Morteza Sadeghi , Neda Mohamadzadeh , Lan Liang , Uditha Bandara , Marcellus M. Caldas , Tyler Hatch
{"title":"基于光学梯形模型(OPTRAM)的土壤水分和水体遥感研究","authors":"Morteza Sadeghi , Neda Mohamadzadeh , Lan Liang , Uditha Bandara , Marcellus M. Caldas , Tyler Hatch","doi":"10.1016/j.srs.2023.100105","DOIUrl":null,"url":null,"abstract":"<div><p>Over the past few years, the Optical Trapezoid Model (OPTRAM) has been widely used as a means for high-resolution mapping of surface soil moisture using optical satellite data. In this paper, we propose a new variant of OPTRAM that can map not only soil moisture, but also water bodies such as lakes and rivers. The proposed variant was tested using laboratory experimental data as well as Landsat-8 reflectance observations. Results showed the new OPTRAM variant has greater skill than the original variant in separating land and water pixels. In addition, the new variant showed less sensitivity to the model parameters, and hence, is less user dependent. To quantitatively examine the user-dependency of the model, we analyzed OPTRAM soil moisture based on Landsat-8 satellite images in California, where we varied the model parameters in a plausible range. The correlations of the resulting maps in terms of R<sup>2</sup> between two largely different sets of parameters were found in the range of 0.47-0.52 for the original variant and 0.67-0.76 for the new variant. Because some OPTRAM parameters can be quite uncertain, particularly in wet regions, the reduced sensitivity promises more consistent soil moisture estimates across the range of parameter choices.</p></div>","PeriodicalId":101147,"journal":{"name":"Science of Remote Sensing","volume":"8 ","pages":"Article 100105"},"PeriodicalIF":5.7000,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new variant of the optical trapezoid model (OPTRAM) for remote sensing of soil moisture and water bodies\",\"authors\":\"Morteza Sadeghi , Neda Mohamadzadeh , Lan Liang , Uditha Bandara , Marcellus M. Caldas , Tyler Hatch\",\"doi\":\"10.1016/j.srs.2023.100105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Over the past few years, the Optical Trapezoid Model (OPTRAM) has been widely used as a means for high-resolution mapping of surface soil moisture using optical satellite data. In this paper, we propose a new variant of OPTRAM that can map not only soil moisture, but also water bodies such as lakes and rivers. The proposed variant was tested using laboratory experimental data as well as Landsat-8 reflectance observations. Results showed the new OPTRAM variant has greater skill than the original variant in separating land and water pixels. In addition, the new variant showed less sensitivity to the model parameters, and hence, is less user dependent. To quantitatively examine the user-dependency of the model, we analyzed OPTRAM soil moisture based on Landsat-8 satellite images in California, where we varied the model parameters in a plausible range. The correlations of the resulting maps in terms of R<sup>2</sup> between two largely different sets of parameters were found in the range of 0.47-0.52 for the original variant and 0.67-0.76 for the new variant. Because some OPTRAM parameters can be quite uncertain, particularly in wet regions, the reduced sensitivity promises more consistent soil moisture estimates across the range of parameter choices.</p></div>\",\"PeriodicalId\":101147,\"journal\":{\"name\":\"Science of Remote Sensing\",\"volume\":\"8 \",\"pages\":\"Article 100105\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2023-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666017223000305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666017223000305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A new variant of the optical trapezoid model (OPTRAM) for remote sensing of soil moisture and water bodies
Over the past few years, the Optical Trapezoid Model (OPTRAM) has been widely used as a means for high-resolution mapping of surface soil moisture using optical satellite data. In this paper, we propose a new variant of OPTRAM that can map not only soil moisture, but also water bodies such as lakes and rivers. The proposed variant was tested using laboratory experimental data as well as Landsat-8 reflectance observations. Results showed the new OPTRAM variant has greater skill than the original variant in separating land and water pixels. In addition, the new variant showed less sensitivity to the model parameters, and hence, is less user dependent. To quantitatively examine the user-dependency of the model, we analyzed OPTRAM soil moisture based on Landsat-8 satellite images in California, where we varied the model parameters in a plausible range. The correlations of the resulting maps in terms of R2 between two largely different sets of parameters were found in the range of 0.47-0.52 for the original variant and 0.67-0.76 for the new variant. Because some OPTRAM parameters can be quite uncertain, particularly in wet regions, the reduced sensitivity promises more consistent soil moisture estimates across the range of parameter choices.