Monitoring geomorphologic processes from 3-D correlation of optical images and LiDAR data

遥感数据量的迅速增加原则上应有助于准确监测地球表面的变化，并有助于收集关于气候对地貌演变影响的客观信息。然而，利用这些数据的方法却很落后。 该项目旨在通过以下方式应对这一挑战：（1）开发一种新方法，将三维光学图像（来自卫星和飞机）与LiDAR（光探测和测距）数据进行配准;（2）测试概念验证应用程序，以监测沙丘动态。该团队建议开发新方法，以便通过高分辨率光学图像和激光雷达数据对地貌过程引起的地球表面变化进行三维跟踪。这些方法将作为COSI-corr软件包中的新工具实施。这些技术将为研究风成过程（特别是沙的搬运和沙丘动态）提供关键的观测数据。该项目包括至少一个测试案例的应用程序，以证明所提出的方法的性能。

The rapidly increasing volume of remote sensing data should, in principle, allow accurate monitoring Earth surface changes and help gather objective information about the impact of climate on landscape evolution. However, methods to exploit these data are lagging behind. This project aims to address this challenge through (1) development of a new method to co-register in three dimensions optical images (from satellites and aircraft) with LiDAR (Light Detection And Ranging) data; and (2) test proof-of-concept applications to monitor sand dune dynamics. The team proposes to develop new methods to allow 3-D tracking of Earth surface changes due to geomorphic processes from high-resolution optical images and LiDAR data. The methods will be implemented as new tools in the COSI-corr software package. These techniques would provide key observational data to study aeolian processes (sand transport and dune dynamics in particular). The project includes application to at least one test case to demonstrate the performance of the proposed methods.