{"title":"基于规则的RGB卫星图像单个树冠自动检测方法","authors":"Tanqiu Jiang, Ziyu Xiong","doi":"10.1109/CSAIEE54046.2021.9543379","DOIUrl":null,"url":null,"abstract":"Along with the rapid growth of wildfire events around the globe, the appeal to a better forest management strategy is becoming increasingly stronger recently. “Tree Delineation”, which refers to the process of identifying each individual tree from images, is a crucial element in the fields of forest management and remote sensing. Many efforts have been done to locate each individual tree in an image, but the vast majority of the researches were not based on the RGB images that are the most common and the most easily available at a large scale. In our study, we used RGB satellite images from Google Earth and attempted to identify each tree in the images with a rule-based methodology. Our method involves steps including recognizing vegetation, isolating trees, and locating local maxima. The result of our algorithm is comparable to labeling trees manually, and the robustness was confirmed by repeating the same approach on multiple images of different locations.","PeriodicalId":376014,"journal":{"name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rule-Based Approach to the Automatic Detection of Individual Tree Crowns in RGB Satellite Images\",\"authors\":\"Tanqiu Jiang, Ziyu Xiong\",\"doi\":\"10.1109/CSAIEE54046.2021.9543379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Along with the rapid growth of wildfire events around the globe, the appeal to a better forest management strategy is becoming increasingly stronger recently. “Tree Delineation”, which refers to the process of identifying each individual tree from images, is a crucial element in the fields of forest management and remote sensing. Many efforts have been done to locate each individual tree in an image, but the vast majority of the researches were not based on the RGB images that are the most common and the most easily available at a large scale. In our study, we used RGB satellite images from Google Earth and attempted to identify each tree in the images with a rule-based methodology. Our method involves steps including recognizing vegetation, isolating trees, and locating local maxima. The result of our algorithm is comparable to labeling trees manually, and the robustness was confirmed by repeating the same approach on multiple images of different locations.\",\"PeriodicalId\":376014,\"journal\":{\"name\":\"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)\",\"volume\":\"30 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSAIEE54046.2021.9543379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSAIEE54046.2021.9543379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Rule-Based Approach to the Automatic Detection of Individual Tree Crowns in RGB Satellite Images
Along with the rapid growth of wildfire events around the globe, the appeal to a better forest management strategy is becoming increasingly stronger recently. “Tree Delineation”, which refers to the process of identifying each individual tree from images, is a crucial element in the fields of forest management and remote sensing. Many efforts have been done to locate each individual tree in an image, but the vast majority of the researches were not based on the RGB images that are the most common and the most easily available at a large scale. In our study, we used RGB satellite images from Google Earth and attempted to identify each tree in the images with a rule-based methodology. Our method involves steps including recognizing vegetation, isolating trees, and locating local maxima. The result of our algorithm is comparable to labeling trees manually, and the robustness was confirmed by repeating the same approach on multiple images of different locations.