遥感学报最新文献

{"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}

{"title":"A review of paddy rice mapping with remote sensing technology","authors":"Xinyi Gao, Hong Chi, Jinliang Huang, Feng Ling, Yifei Han, Xiaofeng Jia, Yifan Li, Duan Huang, Jinwei Dong","doi":"10.11834/jrs.20233014","DOIUrl":"https://doi.org/10.11834/jrs.20233014","url":null,"abstract":"æ°´ç¨»æ˜¯äººç±»çš„ä¸»è¦ç²®é£Ÿä½œç‰©ä¹‹ä¸€ï¼ŒåŠæ—¶å‡†ç¡®çš„èŽ·å–æ°´ç¨»é¢ç§¯åˆ†å¸ƒå’Œæ—¶ç©ºå˜åŒ–å¯¹ç²®é£Ÿæ”¿ç­–åˆ¶å®šå ·æœ‰é‡è¦çš„å‚è€ƒæ„ä¹‰ã€‚æœ¬æ–‡å›´ç»•â€œæ°´ç¨»é¥æ„Ÿåˆ¶å›¾â€ç ”ç©¶ä¸»é¢˜ï¼Œé¦–å ˆå›žé¡¾è°ƒç ”å›½å† å¤–æ–‡çŒ®èµ„æ–™ï¼Œç³»ç»Ÿæ¢³ç†äº†æ°´ç¨»çš„ç”Ÿç†ç”Ÿé•¿è¿‡ç¨‹å’Œä¸»è¦çš„ç§æ¤æ¨¡å¼ã€‚å ¨çƒèŒƒå›´å† ï¼Œæ°´ç¨»ç§æ¤é›†ä¸­åœ¨ä¸œå—äºšåœ°åŒºï¼›ä»Žå ¨å›½èŒƒå›´çœ‹ï¼Œå•å­£ç¨»äº§åŒºä¸»è¦ä½äºŽä¸œåŒ—åœ°åŒºå’Œé•¿æ±Ÿä¸­ä¸‹æ¸¸åœ°åŒºï¼›åŒå­£ç¨»å’Œä¸‰å­£ç¨»äº§åŒºä½äºŽæ¹–å—ã€æ±Ÿè¥¿ã€å¹¿ä¸œç­‰åŽå—çœä»½ã€‚å ¶æ¬¡ï¼Œå—äº‘é›¨å½±å“ï¼Œæ—©æœŸæ°´ç¨»åˆ¶å›¾ä»¥é›·è¾¾æ•°æ®ä¸ºä¸»ï¼Œéšç€é¥æ„Ÿæ•°æ®æºæ—¥ç›Šä¸°å¯Œï¼Œå ‰å­¦å’Œé›·è¾¾æ•°æ®ååŒåº”ç”¨äºŽæ°´ç¨»é¥æ„Ÿåˆ¶å›¾ï¼›åœ¨é‡ç‚¹åˆ†æžæ°´ç¨»çš„â€œï¼ˆé¥æ„Ÿï¼‰ä¿¡å·-空间-æ—¶é—´â€ç‰¹å¾çš„åŸºç¡€ä¸Šï¼ŒæŽ¢è®¨äº†æ°´ç¨»é¥æ„Ÿåˆ¶å›¾ä¸­å ¸åž‹å ‰å­¦æ¤è¢«æŒ‡æ•°å’Œé›·è¾¾åŽå‘æ•£å°„ç³»æ•°ï¼›å¹¶ä»Žä¼ ç»Ÿæœºå™¨å­¦ä¹ å’Œæ·±åº¦å­¦ä¹ ä¸¤ä¸ªæ–¹é¢æ€»ç»“äº†çŽ°é˜¶æ®µæ°´ç¨»é¥æ„Ÿåˆ¶å›¾çš„ä¸»æµæ–¹æ³•ã€‚ç„¶åŽï¼Œä»Žæœºå™¨å­¦ä¹ æ¨¡åž‹ã€å¤šæºé¥æ„Ÿæ•°æ®èžåˆä»¥åŠé¥æ„Ÿè®¡ç®—äº‘å¹³å°ä¸‰ä¸ªæ–¹é¢å½’çº³äº†æ°´ç¨»é¥æ„Ÿåˆ¶å›¾çš„åº”ç”¨çŽ°çŠ¶ã€‚æ€»ç»“å‘çŽ°ç›®å‰æ°´ç¨»åˆ¶å›¾ç ”ç©¶å­˜åœ¨ä»¥ä¸‹éš¾ç‚¹ï¼šï¼ˆ1）由于相似生长周期植物的存在导致水稻的漏分、错分；（2ï¼‰å ‰å­¦å’Œé›·è¾¾æ•°æ®éƒ½å­˜åœ¨æ—¶åºè§‚æµ‹ä¸è¿žç»­çš„çŽ°è±¡ï¼›ï¼ˆ3ï¼‰åœ°å½¢ç ´ç¢ŽåŒºåŸŸæˆ–å¤šå­£ã€è½®ä½œæ°´ç¨»ç§æ¤åœ°åŒºçš„åˆ¶å›¾å›°éš¾è¾ƒå¤§ï¼›ï¼ˆ4）制图方法的泛化问题。针对这些问题，本文从水稻物候特征发掘、水稻时序观测数据获取手段、水稻遥感制图空间分辨率改进等方面探讨了水稻遥感制图的发展方向：（1）水稻物候期遥感信号特征挖掘；（2）覆盖水稻完整生长期的时序遥感数据获取；（3）水稻遥感制图空间分辨率提升；（4ï¼‰å ‰å­¦å’Œé›·è¾¾æ•°æ®çš„ååŒåº”ç”¨ã€‚","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"50 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":"135101794","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 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}

