{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T06:30:00Z","timestamp":1762929000231,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T00:00:00Z","timestamp":1681948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education","award":["K2021-6","2021B1111610001","2021B1212100003"],"award-info":[{"award-number":["K2021-6","2021B1111610001","2021B1212100003"]}]},{"name":"Science and Technology Program of Guangdong Province, China","award":["K2021-6","2021B1111610001","2021B1212100003"],"award-info":[{"award-number":["K2021-6","2021B1111610001","2021B1212100003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing technologies are suitable for detecting marine oil-gas leakages on a large scale. It is important to structure an accurate method for detecting marine oil-gas leakages in varied remote sensing images. However, traditional spectral indexes have limited applicability. Machine learning methods need plenty of training and testing samples to establish the optimized models, which is too rigorous for satellite images. Thus, we proposed a multi-scale encoding (MSE) method with spectral shape information (SSI) to detect the oil-gas leakages in multi-source remote sensing data. First, the spectral amplitude information (SAI) and SSI of the original spectra were encoded into a series of code words according to the scales. Then, the differential code words of the marine oil-gas leakage objects were extracted from the SAI and SSI code words. Finally, the pixels of the encoded hyperspectral image (HSI) and multispectral image (MSI) would be determined by the differential code words. Seven images captured by different platforms\/sensors (Landsat 7, Landsat 8, MODIS, Sentinel 2, Zhuhai-1, and AVIRIS) were used to validate the performance of the proposed method. The experimental results indicated that the MSE method with SSI was convergent and could detect the oil-gas leakages accurately in different images using a small set of samples.<\/jats:p>","DOI":"10.3390\/rs15082184","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T01:33:43Z","timestamp":1682040823000},"page":"2184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Multi-Scale Encoding (MSE) Method with Spectral Shape Information (SSI) for Detecting Marine Oil-Gas Leakages"],"prefix":"10.3390","volume":"15","author":[{"given":"Dong","family":"Zhao","sequence":"first","affiliation":[{"name":"Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Wuhan 434023, China"},{"name":"College of Geophysics and Petroleum Resources, Yangtze University, Wuhan 434023, China"}]},{"given":"Bin","family":"Tan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510670, China"},{"name":"Surveying and Mapping Institute Lands and Resource Department of Guangdong Province, Guangzhou 529001, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1021\/acs.est.5b05356","article-title":"Ultraviolet Radiation Enhances the Toxicity of Deepwater Horizon Oil to Mahi-mahi (Coryphaena hippurus) embryo","volume":"50","author":"Alloy","year":"2016","journal-title":"Environ. 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