Integrating LiDAR, Multispectral and SAR Data to Estimate and Map Canopy Height in Tropical Forests

编号 030022303

推送时间 20200127

研究领域 森林经理 

年份 2020 

类型 期刊 

语种 英语

标题 Integrating LiDAR, Multispectral and SAR Data to Estimate and Map Canopy Height in Tropical Forests

来源期刊 REMOTE SENSING

期 第223期

发表时间 20191118

关键词 ALOS-PALSAR (Phased Array type L-band Synthetic Aperture Radar);  dry tropical forest;  Landsat-8;  learning algorithms;  moist tropical forest;  Sentinel-1;  spatial modelling; 

摘要 Developing accurate methods to map vegetation structure in tropical forests is essential to protect their biodiversity and improve their carbon stock estimation. We integrated LIDAR (Light Detection and Ranging), multispectral and SAR (Synthetic Aperture Radar) data to improve the prediction and mapping of canopy height (CH) at high spatial resolution (30 m) in tropical forests in South America. We modeled and mapped CH estimated from aircraft LiDAR surveys as a ground reference, using annual metrics derived from multispectral and SAR satellite imagery in a dry?forest, a moist?forest, and a rainforest of tropical South America. We examined the effect of the three?forest?types, five regression algorithms, and three predictor groups on the modelling and mapping of CH. Our CH models reached errors ranging from 1.2-3.4 m in the dry?forest?and 5.1-7.4 m in the rainforest and explained variances from 94-60% in the dry?forest?and 58-12% in the rainforest. Our best models show higher accuracies than previous works in tropical forests. The average accuracy of the five regression algorithms decreased from dry forests (2.6 m +/- 0.7) to moist (5.7 m +/- 0.4) and rainforests (6.6 m +/- 0.7). Random?Forest?regressions produced the most accurate models in the three?forest?types (1.2 m +/- 0.05 in the dry, 4.9 m +/- 0.14 in the moist, and 5.5 m +/- 0.3 the rainforest).?Model?performance varied considerably across the three predictor groups. Our results are useful for CH spatial prediction when GEDI (Global Ecosystem Dynamics Investigation lidar) data become available.

服务人员 付贺龙

PDF文件 浏览全文