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Remote Sensing
Volume 12
Issue 18
10.3390/rs12182942
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Article

An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover

by
Du Lyu
1,2,
Baoyuan Liu
1,3,
Xiaoping Zhang
1,3,*,
Xihua Yang
4,
Liang He
3,
Jie He
3,
Jinwei Guo
3,
Jufeng Wang
3 and
Qi Cao
1
1
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
4
New South Wales Department of Planning, Industry and Environment, Parramatta, NSW 2124, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(18), 2942; https://doi.org/10.3390/rs12182942
Submission received: 4 August 2020 / Revised: 31 August 2020 / Accepted: 8 September 2020 / Published: 10 September 2020
(This article belongs to the Special Issue Spectroscopic Analysis of Plants and Vegetation)
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Abstract

Remote sensing technology has been widely used to estimate fractional vegetation cover (FVC) at global and regional scales. Accurate and consistent field spectral measurements are required to develop and validate spectral indices for FVC estimation. However, there are rarely any experimental studies to determine the appropriate times for field spectral measurements, and the existing guidelines or references are rather general or inconsistent, it is still not agreed upon and detailed experiments are missing for a local research. In this experiment, five groundcover objects were measured continuously from 07:30 a.m. to 17:30 p.m. local time in three consecutive sunny days using a portable spectrometer. The coefficients of variation (CV) were applied to investigate the reflectance variation at wavelengths corresponding to MODIS satellite channels and the derived spectral indices used to estimate FVC, including photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV). The results reveal little variation in the reflectance measured between 10:00 a.m. and 16:00 p.m., with CV values generally less than 10%. The CV values of FVC spectral indices for estimating PV, NPV and bare soil (BS) are generally less than 3%. While more experiments are yet to be carried out at different locations and in different seasons, the findings so far imply that the in situ spectrum measured between 9:00 a.m. and 17:00 p.m. local time would be useful to discriminate FVC objects and validate satellite estimates-based indices using visible, near-infrared and shortwave infrared channels.
Keywords: fractional vegetation cover; field spectral measurement; spectral indices; appropriate measurement time fractional vegetation cover; field spectral measurement; spectral indices; appropriate measurement time
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MDPI and ACS Style

Lyu, D.; Liu, B.; Zhang, X.; Yang, X.; He, L.; He, J.; Guo, J.; Wang, J.; Cao, Q. An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover. Remote Sens. 2020, 12, 2942. https://doi.org/10.3390/rs12182942

AMA Style

Lyu D, Liu B, Zhang X, Yang X, He L, He J, Guo J, Wang J, Cao Q. An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover. Remote Sensing. 2020; 12(18):2942. https://doi.org/10.3390/rs12182942

Chicago/Turabian Style

Lyu, Du, Baoyuan Liu, Xiaoping Zhang, Xihua Yang, Liang He, Jie He, Jinwei Guo, Jufeng Wang, and Qi Cao. 2020. "An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover" Remote Sensing 12, no. 18: 2942. https://doi.org/10.3390/rs12182942

APA Style

Lyu, D., Liu, B., Zhang, X., Yang, X., He, L., He, J., Guo, J., Wang, J., & Cao, Q. (2020). An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover. Remote Sensing, 12(18), 2942. https://doi.org/10.3390/rs12182942

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