{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T22:27:45Z","timestamp":1765232865466,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,3,9]],"date-time":"2020-03-09T00:00:00Z","timestamp":1583712000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61635002"],"award-info":[{"award-number":["61635002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Mixed pixels commonly exist in low-resolution remote sensing images, and they are the key factors hindering the classification of land covers and high-precision mapping. To obtain the spatial information at the subpixel level, subpixel mapping (SPM) technologies, including the pixel-swapping algorithm (PSA), that use the unmixed proportions of various land covers and allocate subpixel land covers have been proposed. However, the PSA often falls into a local optimum solution. In this paper, we propose a SPM method, the PSA_MSA algorithm, that combines the PSA and the modified simulated annealing algorithm to find the global optimum solution. The modified simulated annealing algorithm swaps subpixels within a certain range to escape the local optimum solution. The method also optimizes all the mixed pixels in a randomized sequence to further improve the mapping accuracy. The experimental results demonstrate that the proposed PSA_MSA algorithm outperforms the existing PSA-based algorithms for SPM. The images with different spatial dependences are tested and the results show that the proposed algorithm is more suitable for images with high spatial autocorrelation. In addition, the effect of proportion error is analyzed by adding it in the experiments. The result shows that a higher proportion error rate leads to larger degradation of the subpixel mapping accuracy. Finally, the performance of PSA_MSA algorithm with different ranges of selection on subpixel-swapping is analyzed.<\/jats:p>","DOI":"10.3390\/s20051503","type":"journal-article","created":{"date-parts":[[2020,3,10]],"date-time":"2020-03-10T11:59:36Z","timestamp":1583841576000},"page":"1503","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Combining Pixel Swapping and Simulated Annealing for Land Cover Mapping"],"prefix":"10.3390","volume":"20","author":[{"given":"Lijuan","family":"Su","sequence":"first","affiliation":[{"name":"Key Laboratory of Precision Opto-mechatronics Technology Sponsored by Ministry of Education, School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Opto-mechatronics Technology Sponsored by Ministry of Education, School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Yuan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Opto-mechatronics Technology Sponsored by Ministry of Education, School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyi","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Opto-mechatronics Technology Sponsored by Ministry of Education, School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4165","DOI":"10.1109\/TGRS.2018.2828042","article-title":"Hyperspectral Image Super-Resolution Based on Spatial and Spectral Correlation Fusion","volume":"56","author":"Yi","year":"2018","journal-title":"IEEE Trans. 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