农田景观空间异质性分析及遥感监测最优尺度选择——以三江平原为例

doi:10.11821/xb201203006

Abstract

Abstract: Agricultural monitoring requires high temporal frequency data which are currently provided only by moderate spatial resolution sensors. At such moderate spatial resolutions, farmland that is heterogeneous within a pixel will be averaged and hence obscured. This would bias any non-linear estimation of crop growing processes (e.g., net primary productivity (NPP), leaf area index (LAI)). To modify this bias, a first approach is used to explicitly take into account the intra-pixel spatial heterogeneity in the retrieval algorithm. A second approach is to use the surface heterogeneity to disaggregate moderate spatial resolution estimates of land surface variable at a proper scale of spatial variation. Both approaches are required to quantify spatial heterogeneity,and a proper scale selection should be necessary for agricultural monitoring.To this ends, four typical landscape pattern sites in the Jiansanjiang Reclamation Area which is an important basin of commercial grain production in China, were selected and Landsat/TM NDVI image data were analyzed in this study. Based on the variogram analysis, some conclusions can be drawn. (1) Directional experiment variograms analysis can make clear how the human activates and natural factors affect the agricultural spatial heterogeneity qualitatively. For example, dry lands (including the landscape only with dry land and the landscape which is mosaic of dry land and paddy fields in this study) have the largest heterogeneity in North-South direction, while the landscape pattern which only have paddy fields have the largest heterogeneity in East-West direction. Based on this, we can demonstrate that spatial heterogeneity caused by human and natural factors can be examined deeply through variogram analysis. (2) The fitted variograms can present how different landscape patterns have their own spatial heterogeneity quantificationally. In this study, for example, the same type of land use can have lower heterogeneity as different types of land use landscape patterns have larger heterogeneity. (3) Through the variogram analysis of heterogeneity, a method used to select a proper scale (pixel size) for agricultural remote sensing monitoring is discussed.

Key words: Jiansanjiang Reclamation Area, variogram, spatial heterogeneity, scale selection, remote sensing

WEN Zhaofei, ZHANG Shuqing, BAI Jing, DING Changhong, ZHANG Ce. Agricultural Landscape Spatial Heterogeneity Analysis and Optimal Scale Selection: An Example Applied to Sanjiang Plain[J].Acta Geographica Sinica, 2012, 67(3): 346-356.

