Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2007, Vol. 19 Issue (3) : 98-101     DOI: 10.6046/gtzyyg.2007.03.23
GIS |
THE METHOD FOR TRANSFORMING ARCGIS
VECTOR DATA TO KML FILE BASED ON ARCENGINE
LIU Xiang-lei 1,   MA  Jing 2
1.College of the Global Infomation Science & Engineering,Shandong University of Science and Technology,Qingdao 266510, China; 2.Institute of Geo-engineering and Surveying,Chang’an  University, Xi’an 710054, China
Download: PDF(640 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

ESRI is a pioneering and leading technique in GIS domain, and Google Earth provides the global image database.  It is therefore of important practical significance to unify these techniques. This paper has dealt with the method for transforming the ArcGIS Vector Data to KML file, proposed the means for transformation, and completed the program realization.

Keywords Geothermal anomaly      Vegetation effect      Spectrum measurement      Infared temperature      Remote sensing image      Interpretation mark     
: 

 

 
  P 282.2  
  P 283.49

 
Issue Date: 21 July 2009
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Wang Feiyao
Chen Qianghua
Cite this article:   
Wang Feiyao,Chen Qianghua. THE METHOD FOR TRANSFORMING ARCGIS
VECTOR DATA TO KML FILE BASED ON ARCENGINE[J]. REMOTE SENSING FOR LAND & RESOURCES, 2007, 19(3): 98-101.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2007.03.23     OR     https://www.gtzyyg.com/EN/Y2007/V19/I3/98
[1] ZHANG Daming, ZHANG Xueyong, LI Lu, LIU Huayong. Remote sensing image segmentation based on Parzen window density estimation of super-pixels[J]. Remote Sensing for Natural Resources, 2022, 34(1): 53-60.
[2] XUE Bai, WANG Yizhe, LIU Shuhan, YUE Mingyu, WANG Yiying, ZHAO Shihu. Change detection of high-resolution remote sensing images based on Siamese network[J]. Remote Sensing for Natural Resources, 2022, 34(1): 61-66.
[3] SONG Renbo, ZHU Yuxin, GUO Renjie, ZHAO Pengfei, ZHAO Kexin, ZHU Jie, CHEN Ying. A method for 3D modeling of urban buildings based on multi-source data integration[J]. Remote Sensing for Natural Resources, 2022, 34(1): 93-105.
[4] LIU Zhizhong, SONG Yingxu, YE Runqing. An analysis of rainstorm-induced landslides in northeast Chongqing on August 31, 2014 based on interpretation of remote sensing images[J]. Remote Sensing for Natural Resources, 2021, 33(4): 192-199.
[5] ZHANG Chengye, XING Jianghe, LI Jun, SANG Xiao. Recognition of the spatial scopes of tailing ponds based on U-Net and GF-6 images[J]. Remote Sensing for Natural Resources, 2021, 33(4): 252-257.
[6] LI Yikun, YANG Yang, YANG Shuwen, WANG Zihao. A change vector analysis in posterior probability space combined with fuzzy C-means clustering and a Bayesian network[J]. Remote Sensing for Natural Resources, 2021, 33(4): 82-88.
[7] SANG Xiao, ZHANG Chengye, LI Jun, ZHU Shoujie, XING Jianghe, WANG Jinyang, WANG Xingjuan, LI Jiayao, YANG Ying. Application of intensity analysis theory in the land use change in Yijin Holo Banner under the background of coal mining[J]. Remote Sensing for Natural Resources, 2021, 33(3): 148-155.
[8] WANG Yiuzhu, HUANG Liang, CHEN Pengdi, LI Wenguo, YU Xiaona. Change detection of remote sensing images based on the fusion of co-saliency difference images[J]. Remote Sensing for Natural Resources, 2021, 33(3): 89-96.
[9] LIU Wanjun, GAO Jiankang, QU Haicheng, JIANG Wentao. Ship detection based on multi-scale feature enhancement of remote sensing images[J]. Remote Sensing for Natural Resources, 2021, 33(3): 97-106.
[10] LU Qi, QIN Jun, YAO Xuedong, WU Yanlan, ZHU Haochen. Buildings extraction of GF-2 remote sensing image based on multi-layer perception network[J]. Remote Sensing for Land & Resources, 2021, 33(2): 75-84.
[11] HU Suliyang, LI Hui, GU Yansheng, HUANG Xianyu, ZHANG Zhiqi, WANG Yingchun. An analysis of land use changes and driving forces of Dajiuhu wetland in Shennongjia based on high resolution remote sensing images: Constraints from the multi-source and long-term remote sensing information[J]. Remote Sensing for Land & Resources, 2021, 33(1): 221-230.
[12] LIU Zhao, ZHAO Tong, LIAO Feifan, LI Shuai, LI Haiyang. Research and comparative analysis on urban built-up area extraction methods from high-resolution remote sensing image based on semantic segmentation network[J]. Remote Sensing for Land & Resources, 2021, 33(1): 45-53.
[13] ZHENG Zhiteng, FAN Haisheng, WANG Jie, WU Yanlan, WANG Biao, HUANG Tengjie. An improved double-branch network method for intelligently extracting marine cage culture area[J]. Remote Sensing for Land & Resources, 2020, 32(4): 120-129.
[14] WANG Xiaobing. Denoising algorithm based on the fusion of lifting wavelet thresholding and multidirectional edge detection of remote sensing image of mining area[J]. Remote Sensing for Land & Resources, 2020, 32(4): 46-52.
[15] WEI Hongyu, ZHAO Yindi, DONG Jihong. Cooling tower detection based on the improved RetinaNet[J]. Remote Sensing for Land & Resources, 2020, 32(4): 68-73.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech