Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2010, Vol. 22 Issue (3) : 101-107     DOI: 10.6046/gtzyyg.2010.03.21
Technology Application |
Spatial-Temporal Change Characteristics and Cluster Analysis of Rural Settlements in Shandong Province
LIU Fang 1, ZHANG Zeng-xiang 1, ZHAO Xiao-li 1, HU Shun-guang 1,2
1.Institute of Remote Sensing Application, Chinese Academy of Sciences, Beijing 100101, China; 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
Download: PDF(925 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

With remote sensing and GIS technology, the spatial-temporal characteristics of rural settlements of Shandong Province during the period of 1980s-2005 were analyzed from the aspects of structure, morphology, spatial scattering and change intensity. Five indices were chosen,  which indicated the change value of the area proportion, bi-directional change value, relative change rate, the change of aggregation value and the stability change of rural settlements of every city in Shandong Province respectively. Based on these indices, 17 cities in Shandong Province were classified into 3 classes quantitatively and objectively by using the hierarchical cluster method. The first class includes Dezhou City and Binzhou City, which have the maximum stability change value, the highest relative change rate, the fast dynamic change speed, the biggest aggregation change value and the smallest structure change value. The second class includes Zaozhuang City, Tai’an City and Heze City, which have the minimum stability change value, the lowest relative change rate, the slowest dynamic change speed and the biggest structure change value, and the middle-level morphological and aggregation change value. The other 12 cities belong to the third class, characterized by the middle-level rural resident land structure change value, stability change, relative change rate and dynamic change speed, and the minimum aggregation change value.

Keywords TM image      Ecological greenbelt      Guangzhou city     
: 

 

 
  TP 79

 
Issue Date: 20 September 2010
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Cite this article:   
LIU Fang, ZHANG Zeng-Xiang, ZHAO Xiao-Li, HU Shun-Guang. Spatial-Temporal Change Characteristics and Cluster Analysis of Rural Settlements in Shandong Province[J]. REMOTE SENSING FOR LAND & RESOURCES,2010, 22(3): 101-107.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2010.03.21     OR     https://www.gtzyyg.com/EN/Y2010/V22/I3/101

[1]陈思明,吴景.基于GIS的农村居民点用地动态变化分析[J].国土资源科技管理, 2008, 25(4):17-21.

[2]刘英.基于GIS的农村居民点用地时空特征及其优化布局研究——以湖南临澧县为例[J].国土与自然资源研究, 2008(4):35-36.

[3]田光进.基于GIS的中国农村居民点用地分析[J].应用技术, 2003(2):32-35.

[4]牟凤云,张增祥,刘斌,等.济南市二十五年城市建成区的空间扩展遥感监测[J]. 山东农业大学学报(自然科学版),2008,39(1):73-79.

[5]刘纪远.中国资源环境遥感宏观调查玉动态研究[M].北京:中国科学设计出版社,1996.

[6]田光进, 刘纪远, 张增祥. 基于遥感与GIS的中国农村居民点规模分布特征 [J]. 遥感学报, 2002, 6(4):307 - 312.

[7]韦素琼, 陈建飞. 土地利用变化趋于对比研究——以闽台为例[M].北京:科学出版社, 2006.

[8]陈彦光,罗静. 城市形态的分维变化特征及其对城市规划的启示[J]. 城市发展研究,
2006,13(5):35-40.

[9]杨山. 发达地区城乡聚落形态的信息提取与分型研究——以无锡市为例[J]. 地理学报, 2000, 55 (5):671-678.

[10]陈红宇, 胡曰利, 胡晓芙, 等. 城市化进程中的农村居民点用地变化分析——以广州市为例[J]. 中国农学通报, 2005, 21(2):300-303.

[11]Falconer K J. Fractal Geometry, Mathematical Foundations and Applications [M].Wiley John & Sons,Incorporated,1990.

[12]刘纯平, 陈宁强, 夏德深. 土地利用类型的分数维分析[J]. 遥感学报, 2003, 7 (2):136-140.

[13]徐建华. 现代地理学中的数学方法[M]. 北京:高等教育出版社, 2006.

[14]宝音, 包玉海.北方农牧林交错带土地利用区的分析与评价——以科尔沁右翼前旗为例[J].地理科学,1996, 16 (4):377-380.

[15]何晓群. 现代统计分析方法与应用[M]. 北京:中国人民大学出版社, 2003.

[16]潘竞虎, 刘普幸. 黑河下游土地利用与景观格局时空特征分析[J]. 国土资源遥感, 2008(2):84-86.