{"title":"Classifier Mechanism Embedded Feature Extraction Method for Hyperspectral Images","authors":"Changda XING, Meiling WANG, Yongchang XU, Zhisheng WANG","doi":"10.11834/jrs.20233065","DOIUrl":"https://doi.org/10.11834/jrs.20233065","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"282 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":"135550130","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":"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":"Object Units and Transformer Networks Combined Urban Functional Zone Classification Method","authors":"Weipeng LU, Qingkang He, Jialing LI, Shiyi LI, Chao TAO","doi":"10.11834/jrs.20233036","DOIUrl":"https://doi.org/10.11834/jrs.20233036","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"51 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":"135102129","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}

{"title":"Edge-perception Enhanced Segmentation Method for High-resolution Remote Sensing Image","authors":"Chunyan YU, Donglin LI, Meiping SONG, Haoyang YU, Chein-I Chang","doi":"10.11834/jrs.20233098","DOIUrl":"https://doi.org/10.11834/jrs.20233098","url":null,"abstract":"","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"21 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":"135758452","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":"Mapping forest type and tree species fractions of China’s cold-temperate forest based on synthetically mixed data and random forest regression","authors":"Mengyu Wang, Feng Zhao, Yong Pang, Ran Meng, Wen Jia, Chao Yue","doi":"10.11834/jrs.20233103","DOIUrl":"https://doi.org/10.11834/jrs.20233103","url":null,"abstract":"å¯’æ¸©å¸¦æ£®æž—æ˜¯é™†åœ°ä¸Šåˆ†å¸ƒé¢ç§¯æœ€å¹¿çš„æ£®æž—ç”Ÿæ€ç³»ç»Ÿï¼Œå ·æœ‰é‡è¦çš„ç”Ÿæ€å’Œç¤¾ä¼šç»æµŽä»·å€¼ã€‚å®šé‡åˆ»ç”»é•¿æ—¶åºå¯’æ¸©å¸¦æ£®æž—ç±»åž‹å’Œæ ‘ç§è¦†ç›–ä¿¡æ¯å¯¹äºŽé‡åŒ–å ¶ç”Ÿæ€ç³»ç»ŸæœåŠ¡åŠŸèƒ½ä»¥åŠåˆ¶å®šæ£®æž—ç®¡ç†æ”¿ç­–å ·æœ‰é‡è¦æ„ä¹‰ã€‚ç„¶è€Œå—å®žæµ‹è¦†ç›–åº¦æ•°æ®ç¼ºä¹å’Œå¤šå ‰è°±å½±åƒå ‰è°±ä¿¡æ¯æœ‰é™çš„é™åˆ¶ï¼ŒçŽ°æœ‰ç ”ç©¶è¾ƒå°‘æŽ¢è®¨ä¸­åˆ†è¾¨çŽ‡å¤šå ‰è°±æ˜Ÿè½½æ•°æ®ï¼ˆå¦‚Landsatå«æ˜Ÿï¼‰å¯¹ä¸­å›½å¯’æ¸©å¸¦æ£®æž—ç±»åž‹è¦†ç›–åº¦å’Œæ ‘ç§è¦†ç›–åº¦è¿›è¡Œé•¿æ—¶åºåæ¼”çš„å¯è¡Œæ€§ï¼Œå¹¶ä¸”å¯¹äºŽé¥æ„Ÿå½±åƒèŽ·å–æ—¶é—´é¢‘çŽ‡ï¼ˆå•æ—¶ç›¸ã€å¤šæ—¶ç›¸ï¼‰å¯¹åæ¼”ç²¾åº¦çš„å½±å“ä»ç¼ºä¹å®šé‡è¯„ä¼°ã€‚ä¸ºæ­¤ï¼Œæœ¬æ–‡åˆ©ç”¨äººå·¥åˆæˆæ ·æœ¬å’Œéšæœºæ£®æž—å›žå½’æ¨¡åž‹å¯¹é»‘é¾™æ±Ÿçœå­Ÿå®¶å²—æž—åœºçš„æ£®æž—ç±»åž‹å’Œæ ‘ç§è¦†ç›–åº¦åˆ†åˆ«è¿›è¡Œäº†åæ¼”ã€‚å¹¶å°†æ¨¡åž‹åº”ç”¨è‡³1986-2020年的Landsat影像，得到孟家岗林场阔叶林和针叶林35年的覆盖度结果。