Generating high spatiotemporal resolution LAI based on MODIS/GF-1 data and combined Kriging-Cressman interpolation

Authors

  • Liu Zhenhua 1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China; 2. Guangdong Provincial Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China; 3. Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China; 4. Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou 510642, China; 5. Guangzhou Surveying and Mapping Geographic Information Industry Engineering Technology Research Center, Guangzhou 510642, China;
  • Huang Rugen 1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China; 2. Guangdong Provincial Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China; 3. Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China; 4. Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou 510642, China; 5. Guangzhou Surveying and Mapping Geographic Information Industry Engineering Technology Research Center, Guangzhou 510642, China; 6. Pearl River Comprehensive Technology Center (Information Center) of Pearl Water Resources Commission, Guangzhou, 510611, China
  • Hu Yueming 1.College of Natural Resources and Environment, South China Agricultural University 2.Guangdong Provincial Key Laboratory of Land Use and Consolidation,South China Agricultural University
  • Fan Shudi 1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China; 2. Guangdong Provincial Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China; 3. Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China; 4. Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou 510642, China; 5. Guangzhou Surveying and Mapping Geographic Information Industry Engineering Technology Research Center, Guangzhou 510642, China
  • Feng Peihua 1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China; 2. Guangdong Provincial Key Laboratory of Land Use and Consolidation, Guangzhou 510642, China; 3. Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China; 4. Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou 510642, China; 5. Guangzhou Surveying and Mapping Geographic Information Industry Engineering Technology Research Center, Guangzhou 510642, China

Keywords:

data fusion, MODIS, GF-1, LAI, spatiotemporal resolution, spatial interpolation, remote sensing

Abstract

Abstract: Generation of high spatial and temporal resolution LAI (leaf area index) products is challenging because higher spatial resolution remotely sensed data usually have coarse temporal resolutions and vice versa. In this study, a novel method that combining Kriging interpolation and Cressman interpolation was proposed to generate high spatial and temporal resolution LAI products by fusing Moderate Resolution Imaging SpectroRadiometer (MODIS) characterized by coarse spatial resolution and high temporal resolution and Gaofen-1 (GF-1) with fine spatial resolution and coarse temporal resolution. This method was applied to the Huangpu district of Guangzhou, Guangdong, China. The results showed that compared to field observation, the predicted values of LAI had an acceptable accuracy of 73.12%. Using Moran’s I index and Kolmogorov-Smirnov tests, it was found that the MODIS data were spatially auto-correlated and characterized by normal distributions. Scaling down the 1 km×1 km spatial resolution MODIS products to a spatial resolution of 30 m×30 m using point-Kriging resulted in a precision of 79.38% compared to the results at the same spatial resolution derived from an 8 m×8 m spatial resolution GF-1 image by scaling up using block-Kriging. Moreover, the regression models that accounts for the relationship between NDVI (Normalized Difference Vegetation Index) and LAI based on MODIS data obtained the determination coefficients ranging from 0.833 to 0.870. Finally, the data fusion and interpolation of MODIS and GF-1 data using Cressman method generated high spatial and temporal resolution LAI maps, which showed reasonably spatial and temporal variability. The results imply that the proposed method is a powerful tool to create high spatial and temporal resolution LAI products. Keywords: data fusion, MODIS, GF-1, LAI, spatiotemporal resolution, spatial interpolation, remote sensing DOI: 10.3965/j.ijabe.20160905.1777 Citation: Liu Z H, Huang R G, Hu Y M, Fan S D, Feng P H. Generating high spatiotemporal resolution LAI based on MODIS/GF-1 data and combined Kriging-Cressman interpolation. Int J Agric & Biol Eng, 2016; 9(5): 120-131.

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Published

2016-09-30

How to Cite

Zhenhua, L., Rugen, H., Yueming, H., Shudi, F., & Peihua, F. (2016). Generating high spatiotemporal resolution LAI based on MODIS/GF-1 data and combined Kriging-Cressman interpolation. International Journal of Agricultural and Biological Engineering, 9(5), 120–131. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/1777

Issue

Vol. 9 No. 5 (2016): IJABE

Section

Information Technology, Sensors and Control Systems

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