[17]李治, 李国平. 中国城市空间扩展影响因素的实证研究[J]. 同济大学学报(社会科学版),2008,19 (6):30-35.

[18]史文利, 高天宝,王树恩. 基于主成分分析与聚类分析的城市化水平综合评价[J].工业工程, 2008, 11 (3):112-115.

[19]廖邦固, 徐建刚, 宣国富, 等. 1947-2000年上海中心城区居住空间结构演变[J]. 地理学报, 2008, 63 (2):195-205.

[1] TIAN Lei, FU Wenxue, SUN Yanwu, JING Linhai, QIU Yubao, LI Xinwu. Research on spatial change of the boreal forest cover in Siberia over the past 30 years based on TM images[J]. Remote Sensing for Land & Resources, 2021, 33(1): 214-220.
[2] GUO Qiaozhen, NING Xiaoping, WANG Zhiheng, JIANG Weiguo. Impact analysis of landform for land use dynamic change of the partly mountainous area: A case study of Jixian County in Tianjin City[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(1): 153-159.
[3] XU Xu, REN Feipeng, HAN Nianlong. Remote sensing monitoring of spatio-temporal changes of ecosystem service values in Hebei Province, 2000—2009[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(1): 187-193.
[4] LIU Juan, CAI Yanjun, WANG Jin. Soil classification of Qinghai Lake basin based on remote sensing[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(1): 57-62.
[5] XU Chao, ZHAN Jinrui, PAN Yaozhong, ZHU Wenquan. Extraction of cropland information based on multi-temporal TM images[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 166-173.
[6] QIN Yan, DENG Ru-ru, HE Ying-qing, CHEN Lei, CHEN Qi-dong, XIONG Shou-ping. Algorithm for Removing Thick Clouds in TM Image Based on Spectral and Geometric Information[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(4): 55-61.
[7] SHEN Jin-xiang, YANG Liao, CHEN Xi, LI Jun-li, PENG Qing-qing, HU Ju. A Method for Object-oriented Automatic Extraction of Lakes in the Mountain Area from Remote Sensing Image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(3): 84-91.
[8] CHEN Lei, DENG Ru-ru, CHEN Qi-dong, HE Ying-qing, QIN Yan, LOU Quan-sheng. The Extraction of Water Body Information from TM Imagery Based on Water Quality Types[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(1): 90-94.
[9] ZHANG Zhi-xin, DENG Ru-ru, LI Hao, CHEN Lei, CHEN Qi-dong, HE Ying-qing. Remote Sensing Monitoring of Vegetation Coverage in Southern China Based on Pixel Unmixing: A Case Study of Guangzhou City[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(3): 88-94.
[10] LIU Yan, DING Tao- , RUAN Hui-Hua, LIN Na. The Monitoring of Land Desertification in the Manasi River Basin Based
on Multi-source Remotely Sensed Data
[J]. REMOTE SENSING FOR LAND & RESOURCES, 2010, 22(1): 81-84.
[11] ZHENG Rong-Bao, ZHUANG Jian-Shun, ZHANG Jin-Qian. THE RELATIONSHIP BETWEEN NDVI CHANGE ANDLAND USE IN GUANGZHOU CITY[J]. REMOTE SENSING FOR LAND & RESOURCES, 2008, 20(2): 102-108.
[12] SUN Yong-Jun, TONG Qing-Xi, QIN Qi-Ming. THE OBJECT-ORIENTED METHOD FOR WETLAND INFORMATION EXTRACTION[J]. REMOTE SENSING FOR LAND & RESOURCES, 2008, 20(1): 79-82.
[13] ZHANG Li-Su, WU Jia-Ping. REGIONAL LAND USE/COVER CLASSIFICATION WITH
A STRATIFIED AND REGIONALIZED APPROACH:
A CASE STUDY IN QIANTANG RIVER WATERSHED, ZHEJIANG PROVINCE
[J]. REMOTE SENSING FOR LAND & RESOURCES, 2007, 19(3): 74-77.
[14] QI Zhi-Xin, DENG Ru-Ru. THE ATMOSPHERIC CORRECTION METHOD FOR NONHOMOGENEOUS
ATMOSPHERE BASED ON MANY DARK OBJECTS
[J]. REMOTE SENSING FOR LAND & RESOURCES, 2007, 19(2): 16-19.
[15] GAO Zhong-Ling, WANG Xiao-Qin, ZHOU Xiao-Cheng. THE EXTRACTING OF FIRE SCARS FROM TM IMAGE[J]. REMOTE SENSING FOR LAND & RESOURCES, 2005, 17(4): 38-41.
Viewed
Full text


Abstract

Cited

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