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基于U -Net网络和GF-6影像 的尾矿库空间范围识别.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 252, doi. 10.6046/zrzyyg.2021017
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- Article
干旱区河谷绿洲土地利用冲突格局分析.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 243, doi. 10.6046/zrzyyg.2021044
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GIS在全民健身中的应用特征研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 265, doi. 10.6046/zrzyyg.2021003
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- Article
基于RS的陕北地区植被覆盖度变化及驱动力研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 258, doi. 10.6046/zrzyyg.2021019
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- Article
基于主控要素的生态地质脆弱性评价 --以四川省西昌市为例.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 181
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- Article
煤矿开采中SOM的遥感估算和时空动态分析.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 235, doi. 10.6046/zrzyyg.2020418
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- Article
遥感技术在中尼铁路工程地质勘察中的应用.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 219, doi. 10.6046/zrzyyg.2020403
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- Article
京杭大运河沿线地区城市化与 生态环境耦合协调关系研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 162, doi. 10.6046/zrzyyg.2020423
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- Article
基于面向对象的铁尾矿信息提取技术研究 --以迁西地区北京二号遥感影像为例
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 153
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- Article
渝东北2014年"8,3「暴雨诱发滑坡遥感解译与分析.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 192, doi. 10.6046/zrzyyg.2020348
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- Article
基于GEE的三峡蓄水对重庆地表水和植被影响研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 227, doi. 10.6046/zrzyyg.2020404
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- Article
基于CZMIL测深技术的海陆-体地形测量初探.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 173, doi. 10.6046/zrzyyg.2021007
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- Article
湘江流域TRMM卫星降水产品降尺度研究与应用.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 209, doi. 10.6046/zrzyyg.2020395
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- Article
A comparative study on the changes in heat island effect in Chinese and foreign megacities.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 200, doi. 10.6046/zrzyyg.2020393
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- Article
模型集群分析策略联合ELM的土壤 重金属Pb含量预测.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 143, doi. 10.6046/zrzyyg.2020378
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- Article
南海珊瑚礁白化遥感热应力检测改进方法研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 136, doi. 10.6046/zrzyyg.2020391
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- Article
基于U - Net深度学习方法火星沙丘提取研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 130, doi. 10.6046/zrzyyg.2020397
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- Article
卫星热红外温度反演钢铁企业炼钢月产量估算模型.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 121, doi. 10.6046/zrzyyg.2020399
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- Article
GPM卫星降水产品空间降尺度研究 --以贵州省为例.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 111, doi. 10.6046/zrzyyg.2021009
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- Article
基于GF -3全极化SAR数据的滨海湿地信息提取方法.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 105, doi. 10.6046/zrzyyg.2020353
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- Article
基于改进OGMRF - RC模型的SAR图像分类方法.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 98, doi. 10.6046/zrzyyg.2020427
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- Article
城区范围空间划定方法研究.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 89, doi. 10.6046/zrzyyg.2021015
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- Article
高分辨率TerraSAR - X时序差分 干涉沉降监测及精度验证.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 26, doi. 10.6046/zrzyyg.2020379
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- Article
耦合模糊C均值聚类和贝叶斯网络的遥感 影像后验概率空间变化向量分析.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 82, doi. 10.6046/zrzyyg.2021032
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- Article
基于多尺度分割的高分辨率遥感影像镶嵌线自动提取.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 64, doi. 10.6046/zrzyyg.2020386
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- Article
Sentinel - 1A京津冀平原区2016-2018年 地面沉降InSAR监测.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 55, doi. 10.6046/zrzyyg.2020341
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- Article
徐州矿区2016--2018年地面沉降监测与分析.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 43, doi. 10.6046/zrzyyg.2020137
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- Article
联合WT - RF的津保高铁沿线地面沉降预测.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 34, doi. 10.6046/zrzyyg.2020351
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- Article
结合空间约束的卷积神经网络 多模型多尺度船企场景识别.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 72, doi. 10.6046/zrzyyg.2021020
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- Article
基于时间序列遥感数据植被物候 信息提取软件发展现状.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 19, doi. 10.6046/zrzyyg.2020382
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- Article
光学与SAR遥感协同反演土壤水分研究进展.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 10, doi. 10.6046/zrzyyg.2020416
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- Article
紫外-可见光水质参数在线监测技术研究进展.
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- Remote Sensing for Natural Resources, 2021, v. 33, n. 4, p. 1, doi. 10.6046/zrzyyg.2020409
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- Article