结果表明：（1）对于森林类型覆盖度反演，基于生长季Landsat波段和植被指数（归一化耕作指数以及缨帽变换系数）的中值特征估算的精度最高，阔叶林覆盖度估算<inline-formula><alternatives><math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\"><msup><mrow><mover accent=\"true\"><mi>R</mi><mo>¯</mo></mover></mrow><mrow><mn mathvariant=\"normal\">2</mn></mrow></msup></math><graphic specific-use=\"big\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"alternativeImage/C83538AF-3C7B-4d5a-81B1-8BD2456A949D-M001.jpg\"><?fx-imagestate width=\"2.96333337\" height=\"2.96333337\"?></graphic><graphic specific-use=\"small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"alternativeImage/C83538AF-3C7B-4d5a-81B1-8BD2456A949D-M001c.jpg\"><?fx-imagestate width=\"2.96333337\" height=\"2.96333337\"?></graphic></alternatives></inline-formula>= 0.76，针叶林覆盖度估算<inline-formula><alternatives><math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\"><msup><mrow><mover accent=\"true\"><mi>R</mi><mo>¯</mo></mover></mrow><mrow><mn mathvariant=\"normal\">2</mn></mrow></msup></math><graphic specific-use=\"big\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"alternativeImage/C83538AF-3C7B-4d5a-81B1-8BD2456A949D-M001.jpg\"><?fx-imagestate width=\"2.96333337\" height=\"2.96333337\"?></graphic><graphic specific-use=\"small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"alternativeImage/C83538AF-3C7B-4d5a-81B1-8BD2456A949D-M001c.jpg\"><?fx-imagestate width=\"2.96333337\" height=\"2.96333337\"?></graphic></alternatives></inline-formula>= 0.71；（2ï¼‰å¯¹äºŽæ ‘ç§è¦†ç›–åº¦åæ¼”ï¼ŒåŸºäºŽå¤šæ—¶ç›¸Landsat波段和植被指数的精度最高，落叶松覆盖度估算<inline-formula><alternatives><math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\"><msup><mrow><mover accent=\"true\"><mi>R</mi><mo>¯</mo></mover></mrow><mrow><mn mathvariant=\"normal\">2</mn></mrow></msup></math><graphic specific-use=\"big\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"alternativeImage/C83538AF-3C7B-4d5a-81B1-8BD2456A","PeriodicalId":38304,"journal":{"name":"Yaogan Xuebao/Journal of Remote Sensing","volume":"188 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":"135501948","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}