Ayub Sugara , Yenni P. Sari , Muhamad S. Sangadji , Aninda W. Rudiastuti , Teguh A. Pianto , Vincentius P. Siregar , Syamsul B. Agus , Dewayany Sutrisno
{"title":"利用模糊逻辑方法检测无人机图像数据上海胆种群分布","authors":"Ayub Sugara , Yenni P. Sari , Muhamad S. Sangadji , Aninda W. Rudiastuti , Teguh A. Pianto , Vincentius P. Siregar , Syamsul B. Agus , Dewayany Sutrisno","doi":"10.1016/j.kjs.2025.100389","DOIUrl":null,"url":null,"abstract":"<div><div>Unmanned aerial vehicle (UAV) technology has been widely used to identify the spatial distribution of marine and coastal resources. <em>Diadema setosum</em> plays a crucial role in controlling algae populations in coral reef ecosystems, which would otherwise compete with corals for sunlight. <em>Diadema setosum</em> lives in colonies and generally exists in shallow water areas such as coral, seagrass, and sand. Due to its ecological importance in controlling algae and its economic value as a high-nutrient food source, monitoring and managing the distribution and abundance of Diadema setosum is crucial for sustaining coastal ecosystems. This study aimed to assess the ability of UAV imagery to detect the spatial distribution of <em>Diadema setosum</em> colonies using a simple index ratio approach and fuzzy logic. The study was conducted on the southwest coast of Lancang Island, Seribu Islands, Indonesia, from May 3 to 12, 2018. The results showed that the red-green ratio index (RGRI) band combination from the UAV image was better at detecting <em>Diadema setosum</em> colonies than the green-blue ratio index (GBRI) was. The range of index values for <em>Diadema setosum</em> obtained from GBRI and RGRI transformations were 0.717887–1.989796 and 0.510457–1.183333, respectively. The combination of fuzzy logic and the RGRI band index demonstrated strong performance in detecting the distribution of <em>Diadema setosum</em> colonies, achieving an overall classification accuracy exceeding 90%.</div></div>","PeriodicalId":17848,"journal":{"name":"Kuwait Journal of Science","volume":"52 2","pages":"Article 100389"},"PeriodicalIF":1.2000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detection of sea urchins (Diadema setosum) colony distribution on UAV imagery data using fuzzy logic approach\",\"authors\":\"Ayub Sugara , Yenni P. Sari , Muhamad S. Sangadji , Aninda W. Rudiastuti , Teguh A. Pianto , Vincentius P. Siregar , Syamsul B. Agus , Dewayany Sutrisno\",\"doi\":\"10.1016/j.kjs.2025.100389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Unmanned aerial vehicle (UAV) technology has been widely used to identify the spatial distribution of marine and coastal resources. <em>Diadema setosum</em> plays a crucial role in controlling algae populations in coral reef ecosystems, which would otherwise compete with corals for sunlight. <em>Diadema setosum</em> lives in colonies and generally exists in shallow water areas such as coral, seagrass, and sand. Due to its ecological importance in controlling algae and its economic value as a high-nutrient food source, monitoring and managing the distribution and abundance of Diadema setosum is crucial for sustaining coastal ecosystems. This study aimed to assess the ability of UAV imagery to detect the spatial distribution of <em>Diadema setosum</em> colonies using a simple index ratio approach and fuzzy logic. The study was conducted on the southwest coast of Lancang Island, Seribu Islands, Indonesia, from May 3 to 12, 2018. The results showed that the red-green ratio index (RGRI) band combination from the UAV image was better at detecting <em>Diadema setosum</em> colonies than the green-blue ratio index (GBRI) was. The range of index values for <em>Diadema setosum</em> obtained from GBRI and RGRI transformations were 0.717887–1.989796 and 0.510457–1.183333, respectively. The combination of fuzzy logic and the RGRI band index demonstrated strong performance in detecting the distribution of <em>Diadema setosum</em> colonies, achieving an overall classification accuracy exceeding 90%.</div></div>\",\"PeriodicalId\":17848,\"journal\":{\"name\":\"Kuwait Journal of Science\",\"volume\":\"52 2\",\"pages\":\"Article 100389\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2025-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Kuwait Journal of Science\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2307410825000331\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kuwait Journal of Science","FirstCategoryId":"103","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2307410825000331","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Detection of sea urchins (Diadema setosum) colony distribution on UAV imagery data using fuzzy logic approach
Unmanned aerial vehicle (UAV) technology has been widely used to identify the spatial distribution of marine and coastal resources. Diadema setosum plays a crucial role in controlling algae populations in coral reef ecosystems, which would otherwise compete with corals for sunlight. Diadema setosum lives in colonies and generally exists in shallow water areas such as coral, seagrass, and sand. Due to its ecological importance in controlling algae and its economic value as a high-nutrient food source, monitoring and managing the distribution and abundance of Diadema setosum is crucial for sustaining coastal ecosystems. This study aimed to assess the ability of UAV imagery to detect the spatial distribution of Diadema setosum colonies using a simple index ratio approach and fuzzy logic. The study was conducted on the southwest coast of Lancang Island, Seribu Islands, Indonesia, from May 3 to 12, 2018. The results showed that the red-green ratio index (RGRI) band combination from the UAV image was better at detecting Diadema setosum colonies than the green-blue ratio index (GBRI) was. The range of index values for Diadema setosum obtained from GBRI and RGRI transformations were 0.717887–1.989796 and 0.510457–1.183333, respectively. The combination of fuzzy logic and the RGRI band index demonstrated strong performance in detecting the distribution of Diadema setosum colonies, achieving an overall classification accuracy exceeding 90%.
期刊介绍:
Kuwait Journal of Science (KJS) is indexed and abstracted by major publishing houses such as Chemical Abstract, Science Citation Index, Current contents, Mathematics Abstract, Micribiological Abstracts etc. KJS publishes peer-review articles in various fields of Science including Mathematics, Computer Science, Physics, Statistics, Biology, Chemistry and Earth & Environmental Sciences. In addition, it also aims to bring the results of scientific research carried out under a variety of intellectual traditions and organizations to the attention of specialized scholarly readership. As such, the publisher expects the submission of original manuscripts which contain analysis and solutions about important theoretical, empirical and normative issues.