Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data

被引:16
|
作者
Jonikavicius, Donatas [1 ]
Mozgeris, Gintautas [2 ]
机构
[1] Aleksandras Stulginskis Univ, Inst Land Management & Geomat, Lab Geomat, LT-53361 Akademija, Kaunas Distr, Lithuania
[2] Aleksandras Stulginskis Univ, Inst Forest Management & Wood Sci, LT-53361 Akademija, Kaunas Distr, Lithuania
关键词
Forest Damage; Satellite Images; Change Detection; k-Nearest Neighbour; SIMILAR NEIGHBOR; AIRBORNE; VOLUME; INFERENCE; DENSITY; HEIGHT;
D O I
10.3832/ifor0715-006
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
This paper introduces a method for rapid forest damage assessment using satellite images and stand-wise forest inventory data. Two Landsat 5 Thematic Mapper (TM) images from June and September 2010 and data from a forest stand register developed within the frameworks of conventional stand-wise forest inventories in Lithuania were used to assess the forest damage caused by wind storms that occurred on August 8, 2010. Satellite images were geometrically and radiometrically corrected. The percentage of damage in terms of wind-fallen or broken tree volume was then predicted for each forest compartment within the zone potentially affected by the wind storm, using the non-parametric k-nearest neighbor technique. Satellite imagery-based difference images and general forest stand characteristics from the stand register were used as the auxiliary data sets for prediction. All auxiliary data were available from existing databases, and therefore did not involve any added data acquisition costs. Simultaneously, aerial photography of the area damaged by the wind storm was carried-out and color infrared (CIR) orthophotos with a resolution of 0.5 x 0.5 m were produced. A precise manual interpretation of the effects of the wind storm was used to validate satellite image-based estimates. The total wind damaged volume in pine dominating forest (similar to 1.180.000 m(3)) was underestimated by 2.2%, in predominantly spruce stands (similar to 233.000 m(3)) by 2.6% and in predominantly deciduous stands (similar to 195.000 m(3)) by 4.2%, compared to validation data. The overall accuracy of identification of wind-damaged areas was around 95-98%, based solely on difference data from satellite images gathered on two dates.
引用
收藏
页码:150 / 155
页数:6
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