References

[1] Meng Jihua, Wu Bingfang, Li Qiangzi et al. Research advances and outlook of crop monitor ing with remote sensing at field level. Remote Sensing Information, 2010, (3): 122-128. [蒙继华, 吴炳方, 李强子等. 农田农情参数遥感监测进展及应用展望. 遥感信息, 2010, (3): 122-128.]
[2] Friedl M A. Examining the Effects of Sensor Resolution and Sub-pixel Heterogeneity on Spetral Vegetation Indices: Implications for Biophysical Modeling. Boca Raton: Lewis Publishers, 1997.
[3] Weiss M, Baret F, Myneni R B et al. Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data. Agronomie, 2000, 20(1): 3-22.
[4] Garrigues S, Allard D, Baret F et al. Quantifying spatial heterogeneity at the landscape scale using variogram models. Remote Sensing of Environment, 2006, 103(1): 81-96.
[5] Garrigues S, Allard D, Baret F et al. Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data. Remote Sensing of Environment, 2006, 105(4): 286-298.
[6] Ming Dongping, Wang Qun, Yang Jianyu. Spatial scale of remote sensing image and selection of optimal spatial resolution. Journal of Remote Sensing, 2008, 12(4): 529-537. [明冬萍, 王群, 杨建宇. 遥感影像空间尺度特性与最佳空间分辨率选择. 遥感学报, 2008, 12(4): 529-537.]
[7] Merlin O, Chehbouni A, Kerr Y H et al. A downscaling method for distributing surface soil moisture within a microwave pixel: Application to the Monsoon '90 data. Remote Sensing of Environment, 2006, 101(3): 379-389.
[8] Csillag F, Kabos S. Wavelets, boundaries, and the spatial analysis of landscape pattern. Ecoscience, 2002, 9(2): 177-190.
[9] Lyons T J, Halldin S. Surface heterogeneity and the spatial variation of fluxes. Agricultural and Forest Meteorology, 2004, 121(3/4): 153-165.
[10] Kolasa J, Rollo C. Ecological Heterogeneity. New York: Springer-Verlag, 1991.
[11] Li Habin, Wang Zhengquan, Wang Qingcheng. Theory and methodology of spatial heterogeneity quantification. Chinese Journal of Applied Ecology, 1998, 9(6): 651-657. [李哈滨, 王政权, 王庆成. 空间异质性定量研究理论与方法. 应用生态学报, 1998, 9(6): 651-657.]
[12] Garrigues S, Allard D, Baret F et al. Multivariate quantification of landscape spatial heterogeneity using variogram models. Remote Sensing of Environment, 2008, 112(1): 216-230.
[13] Wan Li. Variogram-based quantitative analysis of the spatial heterogeneity. Statistics and Decision, 2006, (2): 26-27. [万丽. 基于变异函数的空间异质性定量分析. 统计与决策, 2006, (2): 26-27.]
[14] Curran P J. The semivariogram in remote sensing: An introduction. Remote Sensing of Environment, 1988, 24: 493-507.
[15] Woodcock C E, Strahler A H, Jupp D L B. The use of variograms in remote sensing: II. Real digital images. Remote Sensing of Environment, 1988, 25(3): 349-379.
[16] Oliver M A, Shine J A, Slocum K R. Using the variogram to explore imagery of two different spatial resolutions. International Journal of Remote Sensing, 2005, 26(15): 3225-3240.
[17] Woodcock C E, Strahler A H. The factor of scale in remote sensing. Remote Sensing of Environment, 1987, 21(3): 311-332.
[18] Atkinson P M, Aplin P. Spatial variation in land cover and choice of spatial resolution for remote sensing. International Journal of Remote Sensing, 2004, 25(18): 3687-3702.
[19] Atkinson P M, Curran P J. Defining an optimal size of support for remote sensing investigations. IEEE Transactions on Geoscience and Remote Sensing, 1995, 33(3): 768-776.
[20] Bai Yanche, Wang Jinfeng. Exploring the scale effect in thematic classification of remotely sensed data:the statistical separability-based method. Remote Sensign Technology and Application, 2004, 19(6): 443-449. [柏延臣, 王劲峰. 基于统计可分性的遥感数据专题分类尺度效应分析. 遥感技术与应用, 2004, 19(6): 443-449.]
[21] Statistical Yearbook of Farm Jiansanjiang. Heilongjiang Province Sanjiang Farm Statistical Yearbook Editorial Department, 2002. [建三江农垦统计年鉴. 黑龙江省建三江农垦统计年鉴编辑部, 2002.]
[22] Records of Jiansanjiang Farm. Jiansanjiang Branc, 2004. [建三江农垦志. 建三江分局, 2004.]
[23] Zhang Xixiang, Wu Jianping. Sanjiang Nature Reserve, Natural Resources Research. Harbin: Northeast Forestry University Press, 2003. [张喜祥, 吴建平. 三江自然保护区自然资源研究. 哈尔滨: 东北林业大学出版社, 2003.]
[24] Solutions I V I. Atmospheric Correction Module: QUAC and FLAASH User's Guide, 2009.
[25] Deng Shubin. ENVI Remote Sensing Image Processing. Beijing: Science Press, 2010. [邓书斌. ENVI遥感图像处理方法. 北京: 科学出版社, 2010.]
[26] Zhang Renduo. Spatial Variation of the Theory and Application. Beijing: Science Press, 2005. [张仁铎. 空间变异理论及应用. 北京: 科学出版社, 2005.]
[27] Tarnavsky E, Garrigues S, Brown M E. Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products. Remote Sensing of Environment, 2008, 112(2): 535-549.
[28] Curran P J, Atkinson P M. Geostatistics and remote sensing. Progress in Physical Geography, 1998, 22(1): 61-78.
[29] Woodcock C E, Strahler A H, Jupp D L B. The use of variograms in remote sensing: I. Scene models and simulated images. Remote Sensing of Environment, 1988, 25(3): 323-348.
[30] Li Xiaowen, Cao Chunxiang, Chang Chaoyi. The first law of geography and spatial-temporal proximity. Chinese Jounal of Nature, 2006, 29(2): 69-71. [李小文, 曹春香, 常超一. 地理学第一定律与时空邻近度的提出. 自然杂志, 2006, 29(2): 69-71.]
[31] Chilès J, Delfiner P. Geostatistics: Modeling Spatial Uncertainty. New York: John Wiley and Sons, 1999.
[32] Webster R. Quantitative spatial analysis of soil in the field. Advances in Soil Science, 1985, 3(1): 1-70.
[33] Johnston K, Hoef J M V, Krivoruchko K et al. Using ArcGIS Geostatistical Analyst. ESRI Press, 2001.
[34] Matheron G. Principles of geostatistics. Economic Geology, 1963, 58: 1246-1266.
[35] Wang Zhengquan. Geostatistics and Its Application in Ecology. Beijing: Science Press, 1999. [王政权. 地统计学及其在生态学中的应用. 北京: 科学出版社, 1999.]
[36] Pannatier Y. VARIOWIN: Software for Spatial Data Analysis in 2D. New York: Springer-Verlag, 1996.
[37] Lantuéjoul C. Geostatistical Simulation: Models and Algorithms. Berlin: Springer-Verlag, 2002.
[38] Schowengerdt R A. Remote Sensing: Models and Methods for Image Processing. San Diego: Academic Press, 2007.
[39] Fu Qiang. Different ridge cultivation on soybean yield to the impact of research. Heilongjiang Agricultural Sciences, 2011, (4): 29-31. [符强. 不同垄向栽培对大豆产量影响的研究. 黑龙江农业科学, 2011, (4): 29-31.]
[40] Shannon C. Communication in the presence of noise. Proc. Institute of Radio Engineers, 1949, 37(1): 10-21.

