Modeling grass yields in Qinghai Province, China, based on MODIS <i>NDVI</i> data—an empirical comparison

doi:10.1007/s11707-019-0780-x

Front. Earth Sci.

2020, Vol. 14

Issue (2) : 413-429 https://doi.org/10.1007/s11707-019-0780-x

RESEARCH ARTICLE

Modeling grass yields in Qinghai Province, China, based on MODIS NDVI data—an empirical comparison

Jianhong LIU^1,^2,³(

), Clement ATZBERGER³, Xin HUANG^1,², Kejian SHEN^4,⁵, Yongmei LIU^1,², Lei WANG^1,²

¹. Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an 710127, China
². College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
³. Institute of Surveying, Remote Sensing and Land Information, University of Natural Resources and Life Sciences (BOKU), Peter Jordan Straße 82, Vienna 1190, Austria
⁴. Remote Sensing Center for Agriculture and Animal Husbandry of Qinghai, Xining 810007, China
⁵. Chinese Academy of Agricultural Engineering Planning and Design, Beijing 100125, China

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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 (VI_max, VI_season and VI_mean) 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.

Keywords Qinghai Province grass yield remote sensing MODIS vegetation index

Corresponding Author(s): Jianhong LIU

Online First Date: 17 January 2020 Issue Date: 21 July 2020

Cite this article:

Jianhong LIU,Clement ATZBERGER,Xin HUANG, et al. Modeling grass yields in Qinghai Province, China, based on MODIS NDVI data—an empirical comparison[J]. Front. Earth Sci., 2020, 14(2): 413-429.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-019-0780-x
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I2/413

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