机构

• 地理科学与资源研究所 [6]
• 遥感与数字地球研究所 [1]
• 沈阳自动化研究所 [1]

采集方式

• OAI收割 [8]

内容类型

• 期刊论文 [5]
• SCI/SSCI论文 [2]
• 会议论文 [1]

发表日期

• 2022 [2]
• 2021 [2]
• 2016 [1]
• 2013 [1]
• 2012 [1]
• 2009 [1]
• 更多

学科主题

• Physical G... [1]

筛选

浏览/检索结果: 共8条，第1-8条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Influence of legacy soil map accuracy on soil map updating with data mining methods 期刊论文  OAI收割 GEODERMA, 2022, 卷号: 416, 页码: 12 作者:  Liu, Xueqi;  Zhu, A-Xing;  Yang, Lin;  Pei, Tao;  Qi, Feng   |  收藏  |  浏览/下载：37/0  |  提交时间：2022/09/21 Digital soil mapping  Machine learning  Map accuracy  Updating conventional soil map  SoLIM  Soil-landscape model   Influence of legacy soil map accuracy on soil map updating with data mining methods 期刊论文  OAI收割 GEODERMA, 2022, 卷号: 416, 页码: 12 作者:  Liu, Xueqi;  Zhu, A-Xing;  Yang, Lin;  Pei, Tao;  Qi, Feng   |  收藏  |  浏览/下载：29/0  |  提交时间：2022/09/21 Digital soil mapping  Machine learning  Map accuracy  Updating conventional soil map  SoLIM  Soil-landscape model   Improving the accuracy of extant gridded population maps using multisource map fusion 期刊论文  OAI收割 GISCIENCE & REMOTE SENSING, 2021, 页码: 18 作者:  Gao, Peng;  Wu, Tianjun;  Ge, Yong;  Li, Zihan   |  收藏  |  浏览/下载：41/0  |  提交时间：2022/09/21 Gridded population maps  multisource map fusion  uncertainty  accuracy  China   Improving the accuracy of extant gridded population maps using multisource map fusion 期刊论文  OAI收割 GISCIENCE & REMOTE SENSING, 2021, 页码: 18 作者:  Gao, Peng;  Wu, Tianjun;  Ge, Yong;  Li, Zihan   |  收藏  |  浏览/下载：51/0  |  提交时间：2022/09/21 Gridded population maps  multisource map fusion  uncertainty  accuracy  China   Modelling building proximity to greenery in a three-dimensional perspective using multi-source remotely sensed data 期刊论文  OAI收割 JOURNAL OF SPATIAL SCIENCE, 2016, 卷号: 61, 期号: 2, 页码: 389-403 作者:  Li, Xiaojiang;  Li, Weidong;  Meng, Qingyan;  Zhang, Chuanrong;  Jancso, Tamas 收藏  |  浏览/下载：18/0  |  提交时间：2017/04/24 DATA SET  ACCURACY  RESOLUTION  DESIGN  REGION  MAP   A line mapping based automatic registration algorithm of infrared and visible images 会议论文  OAI收割 5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013 作者:  Ai R(艾锐);  Shi ZL(史泽林);  Xu DJ(徐德江);  Zhang CS(张程硕) 收藏  |  浏览/下载：38/0  |  提交时间：2013/12/26 There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.   Assessing the quality of training data in the supervised classification of remotely sensed imagery: a correlation analysis SCI/SSCI论文  OAI收割 2012 作者:  Ge Y. 收藏  |  浏览/下载：34/0  |  提交时间：2014/12/25 quality assessment of training data  rough set  measures  correlation  analysis  accuracy assessment  land-cover  scale  map   Surface modelling of soil pH SCI/SSCI论文  OAI收割 2009 Shi W. J.; Liu J. Y.; Du Z. P.; Song Y. J.; Chen C. F.; Yue T. X. 收藏  |  浏览/下载：23/0  |  提交时间：2012/06/08 HASM  Interpolation accuracy  Soil properties  Validation  spatial prediction methods  interpolation methods  fertility management  map quality  regression  salinity  geostatistics  performance  attributes