Comparison of different spatial sampling methods for validation of GEOV1 FVC product over heterogeneous and homogeneous surfaces

Yanling Ding; Yong Ge; Maogui Hu; Hongyan Zhang

doi:10.1117/12.2241618

25 October 2016 Comparison of different spatial sampling methods for validation of GEOV1 FVC product over heterogeneous and homogeneous surfaces

Yanling Ding, Yong Ge, Maogui Hu, Hongyan Zhang

Author Affiliations +

Proceedings Volume 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII; 99980I (2016) https://doi.org/10.1117/12.2241618
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom

Abstract

The development of an efficient ground sampling strategy which can sample the natural dynamics of variations in variables of interest, is critical to ensuring the validation of remotely sensed products. This study attempts to take a fresh look at geostatistical methods for ground sampling and pixel-mean estimating in remote sensing validation campaigns. Spatial random sampling (SRS), Block Kriging (BK), and Means of Surface with Non-homogeneity (MSN) were implemented to estimate the fractional vegetation cover mean values at GEVO1 1 km² pixel level using Landsat 8 OLI and SPOT4 HRVIR1 fine-resolution FVC maps respectively derived from a homogeneous area covered by forest and a heterogeneous area covered by crop. The GEOV1 FVC product was validated using the means estimated by SRS, BK, and MSN. Root square error (RMSE), mean absolute percentage error (MAPE) and product accuracy (PA) were used to evaluate the validation. Results showed that the MSN method performs well for estimating the means of the surface with non-homogeneity, with a high accuracy of the GEOV1 FVC product (RMSE=0.12, MAPE=29.37 and PA= 77.39%). The statistical values outputted by BK were respectively 0.13, 31.46% and 76.21%. These values of SRS were respectively 0.13, 31.16% and 76.10%. For homogeneous surface, the statistical parameters outputted by these three methods were similar. These results revealed that MSN is an effective method for estimating the spatial means for heterogeneous surface and validating remote sensing product. We can conclude that choosing an appropriate sampling method has a significant impact on the validation of remote sensing product.

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Yanling Ding, Yong Ge, Maogui Hu, and Hongyan Zhang "Comparison of different spatial sampling methods for validation of GEOV1 FVC product over heterogeneous and homogeneous surfaces", Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980I (25 October 2016); https://doi.org/10.1117/12.2241618

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