EN中文

PROGRESS IN GEOGRAPHY >

2010 , Vol. 29 >Issue 2: 179 - 185

DOI: https://doi.org/10.11820/dlkxjz.2010.02.008

Original Articles

Robust Estimation for the Determinant Model of Land use Pattern Based on the Area Percentage Dataset of Land Uses

Expand
  • 1. Institute of Geographic Sciences and National Resources Research, CAS, Beijing 100101, China;
    2. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China

Online published: 2010-02-25

Fold

Abstract

Given that the ordinary least square estimate is not adaptable to analyzing the driving mechanism of land use pattern represented by the area percentage data, this paper develops an estimation approach according to the partial least squares regression algorithm capable of analyzing the driving mechanism of land use pattern identified at the pixel specific resolution. The approach can be used to obtain the robust estimates for the determinant model of land use pattern and guarantee that the sum of predicted area of all kinds of land use categories equals the total land area of each grid pixel in addition to deducting the estimation bias resulting from the multi-collinearities between explanatory variables. This paper elaborately deduces the estimation algorithm for the explanatory model for the land use pattern according to the partial least-squares regression algorithm and based on the area percentage data. By using this kind of estimation approach, this paper analyzes the driving mechanism of land use pattern for cultivated land, built-up area and other kinds of land and obtains the estimates with high goodness of fit in Huang-Huai-Hai Plain of China. The research result shows that the partial least squares regression analysis can be used to estimate the driving mechanism of land use pattern represented by the area percentage data. The estimation approach proven applicable in this study is with unbiased, efficient and robust characteristics and worthy of being promoted to use in relevant case studies.

Key words： area percentage data; Huang-Huai-Hai Plain; land use pattern; driving mechanism; partial least squares regression analysis

Cite this article

DENG Xiangzheng1, LIN Yingzhi1, ZHAN Jinyan2, HE Shujin1 . Robust Estimation for the Determinant Model of Land use Pattern Based on the Area Percentage Dataset of Land Uses[J]. PROGRESS IN GEOGRAPHY, 2010 , 29(2) : 179 -185 . DOI: 10.11820/dlkxjz.2010.02.008

References


[1]   刘纪远, 庄大方, 张增祥, 等. 中国土地利用时空数据平台建设及其支持下的相关研究. 地球信息科学, 2002, (3): 3-7.

[2]   陈述彭, 周成虎, 陈秋晓. 网格地图的新一代. 测绘科学, 2004, 29(4): 1-4.

[3]   邓祥征. 土地系统动态模拟. 北京: 大地出版社, 2008.

[4]   李秀彬. 全球环境变化研究的核心领域: 土地利用/土地覆盖变化的国际研究动向. 地理学报, 1996, 51(6): 553-557.

[5]   陈百明. 试论中国土地利用和土地覆被变化及其人类驱动力研究. 自然资源, 1997, 19(2): 31-36.

[6]   蔡运龙. 土地利用土地覆被变化研究: 寻求新的综合途径. 地理研究, 2001, 20(6): 645-652.

[7]   鲁奇, 战金艳, 任国柱. 北京近百年城市用地变化与相关社会人文因素简论. 地理研究, 2001, 20(6): 688~696.

[8]   邓祥征. 土地用途转换分析. 北京: 大地出版社, 2008.

[9]   Ferrers N M. An elementary treatise on trilinear coordinates. London: Macmillan, 1866.

[10] Bacon-Shone J.Modelling structural zeros in compositional data // Thió-Henestrosa S, Martín-Fernández J A. Proceedings of CODAWORK’03, the First Compositional Data Analysis Workshop. Spain: University of Girona， 2003, 15-17.

[11] Aitchison J. The statistical analysis of compositional data. London: Chapman and Hall, 1986.

[12] 张尧庭. 成分数据统计分析引论. 北京: 科学出版社, 2000.

[13] Frisch R. Statistical Confluence Analysis by Means of Complete Regression Systems, Economic Institute, Pub. No. 5, Oslo University, 1934.

[14] Wold S, Albano C, Dunn W J III, et al. Pattern recognition: finding and using patterns in multivariate data. In: Martens H and Russwurm H Jr (Eds.), Food Research and Data Analysis. London: Applied Science Pub. 1983, 147-188.

[15] 高惠璇. 应用多元统计分析. 北京大学出版社, 2005.

[16] Anselin L, Florax R, Rey S. Advances in spatial econometrics: Methodology, tools and applications. Berlin: Springer Verlag， 2004.

Options
Outlines

/

〈 〉