Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Light Detection And Ranging (LiDAR) data have proven to be very effective in the estimation of parameters for forestry applications. Hover, little research has been done regarding the multitemporal analysis of these data.   propose a novel hierarchical change detection approach that first performs the detection of major changes (e.g., harvested trees) and then focuses on the detection of minor changes (e.g., single tree growth), using multitemporal LiDAR data having different point densities. Splitting the change detection problem allows us to analyze the different types of changes with different techniques. In particular, the detection of minor changes is carried out directly on the point clouds in order to exploit all the informative content of the LiDAR data. The approach has been tested on a dataset acquired in 2010 and 2014 on a complex forest area located in the Southern Italian Alps. The experimental results confirm the effectiveness of the proposed approach.
['Daniele Marinelli', 'Claudia Paris', 'Lorenzo Bruzzone']
I am writing a research paper on a idea Fusion of high and very high density LiDAR data for 3D forest change detection
[{"from": "human", "value": "I am writing a research paper on a idea Fusion of high and very high density LiDAR data for 3D forest change detection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Light Detection And Ranging (LiDAR) data have proven to be very effective in the estimation of parameters for forestry applications. Hover, little research has been done regarding the multitemporal analysis of these data.   propose a novel hierarchical change detection approach that first performs the detection of major changes (e.g., harvested trees) and then focuses on the detection of minor changes (e.g., single tree growth), using multitemporal LiDAR data having different point densities. Splitting the change detection problem allows us to analyze the different types of changes with different techniques. In particular, the detection of minor changes is carried out directly on the point clouds in order to exploit all the informative content of the LiDAR data. The approach has been tested on a dataset acquired in 2010 and 2014 on a complex forest area located in the Southern Italian Alps. The experimental results confirm the effectiveness of the proposed approach."}]