[1] |
Zhang P, Hu S, Li W, et al. Improving parcel-level mapping of smallholder crops from vhsr imagery: An ensemble machine-learning-based framework[J]. Remote Sensing, 2021, 13(11): 2146.
doi: 10.3390/rs13112146
|
[2] |
Denize J, Hubert-Moy L, Betbeder J, et al. Evaluation of using sentinel-1 and-2 time-series to identify winter land use in agricultural landscapes[J]. Remote Sensing, 2018, 11(1): 37.
doi: 10.3390/rs11010037
|
[3] |
Xiao X, Boles S, Frolking S, et al. Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images[J]. Remote Sensing of Environment, 2006, 100(1): 95-113.
doi: 10.1016/j.rse.2005.10.004
|
[4] |
王文静, 张霞, 赵银娣, 等. 综合多特征的Landsat 8时序遥感图像棉花分类方法[J]. 遥感学报, 2017, 21(1): 115-124.
|
|
[Wang Wengjing, Zhang Xia, Zhao Yindi, et al. Cotton extraction method of integrated multi-features based on multi-temporal Landsat 8 images[J]. Journal of Remote Sensing, 2017, 21(1): 115-124.]
|
[5] |
Zhang H, Du H, Zhang C, et al. An automated early-season method to map winter wheat using time-series Sentinel-2 data: A case study of Shandong, China[J]. Computers and Electronics in Agriculture, 2021, 182: 105962.
doi: 10.1016/j.compag.2020.105962
|
[6] |
王德军, 姜琦刚, 李远华, 等. 基于Sentinel-2A/B时序数据与随机森林算法的农耕区土地利用分类[J]. 国土资源遥感, 2020, 32(4): 236-243.
|
|
[Wang Dejun, Jiang Qigang, Li Yuanhua, et al. Land use classification of farming areas based on time series Sentinel-2A/B data and random forest algorithm[J]. Remote Sensing for Natural Resources, 2020, 32(4): 236-243.]
|
[7] |
闵钰魁, 柯樱海, 韩月, 等. 融合Sentinel-2和GF-1时序影像的入侵植物互花米草清除动态监测[J]. 遥感学报, 2023, 27(6): 1467-1479.
|
|
[Min Yukui, Ke Yinhai, Han Yue, et al. Dynamic monitoring of invasive Spartina alterniflora clearance via fusion of Sentinel-2 and GF-1 time series images[J]. National Remote Sensing Bulletin, 2023, 27(6): 1467-1479.]
|
[8] |
Fatchurrachman, Rudiyanto, Soh N C, et al. High-resolution mapping of paddy rice extent and growth stages across peninsular malaysia using a fusion of sentinel-1 and 2 time series data in Google Earth Engine[J]. Remote Sensing, 2022, 14(8): 1875.
doi: 10.3390/rs14081875
|
[9] |
Chakhar A, Hernández-López D, Ballesteros R, et al. Improving the accuracy of multiple algorithms for crop classification by integrating sentinel-1 observations with sentinel-2 data[J]. Remote Sensing, 2021, 13(2): 243.
doi: 10.3390/rs13020243
|
[10] |
明義森, 刘启航, 柏荷, 等. 利用光学和SAR遥感数据的若尔盖湿地植被分类与变化监测[J]. 遥感学报, 2023, 27(6): 1414-1425.
|
|
[Ming Yiseng, Liu Qihang, Bai He, et al. Classification and change detection of vegetation in the Ruoergai Wetland using optical and SAR remote sensing data[J]. National Remote Sensing Bulletin, 2023, 27(6): 1414-1425.]
|
[11] |
张琍, 罗文庭, 张皓寰, 等. 时序Sentinel-1和Sentinel-2 数据支持下的鄱阳湖湿地草本植物群落制图分类[J]. 遥感学报, 2023, 27(6): 1362-1375.
|
|
[Zhang Li, Luo Wenting, Zhang Haohuan, et al. Classification scheme for mapping wetland herbaceous plant communities using time series Sentinel-1 and Sentinel-2 data[J]. National Remote Sensing Bulletin, 2023, 27(6): 1362-1375.]
