{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T23:19:47Z","timestamp":1778800787265,"version":"3.51.4"},"reference-count":82,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,7]],"date-time":"2022-02-07T00:00:00Z","timestamp":1644192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41867012"],"award-info":[{"award-number":["41867012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"International Network for Bamboo and Rattan (INBAR)","award":["041902006"],"award-info":[{"award-number":["041902006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>It is of great significance to understand the extent and distribution of bamboo for its valuable ecological services and economic benefits. However, it is challenging to map bamboo using remote sensing images over a large area because of the similarity between bamboo and other vegetation types, the availability of clear optical images, huge workload of image processing, and sample collection. In this study, we use the Landsat 8 times series images archive to map bamboo forests in China via the Google Earth engine. Several spectral indices were calculated and used as classification features, including the normalized difference vegetation index (NDVI), the normalized difference moisture index (NDMI) and textural features of the gray-level co-occurrence matrix (GLCM). We found that the bamboo forest covered an area of 709.92 \u00d7 104 hectares, with the provinces of Fujian, Jiangxi, and Zhejiang containing the largest area concentrations. The bamboo forest map was accurate and reliable with an average producer\u2019s accuracy of 89.97%, user\u2019s accuracy of 78.45% and kappa coefficient of 0.7789. In addition, bamboo was mainly distributed in forests with an elevation of 300\u20131200 m above sea level, average annual precipitation of 1200\u20131500 mm and average day land surface temperature of 19\u201325 \u00b0C. The NDMI is particularly useful in differentiating bamboo from other vegetation because of the clear difference in canopy moisture content, whilst NDVI and elevation are also helpful to improve the bamboo classification accuracy. The bamboo forest map will be helpful for bamboo forest industry planning and could be used for evaluating the ecological service of the bamboo forest.<\/jats:p>","DOI":"10.3390\/rs14030762","type":"journal-article","created":{"date-parts":[[2022,2,7]],"date-time":"2022-02-07T08:38:48Z","timestamp":1644223128000},"page":"762","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Bamboo Forest Mapping in China Using the Dense Landsat 8 Image Archive and Google Earth Engine"],"prefix":"10.3390","volume":"14","author":[{"given":"Shuhua","family":"Qi","sequence":"first","affiliation":[{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research (Ministry of Education), School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5465-9693","authenticated-orcid":false,"given":"Bin","family":"Song","sequence":"additional","affiliation":[{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research (Ministry of Education), School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 510275, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Earth Sciences, The University of Hong Kong, Pokfulam, Hong Kong 999077, China"},{"name":"Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Luo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research (Ministry of Education), School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meinan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianwei","family":"Xiong","sequence":"additional","affiliation":[{"name":"Key Laboratory of Poyang Lake Wetland and Watershed Research (Ministry of Education), School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,7]]},"reference":[{"key":"ref_1","unstructured":"Yi, T., Shi, J., Ma, L., Wang, H., and Yang, L. 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