A SPACE-TIME DATA CUBE: MULTI-TEMPORAL FOREST STRUCTURE MAPS FROM LANDSAT AND LIDAR

被引：0

作者：

Matasci, Giona ^{[1
]}

Hermosilla, Txomin ^{[1
]}

Wulder, Michael A. ^{[2
]}

White, Joanne C. ^{[2
]}

Hobart, Geordie W. ^{[2
]}

Zald, Harold S. J. ^{[3
]}

Coops, Nicholas C. ^{[1
]}

机构：

[1] Univ British Columbia, Dept Forest Resources Management, Integrated Remote Sensing Studio, Vancouver, BC, Canada

[2] Nat Resources Canada, Canadian Forest Serv, Pacific Forestry Ctr, Victoria, BC, Canada

[3] Humboldt State Univ, Dept Forestry & Wildland Resources, Arcata, CA 95521 USA

来源：

2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2017年

关键词：

LiDAR plots; Landsat pixel composites; time-series; forest mapping; imputation; Random Forest; INTEGRATION; INVENTORY; SERIES; PLOTS;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

In this study, we prototype the combination of samples of airborne LiDAR (LiDAR plots) and Landsat data to characterize the development of forest structure attributes through time. A nearest neighbor imputation model was developed using predictors generated from wall-to-wall Landsat best available pixel (BAP) composites and reference measurements of forest structure derived from LiDAR plots. The imputation model was then applied through time on a study area in Canada's boreal forest, resulting in forest structure maps with a 30 m resolution for the period 1984-2012. We characterize post-disturbance trends in these forest structural metrics following wildfire and harvest and offer insights on the large-area, temporally dense mapping opportunities offered by the synergistic use of samples of airborne LiDAR and Landsat BAP composites.

引用

页码：2581 / 2584

页数：4

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