|
[12] |
曹文梅, 刘廷玺, 王喜喜, 等. 科尔沁沙丘草甸相间地区土地利用与覆被识别[J]. 干旱区研究, 2021, 38(2): 526-535.
|
|
[Cao Wenmei, Liu Tingxi, Wang Xixi, et al. Land use and land cover classifications of Horqin Sandy Land dune-meadow areas[J]. Arid Zone Research, 2021, 38(2): 526-535.]
|
[13] |
姚金玺, 王浪, 李建忠, 等. 青海诺木洪地区多源遥感及多特征组合地物分类[J]. 农业工程学报, 2022, 38(3): 247-256.
|
|
[Yao Jinxi, Wang Lang, Li Jianzhong, et al. Multi-source remote sensing and multi-feature combination ground object classification in Nuomuhong areas, Qinghai Province of China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(3): 247-256.]
|
[14] |
Awad M. Google Earth Engine (GEE) cloud computing based crop classification using radar, optical images and Support Vector Machine Algorithm (SVM)[C]// IEEE 3rd International Multidisciplinary Conference on Engineering Technology, 2021: 71-76.
|
[15] |
Virnodkar S, Pachghare V K, Patil V C, et al. Performance evaluation of RF and SVM for sugarcane classification using Sentinel-2 NDVI time-series[C]// Progress in Advanced Computing and Intelligent Engineering: Proceedings of ICACIE, 2021: 163-174.
|
[16] |
Ponganan N, Horanont T, Artlert K, et al. Land Cover Classification using Google Earth Engine’s Object-oriented and Machine Learning Classifier[C]// 2021 2nd International Conference on Big Data Analytics and Practices (IBDAP), IEEE, 2021: 33-37.
|
[17] |
Yao J, Wu J, Xiao C, et al. The classification method study of crops remote sensing with deep learning, machine learning, and Google Earth Engine[J]. Remote Sensing, 2022, 14(12): 2758.
doi: 10.3390/rs14122758
|
[18] |
梁顺林, 白瑞, 陈晓娜, 等. 2019年中国陆表定量遥感发展综述[J]. 遥感学报, 2020, 24 (6): 618-671.
|
|
[Liang Shunlin, Bai Rui, Chen Xiaona, et al. Review of China’s land surface quantitative remote sensing development in 2019[J]. Journal of Remote Sensing, 2020, 24(6): 618-671.]
|
[19] |
邱凤婷, 过志峰, 张宗科, 等. 基于改进SVM分类法的SAR图像水体面积提取研究[J]. 地球信息科学学报, 2022, 24(5): 940-948.
doi: 10.12082/dqxxkx.2022.210095
|
|
[Qiu Fengting, Guo Zhifeng, Zhang Zongke, et al. Water body area extraction from SAR image based on improved SVM classification method[J]. Journal of Geo-information Science, 2022, 24(5): 940-948.]
doi: 10.12082/dqxxkx.2022.210095
|
[20] |
庞海威, 余殿, 任成宝, 等. 宁夏东部半干旱区典型植物群落遥感分类特征[J]. 干旱区研究, 2022, 39(6): 1930-1941.
|
|
[Pang Haiwei, Yu Dian, Ren Chengbao, et al. Remote sensing classification characteristics of typical plant communities in the semi-arid areas of eastern Ningxia[J]. Arid Zone Research, 2022, 39(6): 1930-1941.]
|
[21] |
杨维涛, 孙建国, 马恒利, 等. 地貌形态多尺度综合分类方法[J]. 干旱区研究, 2022, 39(2): 638-645.
|
|
[Yang Weitao, Sun Jianguo, Ma Hengli, et al. A multi-scale integrated classification method for landforms[J]. Arid Zone Research, 2022, 39(2): 638-645.]
|
[22] |
Tassi A, Vizzari M. Object-oriented lulc classification in google earth engine combining snic, glcm, and machine learning algorithms[J]. Remote Sensing, 2020, 12(22): 3776.
