Abstract
Qinghai Province is one of the four largest pastoral regions in China. Timely monitoring of grass growth and accurate estimation of grass yields are essential for its ecological protection and sustainable development. To estimate grass yields in Qinghai, we used the normalized difference vegetation index (NDVI) time-series data derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) and a pre-existing grassland type map. We developed five estimation approaches to quantify the overall accuracy by combining four data pre-processing techniques (original, Savitzky-Golay (SG), Asymmetry Gaussian (AG) and Double Logistic (DL)), three metrics derived from NDVI time series (VImax, VIseason and VImean) and four fitting functions (linear, second-degree polynomial, power function, and exponential function). The five approaches were investigated in terms of overall accuracy based on 556 ground survey samples in 2016. After assessment and evaluation, we applied the best estimation model in each approach to map the fresh grass yields over the entire Qinghai Province in 2016. Results indicated that: 1) For sample estimation, the cross-validated overall accuracies increased with the increasing flexibility in the chosen fitting variables, and the best estimation accuracy was obtained by the so called “fully flexible model” with R2 of 0.57 and RMSE of 1140 kg/ha. 2) Exponential models generally outperformed linear and power models. 3) Although overall similar, strong local discrepancies were identified between the grass yield maps derived from the five approaches. In particular, the two most flexible modeling approaches were too sensitive to errors in the pre-existing grassland type map. This led to locally strong overestimations in the modeled grass yields.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (Grant No. 41401494), National Key Research and Development Plan (No. 2017YFC0404302), and Talented Youth Project of Hebei Education Department (No. BJ2018043).
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Jianhong Liu is an associate professor at Northwest University. She received her BS degree in geographic information system from Wuhan University in 2008, and her PhD degree in cartography and geographic information system from Beijing Normal University in 2013. Her current research interests include remote sensing image analysis and its applications in agricultural monitoring and land cover/land use change detection.
Clement Atzberger is a professor at the University of Natural Resources and Life Science, Vienna. He is head of the Institute of Surveying, Remote Sensing and Land Information. He is an expert at remote sensing image processing, radiative transfer modeling, vegetation monitoring, time series analysis, land use and land cover classification.
Xin Huang is an undergraduate student at the Northwest University and his major is geography. His research interest is remote sensing applications in land use/land cover change monitoring.
Kejian Shen is a senior engineer at Chinese Academy of Agricultural Engineering Planning and Design. He received his BS degree in land resource management from Hebei Agricultural University in 2005, his Master degree in physical geography from China University of Geosciences (Beijing), and his PhD degree in cartography and geographic information system from Beijing Normal University in 2012. His current research interests include remote sensing image analysis and its applications in agricultural monitoring, and land cover/land use change detection.
Yongmei Liu is an associate professor at Northwest University. She received her BS degree in physical geography from Northwest University in 1992, and her PhD degree in soil science from Institute of Soil and Water Conservation, China Academy of Science in 2006. Her current research interests include hyperspectral remote sensing of vegetation, vegetation index analysis and vegetation change detection.
Lei Wang is an associate professor at Northwest University. He received his BS degree from Wuhan University in 1999, his MS degree from Northwest University in 2005, and his PhD degree from China Academy of Science in 2013. He is specialized in cartography, digital elevation modeling and GIS spatial analysis.
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Liu, J., Atzberger, C., Huang, X. et al. Modeling grass yields in Qinghai Province, China, based on MODIS NDVI data—an empirical comparison. Front. Earth Sci. 14, 413–429 (2020). https://doi.org/10.1007/s11707-019-0780-x
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DOI: https://doi.org/10.1007/s11707-019-0780-x