Tropical tree species identification is critical for studies of forest habitat, composition, biomass, and determining the role of forests in climate variability through carbon uptake. The aim of the research was to derive an accurate classification of a tropical forest study site in Costa Rica using high-resolution imagery. A series of corrections for look and view angle, and the utilization of the DigitalGlobe atmospheric compensation procedure (AComp) provided the study with an accurate surface reflectivity dataset from WorldView-3 imagery. A rule-set object-oriented classification schema defined trees in the study area using ENVI-defined tree canopies through a segmentation of the multispectral image. The results show that select WorldView-3 bands, and WorldView-3-specific vegetation indices, can produce an accurate species-level tree classification in a complex tropical forest.

1. TROPICAL TREE SPECIES DELINEATION UTILIZING
HIGH-RESOLUTION SATELLITE IMAGERY FOR
IMPROVED ABOVE-GROUND BIOMASS ESTIMATES
Matthew D. Cross
University of Colorado Denver

2. Introduction
• Carbon concentrations have changed
significantly
• Vegetation - a control for carbon
–Tropical forests - deforestation
• Uncertainties exist in current biomass
estimates
• An improved process for a above-ground
measure of biomass is needed
–Accurately assess the role of tropical forest
on the global climate

3. La Selva Biological Station, Costa Rica

4. • Premier site for
lowland rainforest
research
• Managed by
Organization for
Tropical Studies
• NE Portion of Braulio
Carrillo National Park
La Selva Biological Station, Costa Rica
• 5,000 species of vascular
plants
• 700 species of trees

5. La Selva
Biological
Station

6. Verification

7. Data Sources
• Analytical Spectral Devices (ASD) FieldSpec Pro
Spectroradiometer (300 – 2500 nm)
• Sampling interval from 1.4 nm (350 – 1000 nm) to 2 nm (1000
– 2500nm)
• Output -- digital number or percent reflectance

8. Data Sources
• WorldView-3 Image
• November 11, 2014
– off-nadir data collection -- 26.2°
– azimuth view angle -- 108.8°
• Cloud cover = 0.5%
• Spatial Resolution
– 1.24 m multispectral
– 0.31 cm panchromatic
• Radiometric Resolution
– 11 bits/pixel
• Spectral Resolution
– 8 bands (multispectral)
– 1 panchromatic band
Bands Spectral Range (nm)
Panchromatic 450 - 800
Costal 400 – 450
Blue 450 – 510
Green 510 – 580
Yellow 585 – 625
Red 630 – 690
Red Edge 705 – 745
Near-IR1 770 – 895
Near-IR2 860 – 1040

11. Towers 1 and 2

15. Tower Locations

22. ASD Data
– Processed in MATLAB to WV-3 surface reflectance
– Used Radiance Response Curves for each WV-3 band
– Calculated for each tree collected

24. Original

25. AComp

28. C. Elastica
(df=3)
I. marginata
(df=14)
L. Procera
(df=2)
O. floribunda
(df=7)
P. macroloba
(df=12)
WV-3
Bands
t Sig. t Sig. t Sig. t Sig. t Sig.
Coastal 5.773 0.010 18.610 0.000 6.980 0.020 7.656 0.000 13.109 0.000
Blue 0.056 0.959 6.369 0.000 1.555 0.260 2.028 0.082 5.333 0.000
Green 1.167 0.328 2.681 0.018 1.543 0.263 -0.176 0.866 0.176 0.863
Yellow -2.876 0.064 2.228 0.043 -0.241 0.832 -2.384 0.049 -3.229 0.007
Red -4.282 0.023 4.256 0.001 -5.353 0.033 -2.045 0.080 -4.527 0.001
Red Edge -1.889 0.155 1.281 0.221 2.222 0.156 0.867 0.414 0.015 0.988
Near IR1 0.219 0.841 -0.267 0.794 -0.508 0.662 -0.165 0.874 0.562 0.584
Near IR2 0.020 0.985 0.070 0.945 0.776 0.519 0.308 0.767 -0.524 0.610