doi: 10.3390/rs12223776
|
[23] |
刘通, 任鸿瑞. GEE平台下利用物候特征进行面向对象的水稻种植分布提取[J]. 农业工程学报, 2022, 38(12): 189-196.
|
|
[Liu Tong, Ren Hongrui. Object-oriented extraction of paddy rice planting areas using phenological features from the GEE platform[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(12): 189-196.]
|
[24] |
肖森天, 依力亚斯江·努尔麦麦提, 努尔比耶·穆合塔尔, 等. 基于光学和雷达多源遥感的于田绿洲土壤盐渍化时空分析[J]. 干旱区研究, 2023, 40(1): 59-68.
|
|
[Xiao Sentian, Ilyas Nurmemet, Nuerbiye Muhetaer, et al. Spatial and temporal analysis of soil salinity in Yutian Oasis by combined optical and radar multi-source remote sensing[J]. Arid Zone Research, 2023, 40(1): 59-68.]
|
[25] |
Yang G, Zhao Y, Xing H, et al. Understanding the changes in spatial fairness of urban greenery using time-series remote sensing images: A case study of Guangdong-Hong Kong-Macao Greater Bay[J]. Science of The Total Environment, 2020, 715: 136763.
doi: 10.1016/j.scitotenv.2020.136763
|
[26] |
Achanta R, Susstrunk S. Superpixels and polygons using simple non-iterative clustering[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017: 4651-4660.
|
[27] |
穆学青, 郭向阳, 明庆忠, 等. 黄河流域旅游生态安全的动态演变特征及驱动因素[J]. 地理学报, 2022, 77(3): 714-735.
doi: 10.11821/dlxb202203015
|
|
[Mu Xueqing, Guo Xiangyang, Ming Qingzhong, et al. Dynamic evolution characteristics and driving factors of tourism ecological security in the Yellow River Basin[J]. Acta Geographica Sinica, 2022, 77(3): 714-735.]
doi: 10.11821/dlxb202203015
|
[28] |
王振武, 孙佳骏, 于忠义, 等. 基于支持向量机的遥感图像分类研究综述[J]. 计算机科学, 2016, 43(9): 11-17.
doi: 10.11896/j.issn.1002-137X.2016.09.002
|
|
[Wang Zhenwu, Sun Jiajun, Yu Zhongyi, et al. Review of remote sensing image classification based on support vector machine[J]. Computer Science, 2016, 43(9): 11-17.]
doi: 10.11896/j.issn.1002-137X.2016.09.002
|
[29] |
戴声佩, 易小平, 罗红霞, 等. 基于GEE和Landsat时间序列数据的海南岛土地利用分类研究[J]. 热带作物学报, 2021, 42(11): 3351-3357.
|
|
[Dai Shengpei, Yi Xiaoping, Luo Hongxia, et al. Mapping land use in Hainan Island based on Google Earth Engine and Landsat time series data[J]. Chinese Journal of Tropical Crops, 2021, 42(11): 3351-3357.]
|
[30] |
宁晓刚, 常文涛, 王浩, 等. 联合GEE与多源遥感数据的黑龙江流域沼泽湿地信息提取[J]. 遥感学报, 2022, 26(2): 386-396.
doi: 10.11834/jrs.20200033
|
|
[Ning Xiaogang, Chang Wentao, Wang Hao, et al. Extraction of marsh wetland in Heilongjiang Basin based on GEE and multi-source remote sensing data[J]. National Remote Sensing Bulletin, 2022, 26(2): 386-396.]
doi: 10.11834/jrs.20200033
|
[31] |
杨泽航, 王文, 鲍健雄. 融合多源遥感数据的黑河中游地区生长季早期作物识别[J]. 地球信息科学学报, 2022, 24(5): 996-1008.
doi: 10.12082/dqxxkx.2022.210527
|
|
[Yang Zehang, Wang Wen, Bao Jianxiong. Identifying crop types in early growing season in the middle reaches of Heihe River by fusing multi-source remote sensing data[J]. Journal of Geo-information Science, 2022, 24(5): 996-1008.]
doi: 10.12082/dqxxkx.2022.210527
|