Filtering Airborne Laser Scanning Data with Morphological Methods

Abstract

Filtering methods based on morphological operations have been developed in some previous studies. The biggest challenge for these methods is how to keep the terrain features unchanged while using large window sizes for the morphological opening. Zhang et al. (2003) tried to achieve this goal, but their method required the assumption that the slope is constant. This paper presents a new method to achieve this goal without such restrictions, and methods for filling missing data and removing outliers are proposed. The experimental test results using the ISPRS Commission III/WG3 dataset show that this method performs well for most sites, except those with missing data due to the lack of overlap between swaths. This method also shows encouraging results for laser data with low pulse density.

Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners

“…The crown returns reflected above CBH were transformed to the CHM [32]. The CGV values derived from CHM were calculated using the "Surface Volume Calculation Module" of ArcInfo program [33] (Figure 3(c)).…”

Implications of differing input data sources and approaches upon forest carbon stock estimation

“…The reflected pulses can be categorized as either first or last pulse returns (Lim et al 2003). Although LIDAR pulses interact with the terrain and all materials above the ground to produce a complex cloud of points, increasingly reliable post-processing procedures for distinguishing between ground and object points are being implemented (e.g., Roggero 2001; Sithole and Vosselman 2004;Chen et al 2007). More advanced LIDAR systems allow multiple returns to be recorded for each emitted pulse.…”

Remote sensing of environmental change over China: A review

“…Most other types of changes can be quantitatively characterized. Such changes can be directly obtained by comparing measurements taken at different times [17][18][19]. Comparison methods include statistical regression models [20][21][22][23], inversion of physical models [24][25][26], or data assimilation [27,28].…”