29. R. kunthiana
(df=4)
S. microstachyum
(df=9)
S. Mombin
(df=6)
Z. longifolia
(df=17)
WV-3
Bands
t Sig t Sig t Sig t Sig
Coastal 2.231 0.089 -4.190 0.002 0.058 0.956 16.439 0.000
Blue -4.899 0.008 -26.598 0.000 -9.580 0.000 12.637 0.000
Green -2.641 0.058 -31.894 0.000 -9.445 0.000 -0.069 0.946
Yellow -7.194 0.002 -31.851 0.000 -17.995 0.000 -0.391 0.701
Red -12.525 0.000 -23.180 0.000 -16.470 0.000 2.288 0.035
Red Edge -0.759 0.490 -2.641 0.027 -3.136 0.020 -0.837 0.414
Near IR1 0.335 0.754 -0.045 0.965 0.406 0.699 1.140 0.270
Near IR2 0.164 0.878 0.193 0.852 -0.553 0.600 0.613 0.548

30. Classification

37. Tree Species Family
Approximate
Location
Canopy Total Total pixels
Collection Size
(m2)
Castilla elastica Moraceae
Lab area and west
La Selva
3 81 100.44
Cedrela odorata Meliaceae
Lab area and east
La Selva
2 81 100.44
Cordia alliodora Boraginaceae
Arboretum trail
from lab
2 39 48.36
Pentaclethra
macroloba
Fabaceae
Station entrance
and west
La Selva
9 217 269.08
Pterocarpus sp. A Fabaceae
Lab area and
east La Selva
2 128 158.72
Stryphnodendron
microstachyum
Fabaceae
Station entrance
and lab area
3 87 107.88

39. Spectral Vegetation Indices
• Used for assessing plant health, vegetation extent,
biomass
• Two newly developed SVIs for La Selva
– WV-ACRI (WorldView Average Canopy Reference Index)
𝑊𝑉𝐴𝐶𝑅𝐼 =
𝑁𝐼𝑅1 − ACnir1 + 𝑁𝐼𝑅2 − 𝐴𝐶𝑛𝑖𝑟2
2
+
𝐺𝑟𝑒𝑒𝑛 − 𝐴𝐶𝑔𝑟𝑛 + 𝑌𝑒𝑙𝑙𝑜𝑤 − 𝐴𝐶𝑦𝑒𝑙 + (𝑅𝑒𝑑𝐸𝑑𝑔𝑒 − 𝐴𝐶𝑟𝑒)
– WV-RESWI (WorldView Red Edge Slope Weighted Index)
𝑊𝑉𝑅𝐸𝑆𝑊𝐼 =
𝑁𝐼𝑅1 − 𝑅𝑒𝑑
0.173
∗ 𝑅𝑒𝑑𝐸𝑑𝑔𝑒

41. Band Locations Wilks’ Lambda F-test
Costal 0.862 20.090
Blue 0.662 64.082
Green 0.717 49.514
Yellow 0.710 51.138
Red 0.626 74.983
Red Edge 0.560 98.605
Near-IR1 0.500 125.583
Near-IR2 0.529 111.681
WV-ACRI 0.529 111.568
WV-RESWI 0.485 133.042

45. C. elastica – green
C. odorata – blue
C. alliodora – red
P. macroloba – yellow
P. sp. A – teal
S. microstachyum –
magenta

46. Bands/Index Used: Dependent on Rule-set for each Species
Overall Accuracy = 85.37%, Kappa = 0.808
Field Reference
Classification
C.
elastica
C.
odorata
C.
alliodora
P.
macroloba
P.
sp. A
S.
micro.
Total Users Acc.
C. elastica 2 2 100%
C. odorata 3 1 4 75.00%
C. alliodora 1 11 12 91.67%
P. macroloba 13 13 100%
P. sp. A 1 5 6 83.33%
S. micro. 1 1 100%
Unknown 1 1 1 3
Total 3 3 12 15 7 1 41
Prod. Acc. 66.67% 100% 91.67% 86.67% 71.43% 100% 85.37%

47. Future Research
• Biomass calculations
• Longitudinal studies (before/after)
• Forest inventory
• Forest diversity (clear cut)
• Forest Health (pine beetle pic)
• Archaeological findings/infrastructure (china)
• Bi-directional reflectance improvements

48. Thank You