Next Article in Journal
The Socio-Economic and Environmental Variables Associated with Hotspots of Infrastructure Expansion in South America
Next Article in Special Issue
Characterizing Land Surface Phenology and Exotic Annual Grasses in Dryland Ecosystems Using Landsat and Sentinel-2 Data in Harmony
Previous Article in Journal
Feasibility Study of Tractor-Test Vehicle Technique for Practical Structural Condition Assessment of Beam-Like Bridge Deck
Article

Comparison of Different Multispectral Sensors for Photosynthetic and Non-Photosynthetic Vegetation-Fraction Retrieval

by 1,2, 1,*, 3,4 and 5
1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2
School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
3
State Key Laboratory of Desertification and Aeolian Sand Disaster Combating, Gansu Desert Control Research Institute, Lanzhou 730070, China
4
School of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
5
Earth Atmosphere and Environment, Science Faculty, Monash University, Clayton, VIC 3800, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(1), 115; https://doi.org/10.3390/rs12010115
Received: 3 November 2019 / Revised: 16 December 2019 / Accepted: 24 December 2019 / Published: 1 January 2020
(This article belongs to the Special Issue Remote Sensing of Dryland Environment)
It is very difficult and complex to acquire photosynthetic vegetation (PV) and non-PV (NPV) fractions (fPV and fNPV) using multispectral satellite sensors because estimations of fPV and fNPV are influenced by many factors, such as background-noise interference of pixel-, spatial-, and spectral-scale effects. In this study, comparisons between Sentinel-2A Multispectral Instrument (S2 MSI), Landsat-8 Operational Land Imager (L8 OLI), and GF1 Wide Field View (GF1 WFV) sensors for retrieving sparse photosynthetic and non-photosynthetic vegetation coverage are presented. The analysis employed a linear spectral-mixture model (LSMM) and nonlinear spectral-mixture model (NSMM) to unmix pixels with different spectral and spatial resolution images based on field endmembers; the estimated endmember fractions were later validated with reference to fraction measurements. The results demonstrated that: (1) with higher spatial and spectral resolution, the S2 MSI sensor had a clear advantage for retrieving PV and NPV fractions compared to L8 OLI and GF1 WFV sensors; (2) through incorporating more red edge (RE) and near-infrared (NIR) bands, the accuracy of NPV fraction estimation could be greatly improved; (3) nonlinear spectral mixing effects were not obvious on the 10–30 m spatial scale for desert vegetation; (4) in arid regions, a shadow endmember is a significant factor for sparse vegetation coverage estimated with remote-sensing data. The estimated NPV fractions were especially affected by the shadow effects and could increase root mean square by 50%. The utilized approaches in the study could effectively assess the performance of major multispectral sensors to extract fPV and fNPV through the novel method of spectral-mixture analysis. View Full-Text
Keywords: Sentinel-2A MSI; GF1 WFV; Landsat-8 OLI; photosynthetic vegetation; non-photosynthetic vegetation; linear and nonlinear spectral-mixture analysis Sentinel-2A MSI; GF1 WFV; Landsat-8 OLI; photosynthetic vegetation; non-photosynthetic vegetation; linear and nonlinear spectral-mixture analysis
Show Figures

Figure 1

MDPI and ACS Style

Ji, C.; Li, X.; Wei, H.; Li, S. Comparison of Different Multispectral Sensors for Photosynthetic and Non-Photosynthetic Vegetation-Fraction Retrieval. Remote Sens. 2020, 12, 115. https://doi.org/10.3390/rs12010115

AMA Style

Ji C, Li X, Wei H, Li S. Comparison of Different Multispectral Sensors for Photosynthetic and Non-Photosynthetic Vegetation-Fraction Retrieval. Remote Sensing. 2020; 12(1):115. https://doi.org/10.3390/rs12010115

Chicago/Turabian Style

Ji, Cuicui, Xiaosong Li, Huaidong Wei, and Sike Li. 2020. "Comparison of Different Multispectral Sensors for Photosynthetic and Non-Photosynthetic Vegetation-Fraction Retrieval" Remote Sensing 12, no. 1: 115. https://doi.org/10.3390/rs12010115

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop