{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T04:53:19Z","timestamp":1775710399804,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2016,4,22]],"date-time":"2016-04-22T00:00:00Z","timestamp":1461283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent decades, plastic-mulched farmland has expanded rapidly in China as well as in the rest of the world because it results in marked increases of crop production. However, plastic-mulched farmland significantly influences the environment and has so far been inadequately investigated. Accurately monitoring and mapping plastic-mulched farmland is crucial for agricultural production, environmental protection, resource management, and so on. Monitoring plastic-mulched farmland using moderate-resolution remote sensing data is technically challenging because of spatial mixing and spectral confusion with other ground objects. This paper proposed a new scheme that combines spectral and textural features for monitoring the plastic-mulched farmland and evaluates the performance of a Support Vector Machine (SVM) classifier with different kernel functions using Landsat-8 Operational Land Imager (OLI) imagery. The textural features were extracted from multi-bands OLI data using a Grey Level Co-occurrence Matrix (GLCM) algorithm. Then, six combined feature sets were developed for classification. The results indicated that Landsat-8 OLI data are well suitable for monitoring plastic-mulched farmland; the SVM classifier with a linear kernel function is superior both to other kernel functions and to two other widely used supervised classifiers: Maximum Likelihood Classifier (MLC) and Minimum Distance Classifier (MDC). For the SVM classifier with a linear kernel function, the highest overall accuracy was derived from combined spectral and textural features in the 90\u00b0 direction (94.14%, kappa 0.92), followed by the combined spectral and textural features in the 45\u00b0 (93.84%, kappa 0.92), 135\u00b0 (93.73%, kappa 0.92), 0\u00b0 (93.71%, kappa 0.92) directions, and the spectral features alone (93.57%, kappa 0.91). Spectral features make a more significant contribution to monitoring the plastic-mulched farmland; adding textural features from medium resolution imagery provide only limited improvement in accuracy.<\/jats:p>","DOI":"10.3390\/rs8040353","type":"journal-article","created":{"date-parts":[[2016,4,25]],"date-time":"2016-04-25T09:55:00Z","timestamp":1461578100000},"page":"353","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":96,"title":["Monitoring Plastic-Mulched Farmland by Landsat-8 OLI Imagery Using Spectral and Textural Features"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6434-8570","authenticated-orcid":false,"family":"Hasituya","sequence":"first","affiliation":[{"name":"Key Laboratory of Agri-informatics, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, No. 12, Zhongguancun Nan Dajie, Beijing 100081, China"}]},{"given":"Zhongxin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agri-informatics, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, No. 12, Zhongguancun Nan Dajie, Beijing 100081, China"}]},{"given":"Limin","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agri-informatics, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, No. 12, Zhongguancun Nan Dajie, Beijing 100081, China"}]},{"given":"Wenbin","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agri-informatics, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, No. 12, Zhongguancun Nan Dajie, Beijing 100081, China"}]},{"given":"Zhiwei","family":"Jiang","sequence":"additional","affiliation":[{"name":"National Meteorological Information Center, China Meteorological Administration, No. 46, Zhongguancun Nan Dajie, Beijing 100081, China"}]},{"given":"He","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agri-informatics, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, No. 12, Zhongguancun Nan Dajie, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,4,22]]},"reference":[{"key":"ref_1","first-page":"135","article-title":"Effects of mulching with different kinds of plastic film on growth and water use efficiency of winter wheat in Weibei Highland","volume":"28","author":"Bai","year":"2010","journal-title":"Agric. 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