Agricultural Landscape Spatial Heterogeneity Analysis and Optimal Scale Selection: An Example Applied to Sanjiang Plain

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

[1]	XU Chenchen, YE Huping, YUE Huanyin, TAN Xiang, LIAO Xiaohan. Iterative construction of UAV low-altitude air route network in an urbanized region: Theoretical system and technical roadmap [J]. Acta Geographica Sinica, 2020, 75(5): 917-930.
[2]	YAO Yonghui, ZHANG Junyao, SUONAN Dongzhu. Compilation of 1∶50000 vegetation type map with remote sensing images based on mountain altitudinal belts of Taibai Mountain in the north-south transitional zone of China [J]. Acta Geographica Sinica, 2020, 75(3): 620-630.
[3]	ZHOU Chenghu, SUN Jiulin, SU Fenzhen, YANG Xiaomei, PEI Tao, GE Yong, YANG Yaping, ZHANG An, LIAO Xiaohan, LU Feng, GAO Xing, FU Dongjie. Geographic information science development and technological application [J]. Acta Geographica Sinica, 2020, 75(12): 2593-2609.
[4]	YU Shuchen, WANG Lunche, XIA Weiping, YU Deqing, LI Chang'an, HE Qiuhua. Spatio-temporal evolution of riparian lakes in Dongting Lake area since the late Qing Dynasty [J]. Acta Geographica Sinica, 2020, 75(11): 2346-2361.
[5]	ZHAO Guining, ZHANG Zhengyong, LIU Lin, XU Liping, WANG Puyu, LI Li, NING Shan. Changes of glacier mass balance in Manas river basin based on multi-source remote sensing data [J]. Acta Geographica Sinica, 2020, 75(1): 98-112.
[6]	LIU Wenchao, LIU Jiyuan, KUANG Wenhui. Spatiotemporal patterns of soil protection effect of the Grain for Green Project in northern Shaanxi [J]. Acta Geographica Sinica, 2019, 74(9): 1835-1852.
[7]	LONG Yuannan,YAN Shixiong,JIANG Changbo,WU Changshan,LI Zhiwei,TANG Rong. A new method for extracting lake bathymetry using multi-temporal and multi-source remote sensing imagery: A case study of Dongting Lake [J]. Acta Geographica Sinica, 2019, 74(7): 1467-1481.
[8]	TU Jianjun,TANG Siqi,ZHANG Qian,WU Yue,LUO Yunchao. Spatial heterogeneity of the effects of mountainous city patternon catering industry location [J]. Acta Geographica Sinica, 2019, 74(6): 1163-1177.
[9]	Jiangbo GAO, Kewei JIAO, Shaohong WU. Revealing the climatic impacts on spatial heterogeneity of NDVI in China during 1982-2013 [J]. Acta Geographica Sinica, 2019, 74(3): 534-543.
[10]	Chengde YANG, Xin WANG, Junfeng WEI, Qionghuan LIU, Anxin LU, Yong ZHANG, Zhiguang TANG. Chinese glacial lake inventory based on 3S technology method [J]. Acta Geographica Sinica, 2019, 74(3): 544-556.
[11]	FAN Keke,ZHANG Qiang,SHI Peijun,SUN Peng,YU Huiqian. Evaluation of remote sensing and reanalysis soil moisture products on the Tibetan Plateau [J]. Acta Geographica Sinica, 2018, 73(9): 1778-1791.
[12]	CHEN Weitong,ZHANG Dong,CUI Dandan,LV Lin,XIE Weijun,SHI Shunjie,HOU Zeyu. Monitoring spatial and temporal changes in the continental coastline and the intertidal zone in Jiangsu province, China [J]. Acta Geographica Sinica, 2018, 73(7): 1365-1380.
[13]	LIU Jiyuan,NING Jia,KUANG Wenhui,XU Xinliang,ZHANG Shuwen,YAN Changzhen,LI Rendong,WU Shixin,HU Yunfeng,DU Guoming,CHI Wenfeng,PAN Tao,NING Jing. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015 [J]. Acta Geographica Sinica, 2018, 73(5): 789-802.
[14]	YANG Siqi,XING Xiaoyue,DONG Weihua,LI Shuaipeng,ZHAN Zhicheng,WANG Quanyi,YANG Peng,ZHANG Yi. The spatio-temporal response of influenza A (H1N1) to meteorological factors in Beijing [J]. Acta Geographica Sinica, 2018, 73(3): 460-473.
[15]	WEN Qi,SHI Linna,MA Caihong,WANG Yongsheng. Spatial heterogeneity of multidimensional poverty at the village level: Loess Plateau [J]. Acta Geographica Sinica, 2018, 73(10): 1850-1864.