Comparison of hyperspectral retrieval models for soil moisture content

Mingli Hao; Wenying Hu

doi:10.1117/12.2520021

12 March 2019 Comparison of hyperspectral retrieval models for soil moisture content

Mingli Hao, Wenying Hu

Proceedings Volume 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application; 110232E (2019) https://doi.org/10.1117/12.2520021
Event: Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 2018, Xi'an, China

Abstract

In order to improve the estimation accuracy of Soil Moisture Content (SMC) by hyperspectral technology, the paper used actual measured spectral data to study quantitative relationship between soil hyperspectral reflectance and the SMC. All total of soil samples from the Puzhehei Scenic Spot in Qiubei County, Yunnan Province in December 2016 were measured in the lab with the spectrometer. This paper used the original reflectivity of the soil samples and its four mathematical transformations as the inversion indicators to construct Unary Linear Regression Model (ULRM), Multiple Stepwise Regression Model (MSRM) and Partial Least Squares Regression Model (PLSRM) aiming to compare the performance and inversion accuracy of these three models, and find the best performance model to inverse the SMC. The results showed that: (1) It was determined that 1350nm, 1450nm, 1841nm, 1897nm, 1905nm, 1935nm and 2146nm were the hyper-spectral characteristic bands of SMC by analyzing the correlation between soil moisture content and reflectance. (2) The coefficients of determinations R² varied between 0.73 and 0.91 and the Root Mean Square Error (RMSE) ranged from 1.51 to 1.86 with the best performance obtained with the PLSM, and the LRM had the lowest inversion accuracy. (3) The PLSRM established by the logarithm of the reflectivity of 1450nm, 1841nm, 1897nm, 1905nm, 1935nm and 2146nm was the best model of the 15 models by comparing the inversion precision of the samples in each model in this study

Citation Download Citation

Mingli Hao and Wenying Hu "Comparison of hyperspectral retrieval models for soil moisture content", Proc. SPIE 11023, Fifth Symposium on Novel Optoelectronic Detection Technology and Application, 110232E (12 March 2019); https://doi.org/10.1117/12.2520021

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Soil science

Reflectivity

Statistical modeling

Error analysis

Mathematical modeling

Remote sensing

Statistical analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years