_DEN_COEFF_4: -4.785200534247517E-03 LINE_DEN_COEFF_5: +4.378224454068469E-05 LINE_DEN_COEFF_6: -8.018136936822684E-06 LINE_DEN_COEFF_7: -1.249423873247631E-05

Source Data quality & Mapping Specifications or How good is good enough?

Old specifications summarized… Horizontal accuracy – within ½ mm at plotting scale… Vertical accuracy – within ½ contour interval… Plotting scale 1:

Contour Interval

500

0.5 m

1: 1,000

1.0 m

1: 2,000

2.0 m

1: 5,000

5.0 m

1:10,000

10.0 m

1:20,000

20.0 m

1:50,000

50.0 m

…specifications modernized Map scale

X/Y/Z

1: 500 1: 1,000 1: 2,000 1: 5,000 1: 10,000 1: 20,000 1: 50,000

± 0.25 m ± 0.50 m ± 1.00 m ± 2.50 m ± 5.00 m ± 10.0 m ± 25.0 m

Specifications modernized… but @ what imagery GSD? Map scale

X/Y/Z

GSD

1:

500

± 0.25 m

5 cm

1: 1,000

± 0.5 m

10 cm

1: 2,000

± 1.0 m

20 cm

1: 5,000

± 2.5 m

50 cm

1: 10,000

±5m

1m

1: 20,000

± 10 m

2m

1: 50,000

± 25 m

5m

Specifications distilled… Map scale

X/Y/Z

GSD

DEM

1:

500

± 0.25 m

0.05 m

0.25 m

1: 1,000

± 0.5 m

0.1 m

0.5 m

1: 2,000

± 1.0 m

0.2 m

1m

1: 5,000

± 2.5 m

0.5 m

2.5 m

1: 10,000

±5m

1m

5m

1: 20,000

± 10 m

2m

10 m

1: 50,000

± 25 m

5m

25 m

x f/b =

…and where does inventory mapping fit? Map scale 1: 500 1: 1,000 1: 2,000 1: 5,000 1: 10,000 1: 20,000 1: 50,000

X/Y/Z ± 0.25 m ± 0.50 m ± 1.00 m ± 2.50 m ± 5.00 m ± 10.0 m ± 25.0 m

Forest Inventory Mapping

Map scale 1: 20,000

X/Y/Z ± 20.0 m

What size GSD?

Map Scale

Contour Interval

Positional Accuracy X

Y

Z

Image Tree Height GSD Accuracy

1:500

0.5m

0.25m

0.25m

0.25m

5cm 25cm

1:1000

1.0m

0.50m

0.50m

0.50m

10cm 50cm

1:2000

2.0m

1.0m

1.0m

1.0m

1:5000

5.0m

2.5m

2.5m

2.5m

1:10000

10.0m

5m

5m

5m

1:20000

20.0m

10m

10m

10m

2m 10m

1:50000

50.0m

25m

25m

25m

5m 25m

20cm 1m 0.5m 2.5m 1m 5m

What else?

Synthetic Stereo Image Model from RADAR or LiDAR Data…

or ortho-mosaics

dSIM view of a 25 photo prthophoto mosaic… tone, color balanced…

dynamic Synthetic Image Model (dSIM)

Multiple Dataset Attachment and dSIM Configuration

Multiple Datasets

dSIM on-the-fly - Exaggeration Factor manually applied for orthophoto/DEM without ‘Model Source’ metadata.

toggles between Primary/Secondary datasets

PurVIEW-Standard: Mouse-digitizes to nearest monitor pixel

Upgrades…

PurVIEW–X, or MX : Dynamic panning [fixed cursor, moving image], digitizes in user-selectable terrain coordinate units

beyond next… Last inventory polygons stereo-superimposed on new imagery is “Training Set”

Next inventory needs only:

Update harvested areas… Update hydrography and access; Adjust polygon/stand boundaries; Re-estimate stand mixture; Re-measure tree height-class; Re-measure tree crown closure; Auto-calculate tree age-class; S/E/A might not have changed…

and beyond beyond next… image models

viewable on-demand

D.E.M.

coverage everywhere

professional purview

review legacy data models QA new mapping delivery update, upgrade, retrofit …geodatabase-direct ortho-on-the-fly

…no excuses.

shaky grounds… Mapping : Hardcopy to softcopy Surveying : Optical to electronic Photogrammetry : Cast iron to silicon chip Imaging 4 Film to digital Choices: retrain…re-qualify; …or redundancy or retirement

Arc/PurVIEW a new era of Data Model self-updating, -upgrading or -retrofitting …geodatabase direct

[email protected]