Title
An Experimental Study on Field Spectral Measurements to Determine Appropriate Daily Time for Distinguishing Fractional Vegetation Cover.
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.
Year
DOI
Venue
2020
10.3390/rs12182942
REMOTE SENSING
Keywords
DocType
Volume
fractional vegetation cover,field spectral measurement,spectral indices,appropriate measurement time
Journal
12
Issue
Citations 
PageRank 
18
0
0.34
References 
Authors
0
9
Name
Order
Citations
PageRank
Du Lyu100.34
Y. B. Liu230.71
Xiaoping Zhang300.34
Xihua Yang423.79
Liang He500.34
Jie He600.34
Jinwei Guo700.34
Jufeng Wang800.34
Qi Cao900.34