模糊坡位信息在精细土壤属性空间推测中的应用

doi:10.11821/yj2010090016

地理研究 ›› 2010, Vol. 29 ›› Issue (9): 1706-1714.doi: 10.11821/yj2010090016

模糊坡位信息在精细土壤属性空间推测中的应用

秦承志¹, 卢岩君², 邱维理², 朱阿兴¹, 张灵燕², 杨琳¹

1. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101;
2. 北京师范大学地理学与遥感科学学院,北京 100875

收稿日期:2009-07-27 修回日期:2009-12-01 出版日期:2010-09-20 发布日期:2010-09-20
作者简介:秦承志(1977-),山东蒙阴人,副研究员。主要从事数字地形分析研究。E-mail:qincz@lreis.ac.cn ;
卢岩君(1987-),福建泉州人,研究生。主要从事数字地形分析研究。
基金资助:
国家自然科学基金资助项目(40971235、40671111);中国科学院知识创新工程项目资助(KZCX2-YW-Q10-1-5);国家科技支撑计划(2007BAC15B01);中国科学院地理科学与资源研究所、资源与环境信息系统国家重点实验室自主创新资助

Application of fuzzy slope positions in predicting spatial distribution of soil property at finer scale

QIN Cheng-zhi¹, LU Yan-jun², QIU Wei-li², ZHU A-xing¹, ZHANG Ling-yan², YANG Lin¹

1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resources Research, CAS, Beijing 100101, China;
2. School of Geography, Beijing Normal University, Beijing 100875, China

Received:2009-07-27 Revised:2009-12-01 Online:2010-09-20 Published:2010-09-20

摘要/Abstract

摘要：

坡位的空间渐变特征影响着小流域及坡面尺度上的土壤、水文、地貌等现象和过程,因此对精细尺度下的地理建模(如土壤空间信息推理)有重要作用。虽然目前已有多种模糊坡位信息定量提取方法,但所得到的模糊坡位信息还缺乏实际应用。本文以精细尺度下的土壤属性空间分布推测为例,对此展开探索。应用模型假设:(1)在小流域内,地形因素主导着土壤属性空间分布的变化;(2)典型坡位上对应分布着典型的土壤属性值,土壤属性与坡位之间存在协同变化关系。据此建立以模糊坡位信息对各类典型坡位上土壤样点属性值的加权平均模型,推测土壤属性的空间分布。模型应用于黑龙江省嫩江流域一个地形平缓的小区(面积约60 km²),通过一个以坡位典型位置作为原型的模糊坡位定量方法提取5类坡位(山脊、坡肩、背坡、坡脚、沟谷)的空间渐变信息,对土壤表层有机质含量的空间分布进行推测。推测结果通过研究区70个土壤采样点进行评价,以推测结果与评价样点集之间的相关系数、平均绝对误差、均方根误差作为定量评价指标,与使用常用地形属性的多元线性回归模型推测结果进行对比。评价结果表明,仅使用极少建模点的加权平均模型的推测结果优于多元线性回归模型的推测结果。

关键词: 模糊坡位, 土壤属性空间分布, 推测模型, 土壤表层有机质

Abstract:

The spatial gradation of slope position has a great effect on the soil, hydrological, geomorphic phenomena and processes in small watershed or on slope. The fuzzy slope positions extracted with various methods can quantify the spatial gradation of slope positions and are considered as a kind of promising information to geographic modeling, such as digital soil mapping at finer scale. However, few studies have actually applied the fuzzy slope positions in geographic modeling. This paper attempts to examine the possibility of application of fuzzy slope positions in predicting spatial distribution of soil property at finer scale. In this case, two fundamental assumptions are made as follows: 1) terrain condition which can be comprehensively reflected by slope positions shows most important effect on spatial distribution of soil property in small catchment, and 2) soil property on typical slope position generally represents a typical value when soil property co-varies spatially with slope position. Based on these two assumptions, a weighted average model in which typical values of soil property on typical slope positions are weighted with fuzzy slope positions is developed to predict the spatial distribution of soil property (A-horizon soil organic matter in this study). The fuzzy information of a system of five slope positions (i.e., summit, shoulder slope, back slope, foot slope, and valley) was derived by a method based on typical locations of slope positions. The weighted average model was evaluated in a low-relief catchment (about 60 km²) of Nenjiang watershed in Heilongjiang Province, Northeast China. The multiple linear regression model based on topographic attributes was also applied to comparison of model performance. Three indices, i.e. correlation coefficient between predicted and observed values, mean absolute error (MAE) and root mean square error (RMSE) based on a validation set of 70 soil samples were calculated for quantitative assessment of the model performance. Results show that the weighted average method with very few modeling points can better predict the spatial distribution of A-horizon soil organic matter than the multiple linear regression model does.

Key words: fuzzy slope position, spatial distribution of soil property, predicting model, A-horizon soil organic matter

秦承志, 卢岩君, 邱维理, 朱阿兴, 张灵燕, 杨琳. 模糊坡位信息在精细土壤属性空间推测中的应用[J]. 地理研究, 2010, 29(9): 1706-1714.

QIN Cheng-zhi, LU Yan-jun, QIU Wei-li, ZHU A-xing, ZHANG Ling-yan, YANG Lin. Application of fuzzy slope positions in predicting spatial distribution of soil property at finer scale[J]. GEOGRAPHICAL RESEARCH, 2010, 29(9): 1706-1714.

