Converting along-track photons into a point-region quadtree to assist with ICESat-2-based canopy cover and ground photon detection

Abstract

The advanced laser altimetry satellite—the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2)1—is a potentially feasible, rapid and effective tool for monitoring carbon cycle and carbon storage to support the sustainable development of Earth system at landscape-to-global scales. To assist with these scientific goals, accurate signal photon detection is required. In this study, we attempted to develop an effective ICESat-2-based signal detection algorithm for different land covers by converting the along-track photons into a point-region (PR)2 quadtree. Firstly, we performed photon homogenization of the background photon. The total number of divisions in the process of converting the spatial distribution of the photons into a point-region quadtree was then calculated. Finally, the signal photons were detected with the appropriate thresholds. For complex woodland areas, the above steps should be performed twice. The results showed that the signal detection algorithm performs well in preserving signal photons and identifying noise photons. The value of F-measure (F)3 obtained at medium and low noise rates are all above 0.9. For more complex woodland areas, the strategy of calculating twice is helpful, giving a high-accuracy performance (F greater than 0.97). The proposed signal detection algorithm enriches an available reference for extracting signal photons from ICESat-2 altimetry data to meet the challenge of achieving carbon neutrality.