Atmospheric correction is a fundamental process of ocean color remote sensing to remove the atmospheric effect from the top-of-atmosphere. Generally, Near Infrared (NIR) based algorithms perform well for clear waters,...
详细信息
Atmospheric correction is a fundamental process of ocean color remote sensing to remove the atmospheric effect from the top-of-atmosphere. Generally, Near Infrared (NIR) based algorithms perform well for clear waters, while Ultraviolet (UV) based algorithms can obtain good results for turbid waters. However, the latter tends to produce noisy patterns for clear waters. An ideal and practical solution to deal with such a dilemma is to apply NIR- and UV-based algorithms for clear and turbid waters, respectively. We propose a novel atmospheric correction method that integrates the advantages of UV- and NIR-based atmospheric correction (AC) algorithms for coastal ocean color remote sensing. The new approach is called UV-NIR combined AC algorithm. The performance of the new algorithm is evaluated based on match-ups between GOCI images and the AERONET-OC dataset. The results show that the values of retrieved Rrs (Remote Sensing Reflectance) at visible bands agreed well with the in-situ observations. Compared with the SeaDAS (SeaWiFS Data Analysis System) standard NIR algorithm, the new AC algorithm can achieve better precision and provide more available data.
In the earthquake rescue, the unmanned aerial vehicle (UAV) equipped with radar life detector can be used for trapped people searching. In order to shorten the time of UAV detection, we propose a coupling method of Di...
详细信息
ISBN:
(纸本)9781538680988;9781538680971
In the earthquake rescue, the unmanned aerial vehicle (UAV) equipped with radar life detector can be used for trapped people searching. In order to shorten the time of UAV detection, we propose a coupling method of Dijkstra's algorithm and simulated annealing (SA) algorithm to optimize the search path. Concisely, the mathematical model is further abstracted as the Traveling Salesman Problem (TSP) and the shortest loop can be obtained by SA algorithm. We implement this algorithm to a real earthquake event in Jiuzhaigou (Sichuan Province, China). Moreover, the digital elevation model (DEM) data is extracted from Google Earth to demonstrate the real geo-environment. Setting six critical areas as our life detection targets, UAV 3D path simulation is conducted with MATLAB. The results indicate that our method can achieve the function of obstacle avoidance and speed up the search process obviously.
暂无评论