参考文献

[1] Blaszczynski J S. Landform characterization with geographic information systems. Photogrammetric Engineering and Remote Sensing, 1997, 63(2): 183~191.

[2] MacMillan R A, Pettapiece W W, Nolan S C, et al. A generic procedure for automatically segmenting landforms into landform elements using DEMs, Heuristic rules and fuzzy logic. Fuzzy Sets and Systems, 2000, 113: 81~109.

[3] 周启鸣,刘学军.数字地形分析.北京:科学出版社,2006.

[4] Schmidt J, Hewitt A. Fuzzy land element classification from DTMs based on geometry and terrain position. Geoderma, 2004, 121: 243~256.

[5] 朱阿兴,等.精细数字土壤普查模型与方法.北京:科学出版社,2008.

[6] 秦承志,朱阿兴,施迅,等.坡位渐变信息的模糊推理.地理研究,2007,26(6):1165~1174.

[7] Burrough P A, van Gaans P F M, MacMillan R A. High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems, 2000, 113: 37~52.

[8] Qin C, Zhu A X, Shi X, et al. Quantification of spatial gradation of slope positions. Geomorphology, 2009, 110: 152~161.

[9] 刘学军,卢华兴,仁政,等.论DEM地形分析中的尺度问题.地理研究,2007,26(3):433~442.

[10] 杨琳,朱阿兴,秦承志,等.运用模糊隶属度进行土壤属性制图的研究——以黑龙江鹤山农场研究区为例.土壤学报,2009,46(1):9~15.

[11] Ventura S J, Irvin B J. Automated landform classification methods for soil-landscape studies. In:Wilson J P,Gallant J C. Terrain Analysis:Principles and Applications, New York:John Wiley & Sons, 2000. 267~294.

[12] Qin C Z, Zhu A X, Yang L, et al. Primary discussion on the relationship between distributions of fuzzy slope positions and soil types. In: 16^th International Conference on Geoinformatics & Joint Conference on GIS and Built Environment, Guangzhou, China, 6, 28~29, 2008.

[13] 杨琳,朱阿兴,李宝林,等.应用模糊c均值聚类获取土壤制图所需土壤——环境关系知识的方法研究.土壤学报,2007,44(5):791~798.

[14] 孙孝林,赵玉国,秦承志,等. DEM水平分辨率对多元线性土壤——景观模型及其制图应用的影响.土壤学报,2008,45(5):971~977.

[15] Pennock D J, Zebarth B J, de Jong E. Landform classification and soil distribution in hummocky terrain, Saskatchewan, Canada. Geoderma, 1987, 40: 297~315.

[16] Nizeyimana E, Bicki T. Soil and soil-landscape relationships in the north central of Rwanda, East-Central Africa. Soil Science, 1992, 153: 225~236.

[17] Hengl T, Rossiter D G. Supervised landform classification to enhance and replace photo-interpretation in semi-detailed soil survey. Soil Science Society of America Journal, 2003, 67(6): 1810~1822.

[18] 秦承志,朱阿兴,李宝林,等.坡位的分类及其空间分布信息的定量化.武汉大学学报(信息科学版),2009,34(3):374~377.

[19] Deng Y. New trends in digital terrain analysis: Landform definition, representation, and classification. Progress in Physical Geography, 2007, 31(4): 405~419.

[20] Conacher A J, Dalrymple J B. The nine unit landsurface model: An approach to pedogeomorphic research. Geoderma, 1977, 18(1/2): 1~154.

[21] Speight J G. Landform. In:McDonald R C,Isbell R F, Speight J G, et al. Australian Soil and Land Survey Field Handbook (2nd edn.) .Melbourne: Inkata Press, 1990. 9~57.

[22] Dymond J R, de Rose R C, Harmsworth G R. Automated mapping of land components from digital elevation data. Earth Surface Processes and Landforms, 1995, 20(2): 131~137.

[23] Zhu A X, Band L, Vertessy R, et al. Derivation of soil properties using a Soil Land Inference Model (SoLIM). Soil Science Society of America Journal, 1997, 61: 523~533.

[24] Bishop T F A, McBratney A B. A comparison of prediction methods for the creation of field-extent soil property maps. Geoderma, 2001, 103: 149~160.

[25] McBratney A B, Mendonca Santos M L, Minasny B. On digital soil mapping. Geoderma, 2003, 117: 3~52.

[26] Skidmore A K. Terrain positions mapped from a gridded digital elevation model. International Journal of Geographical Information Systems, 1990, 4(1): 33~49.

[27] 秦承志,卢岩君,包黎莉,等. 简化数字地形分析软件(SimDTA)及其应用——以嫩江流域鹤山农场区的坡位模糊分类为例.地球信息科学学报,2009,11(6):737~743.

[28] 林成谷,主编.土壤学(北方本).北京:农业出版社,1983.

[29] Gessler P E, Moore I D, McKenzie N J, et al. Soil-landscape modelling and spatial prediction of soil attributes. International Journal of Geographical Information System, 1995, 9: 421~432

[30] Shary P A, Sharaya L S, Mitusov A V. Fundamental quantitative methods of land surface analysis. Geoderma, 2002, 107: 1~32.

[31] 秦承志,杨琳,朱阿兴,等.平缓地区地形湿度指数的计算方法.地理科学进展,2006,25(6):87~93.

模糊坡位信息在精细土壤属性空间推测中的应用

Application of fuzzy slope positions in predicting spatial distribution of soil property at finer scale

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

Metrics

本文评价

推荐阅读 0