Ms. Zan Mei Profile

Zan Mei

at Xinjiang Normal Univ

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

SPIE Journal Paper | 2 July 2024

Monitoring soil moisture in cotton fields with synthetic aperture radar and optical data in arid and semi-arid regions

Jingwei Fan, Donghua Chen, Chen Zou, Qihang Zhen, Yisha Du, Deting Jiang, Saisai Liu, Mei Zan

JARS, Vol. 18, Issue 03, 034501, (July 2024) https://doi.org/10.1117/12.10.1117/1.JRS.18.034501

KEYWORDS: Soil moisture, Data modeling, Vegetation, Synthetic aperture radar, Cotton, Environmental monitoring, Backscatter, Polarization, Remote sensing, Education and training

Read Abstract +

Soil moisture is a key factor affecting the growth of crops, and microwave remote sensing is one of the most important methods for inverse studies of soil moisture in agricultural fields in recent years. Cotton is a typical water-demanding crop in arid zones, and accurate estimation of soil moisture information in cotton fields is extremely important for optimizing irrigation management, improving water use efficiency, and increasing cotton yield. This study focuses on extracting feature sets by combining Sentinel-1 and Gaofen-6 satellite data, constructing convolutional neural network (CNN), random forest, support vector regression, and eXtreme gradient boosting model to estimate the soil moisture in cotton fields in Shihezi area of Xinjiang, and designing eight groups of experiments according to the different input data sources. The experimental results show that the accuracy of the soil moisture estimate in cotton fields in arid areas with multi-source data is significantly better than that of a single data source. Moreover, the CNN was best estimated when using multi-source data feature sets as inputs, with a coefficient of determination of 0.789, a root mean square error of 0.0249 cm3/cm3, and an average absolute error of 0.0198 cm3/cm3 for its CNN model. This result demonstrates the effectiveness of CNN in soil moisture estimation and also provides a new method for the use of multi-source remote sensing data for accurate soil moisture estimation in cotton fields in arid areas, and also explores the application of Gaofen-6 data in soil moisture.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

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:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years