共 28 条
Mitigation of Spatial Effects on an Area-Based Lidar Forest Inventory (2024)
被引:0
|作者:
Strunk, Jacob L.
[1
]
Cosenza, Diogo N.
[2
]
Mauro, Francisco
[3
]
Andersen, Hans-Erik
[4
]
de Bruin, Sytze
[5
]
Bryant, Timothy
[6
]
Packalen, Petteri
[7
]
机构:
[1] USDA Forest Serv Pacific Northwest Res Stn, Olympia, WA 98512 USA
[2] Univ Fed Vicosa, Dept Forest Engn, BR-36570900 Vicosa, Brazil
[3] Univ Valladolid, iuFOR, EiFAB, Campus Soria, Soria 42004, Spain
[4] Univ Washington, USDA Forest Serv Pacific Northwest Res Stn, Seattle, WA 98195 USA
[5] Wageningen Univ, Lab GeoInformat Sci & Remote Sensing, NL-6708PB Wageningen, Netherlands
[6] USDA Forest Serv Pacific Northwest Reg, Portland, OR 97204 USA
[7] Nat Resources Inst Finland Luke, Bioecon & Environm Unit, FI-00790 Helsinki, Finland
关键词:
Forestry;
Laser radar;
Shape;
Size measurement;
Measurement;
Shape measurement;
Vegetation;
Remote sensing;
Estimation;
Predictive models;
Airborne laser scanning (ALS);
area-based approach (ABA);
change of spatial support problem (COSP);
estimation;
lidar forest inventory;
model-assisted;
modifiable areal unit problem (MAUP);
INDIVIDUAL TREE DETECTION;
UNIT PROBLEM;
UNCERTAINTY;
D O I:
10.1109/JSTARS.2025.3528834
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
Different sizes and shapes of field plots relative to raster grid cells were found to negatively affect lidar augmented forest inventory. This issue is called the "change of spatial support problem (COSP)" and caused biases and reduction in estimation efficiency (precision per number of plots). For a similar to 14 000 km(2) study area in Oregon State, USA, we examined three different plot shapes, both fixed-radius and cluster plots, alongside grid cell sizes ranging from 5 to 70 m. Effect size varied with the magnitude of spatial mismatch between plots and raster grid cells. There was up to 15% bias and a 98% reduction in estimation efficiency. Fortunately, no negative effects were observed for circle (plots) versus square (grid cell) shaped regions with the same areas (m(2)). This study contributes to the sparse body of literature around change of spatial support in the area-based approach to lidar forest inventory and provides methods to easily avoid and mitigate negative effects. The simplest approach to avoid bias, although not always practical or feasible, is to exactly match the area (m(2)) of circular field plots and raster grid cells. Use of metrics robust to spatial effects, such as median height and height ratios, can also reduce change of spatial support effects. Finally, we demonstrate that attribution of plots directly from raster grid cells (the "raster-intersect" approach) is robust to change of spatial support and flexible in application, but sacrifices a small amount of predictive power (a glossary of technical terminology is also provided in the appendix).
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页码:5287 / 5302
页数:16
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