Yu, R, Evans, AJ orcid.org/0000-0002-3524-1571 and Malleson, N orcid.org/0000-0002-6977-0615 (2018) Quantifying grazing patterns using a new growth function based on MODIS Leaf Area Index. Remote Sensing of Environment, 209. pp. 181-194. ISSN 0034-4257
Abstract
Monitoring grazing activities on grassland is crucial for ensuring sustainable grassland development and for protecting it from grazing-led degradation. The Leaf Area Index (LAI), which measures leaf coverage over a surface area, is commonly used as a proxy for grassland condition. However, current studies focus on the year-round or seasonal aggregated LAI change rather than the change that can be attributed explicitly to grazing, which is the important indicator for quantifying grassland grazing. This paper presents a new exponential growth function under grazing with an estimation algorithm, the purpose of which is to extract grazing-led LAI changes for every 8 days' satellite observations. All the analyses are based on the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2H products. An improved MODIS LAI and an expected LAI are produced separately, considering both current and previous grazing-led LAI changes. The differences between expected LAI and improved LAI are then converted to the equivalent carbon mass of grazed material. This grazed carbon mass is then aggregated within the growing season, and compared with the expected carbon mass consumed by livestock (calculated from statistics yearbooks). In addition, Net Primary Productivity (NPP) is produced using the improved LAI, simulated by a Light Use Efficiency with Vegetation Photosynthesis Model (LUE-VPM). This is compared with the NPP produced by LUE-VPM based on original MODIS LAI, MODIS NPP products (MOD17A2H) and grassland monitoring stations' in situ measured data. Results show that the NPP calculated from the improved LAI is statistically the same as in situ converted NPP with a p-value equalling 0.998 (the RMSE between the two is 97.77 gC/m2). Conversely, the p-value between converted in situ measured carbon mass and the MODIS NPP product is 0.011 (the RMSE between the two is 133.98 gC/m2), indicating they are statistically different. The results detailed in this paper provide precise and almost real-time grassland grazing monitoring information for policy makers managing grassland.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Crown Copyright © 2018 Published by Elsevier Inc. This is an author produced version of a paper published in Remote Sensing of Environment. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Leaf Area Index (LAI); MODIS; Grassland productivity; Livestock grazing; Light Use Efficiency (LUE) |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Jun 2018 11:42 |
Last Modified: | 19 Mar 2019 01:39 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.rse.2018.02.034 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132062 |
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