Automatic generation of plant distributions for existing and future natural environments using spatial data

摘要: This research proposes an algorithm for the generation of realistic plant distribution both existing and future areas using spatial data. The main motivation this is to be able generate positions 3D visualization natural environments. Current techniques determining are limited. Plant detection from remote sensing domain only detect large plants high-resolution imagery LiDAR Often, type each detected position not known. In addition, data available areas. demonstrates that can generated by dynamic ecological models. These models produce height, biomass, coverage maps proposed must translate as well produces a distribution. A contain small with their corresponding type. To realize this, integrates concepts procedural modeling. Different datasets provided input analyzed obtain information where certain types or cannot placed in target area. was tested on area model. results were validated statistical expert validation methods. showed map correctly distributions general judged most issues because missing due low quality. future, could used different applications research. One possibility improve current technique providing additional about point algorithm.