Airborne lidar intensity calibration and application for land use classification

Dong Li; Cheng Wang; She-Zhou Luo; Zheng-Li Zuo

doi:10.1117/12.2069014

17 November 2014 Airborne lidar intensity calibration and application for land use classification

Dong Li, Cheng Wang, She-Zhou Luo, Zheng-Li Zuo

Proceedings Volume 9262, Lidar Remote Sensing for Environmental Monitoring XIV; 926212 (2014) https://doi.org/10.1117/12.2069014
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China

Abstract

Airborne Light Detection and Ranging (LiDAR) is an active remote sensing technology which can acquire the topographic information efficiently. It can record the accurate 3D coordinates of the targets and also the signal intensity (the amplitude of backscattered echoes) which represents reflectance characteristics of targets. The intensity data has been used in land use classification, vegetation fractional cover and leaf area index (LAI) estimation. Apart from the reflectance characteristics of the targets, the intensity data can also be influenced by many other factors, such as flying height, incident angle, atmospheric attenuation, laser pulse power and laser beam width. It is therefore necessary to calibrate intensity values before further applications. In this study, we analyze the factors affecting LiDAR intensity based on radar range equation firstly, and then applying the intensity calibration method, which includes the sensor-to-target distance and incident angle, to the laser intensity data over the study area. Finally the raw LiDAR intensity and normalized intensity data are used for land use classification along with LiDAR elevation data respectively. The results show that the classification accuracy from the normalized intensity data is higher than that from raw LiDAR intensity data and also indicate that the calibration of LiDAR intensity data is necessary in the application of land use classification.

Citation Download Citation

Dong Li, Cheng Wang, She-Zhou Luo, and Zheng-Li Zuo "Airborne lidar intensity calibration and application for land use classification", Proc. SPIE 9262, Lidar Remote Sensing for Environmental Monitoring XIV, 926212 (17 November 2014); https://doi.org/10.1117/12.2069014

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