Remote Sensing Scale Transformation of Soil Moisture Based on Block Kriging

  • 1. College of Informatics, South China Agricultural University, Guangzhou 510642, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Guangzhou Institute of Geochemistry, CAS, Guangzhou 510642, China

Received date: 2012-06-14

  Revised date: 2012-07-10

  Online published: 2012-08-22

Supported by



The reasonable remote sensing sale transformation method is very important for RS data utilization. In order to find a suitable scaling model for ascending scale and downscaling transformation with spectral data, given the randomness and structural of soil moisture data as regional variation, point Kriging method accounting for spatial heterogeneity is used in this study to transfer from ASTER soil moisture data with 15m resolution to 7.5m resolution. The similarity degree of fractal dimension is shown that the transformation result is reasonable. Block Kriging method is engaged in the upscaling transformation for the field measured point soil content to 7.5m spatial resolution. The 7.5m resolution upscaling scale conversion results and average of measured sample point soil moisture with downscaling 7.5 m resolution remote sensing data were compared respectively. The result shows that 7.5m resolution soil moisture mean error of the measured sample points is in the range of 1.5782 to 5.019, the error between 7.5m resolution upscaling scale conversion results and downscaling 7.5 m resolution remote sensing data is from 1.2825 to 5.0481, which indicates that soil moisture value acquired by Kriging is much better than the soil moisture average without considering spatial heterogeneity under the same scale because of Kriging method taking account of the relationship between the points and the surrounding.

Cite this article

WANG Lu, HU Yueming, ZHAO Yingshi, Liu Zhenhua* . Remote Sensing Scale Transformation of Soil Moisture Based on Block Kriging[J]. Journal of Geo-information Science, 2012 , 14(4) : 465 -473 . DOI: 10.3724/SP.J.1047.2012.00465


[1] 杨胜天,刘昌明. 黄河流域土壤水分遥感计算及水循环过程分析[J].中国科学E辑:技术科学,2004,34(增刊I):1-12.

[2] 彭晓鹃,邓孺孺,刘小平. 遥感尺度转换研究进展[J].地理与地理信息科学,2004,20(5):6-10.

[3] Marceau D J. The scale issue in social and natural sciences[J]. Canadian Journal of Remote Sensing, 1999,25(4):347-356.

[4] 刘明亮,唐先明,刘纪远,等. 基于1km格网的空间数据尺度效应研究[J].遥感学报,2001,5(3):183-190.

[5] Bloschl G, Sivapalan M. Scale issues in hydrological modelling: a review[J]. Hydrological Processes, 1995,9(3-4):251-290.

[6] Lam N S N, Quattrochi D A. On the Issues of Scale, Resolution, and Fractal Analysis in the Mapping Sciences[J]. The Professional Geographer, 1992,44(1):88-98.

[7] Goodchild M F, Quattrochi D A. Scale, multiscaling, remote sensing, and GIS. Boca Rotan:Lewis Publishers, 1997.

[8] 吴骅,姜小光,习晓环,等. 两种普适性尺度转换方法比较与分析研究[J].遥感学报, 2009,13(2):183-189.

[9] Burnett C, Blaschke T. A multi-scale segmentation/object relationship modelling methodology for landscape analysis[J]. Ecological Modelling, 2003, 168(3): 233-249.

[10] Li C T, Chiao R. Unsupervised texture segmentation using multiresolution hybrid genetic algorithm. Proceedings of 2003 International Conference on Image Processing,2003.

[11] Fernandes R A, Miller J R, Chen J M, et al. Evaluating image-based estimates of leaf area index in boreal conifer stands over a range of scales using high-resolution CASI imagery[J]. Remote Sensing of Environment,2004,89(2):200-216.

[12] 王晅,肖斌,马建峰. 基于Radon和解析Fourier-Mellin变换的尺度与旋转不变目标识别算法[J]. 中国图象图形学报,2008,13(11): 2157-2162.

[13] Hay G J, Niernann K O, Goodenough D G. Spatial thresholds, image-objects, and upscaling: a multiscale evaluation[J]. Remote Sensing of Environment,1997, 62(1):1-19.

[14] 胡国彪,傅扬镳,胡小保. 基于变异函数套合的遥感图像尺度效应研究[J].科技风,2011(4):34-35.

[15] 冉有华,李新. 基于块克里金的土壤水分点观测向像元尺度的尺度上推研究[J].冰川冻土,2009,31(2):275-283.

[16] Liu Z, Zhao Y. Research on the method for retrieving soil moisture using thermal inertia model[J]. Science in China Series D: Earth Sciences, 2006,49(5):539-545.

[17] Journel A G, Huijbregts C J. Mining geostatistics[M]. Waltham, MA, USA: Academic Press, 1978.

[18] Matheron G. Principles of geostatistics[J]. Economic Geology, 1963,58(8):1246-1266.

[19] Krummel J R, Gardner R H, Sugihara G, et al. Landscape patterns in a disturbed environment[J]. Oikos, 1987,48(3):321-324.