Chuanghai ZHU, Xuehong CHEN, Jin CHEN, Yuheng YUAN, Kai TANG
{"title":"A Siamese Nested-UNet for change detection in Posterior Probability Space （SNU-PS）","authors":"Chuanghai ZHU, Xuehong CHEN, Jin CHEN, Yuheng YUAN, Kai TANG","doi":"10.11834/jrs.20233070","DOIUrl":"https://doi.org/10.11834/jrs.20233070","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135794724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of topography analysis based on multi-source data in the construction of the International Lunar Research Station","authors":"Xing DU, Zhizhong KANG, Teng HU, Meng XIAO, Mo LI","doi":"10.11834/jrs.20233011","DOIUrl":"https://doi.org/10.11834/jrs.20233011","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135101431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.34133/remotesensing.0057
Anxin Ding, Z. Jiao, Xiaoning Zhang, Yadong Dong, A. Kokhanovsky, Jing Guo, Hailan Jiang
The MODerate Resolution Imaging Spectroradiometer (MODIS) MCD43A products have been extensively applied in the remote sensing field, but recent researchers have demonstrated that these products still had the potential to be further improved by using the latest development of the kernel-driven model [RossThick-LiSparseReciprocal-Snow (RTLSRS)] in snow-covered areas, since the MCD43A product algorithm [RossThick-LiSparseReciprocal (RTLSR)] needed to be improved for the accurate simulation of snow bidirectional reflectance distribution function (BRDF) signatures. In this paper, we proposed a practical approach to improve the MCD43A products, which used the Polarization and Directionality of the Earth's Reflectance (POLDER) observations and random forest algorithm to establish the relationship between the BRDF parameters (MCD43A1) estimated by the RTLSR and RTLSRS models. We applied this relationship to correct the MCD43A1 product and retrieve the corresponding albedo (MCD43A3) and nadir reflectance (MCD43A4). The results obtained highlight several aspects: (a) The proposed approach can perform well in correcting BRDF parameters [root mean square error (RMSE) = ~0.04]. (b) The corrected BRDF parameters were then used to retrieve snow albedo, which matched up quite well with the results of the RTLSRS model. (c) Finally, the snow albedo retrieved by the proposed approach was assessed using ground-based albedo observations. Results indicated that the retrieved snow albedo showed a higher accuracy as compared to the station measurements (RMSE = 0.055, bias = 0.005), which was better than the results of the MODIS albedo product (RMSE = 0.064, bias = −0.018), especially at large angles. These results demonstrated that this proposed approach presented the potential to further improve the MCD43A products in snow-covered areas.
{"title":"A Practical Approach to Improve the MODIS MCD43A Products in Snow-Covered Areas","authors":"Anxin Ding, Z. Jiao, Xiaoning Zhang, Yadong Dong, A. Kokhanovsky, Jing Guo, Hailan Jiang","doi":"10.34133/remotesensing.0057","DOIUrl":"https://doi.org/10.34133/remotesensing.0057","url":null,"abstract":"The MODerate Resolution Imaging Spectroradiometer (MODIS) MCD43A products have been extensively applied in the remote sensing field, but recent researchers have demonstrated that these products still had the potential to be further improved by using the latest development of the kernel-driven model [RossThick-LiSparseReciprocal-Snow (RTLSRS)] in snow-covered areas, since the MCD43A product algorithm [RossThick-LiSparseReciprocal (RTLSR)] needed to be improved for the accurate simulation of snow bidirectional reflectance distribution function (BRDF) signatures. In this paper, we proposed a practical approach to improve the MCD43A products, which used the Polarization and Directionality of the Earth's Reflectance (POLDER) observations and random forest algorithm to establish the relationship between the BRDF parameters (MCD43A1) estimated by the RTLSR and RTLSRS models. We applied this relationship to correct the MCD43A1 product and retrieve the corresponding albedo (MCD43A3) and nadir reflectance (MCD43A4). The results obtained highlight several aspects: (a) The proposed approach can perform well in correcting BRDF parameters [root mean square error (RMSE) = ~0.04]. (b) The corrected BRDF parameters were then used to retrieve snow albedo, which matched up quite well with the results of the RTLSRS model. (c) Finally, the snow albedo retrieved by the proposed approach was assessed using ground-based albedo observations. Results indicated that the retrieved snow albedo showed a higher accuracy as compared to the station measurements (RMSE = 0.055, bias = 0.005), which was better than the results of the MODIS albedo product (RMSE = 0.064, bias = −0.018), especially at large angles. These results demonstrated that this proposed approach presented the potential to further improve the MCD43A products in snow-covered areas.","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44355529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hu Huacan, Jianjun Zhu, Haiqiang Fu, Juan M. Lopez-Sanchez, Gómez Cristina, Tao Zhang, Kui Liu
{"title":"Large-Scale Sub-Canopy Topography Estimation From Tandem-X InSAR and ICESat-2 Data Using Machine Learning Method","authors":"Hu Huacan, Jianjun Zhu, Haiqiang Fu, Juan M. Lopez-Sanchez, Gómez Cristina, Tao Zhang, Kui Liu","doi":"10.11834/jrs.20233152","DOIUrl":"https://doi.org/10.11834/jrs.20233152","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134981225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A review of research on land use/cover change and its impact on forest carbon balance","authors":"Zihao Huang, Huaqiang Du, Xuejian Li, Fangjie Mao","doi":"10.11834/jrs.20233169","DOIUrl":"https://doi.org/10.11834/jrs.20233169","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"320 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135357592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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