Neyman-Pearson detection of ground water and nonwater sites using Sentinel-1 SAR data

Songxin Tan

doi:10.1117/12.2674915

17 October 2023 Neyman-Pearson detection of ground water and nonwater sites using Sentinel-1 SAR data

Songxin Tan

Proceedings Volume 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV; 1272709 (2023) https://doi.org/10.1117/12.2674915
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

The study aims to detect ground standing water in cropland during the spring/early summer season in eastern South Dakota, USA. The goal is to develop a reliable and accurate method that can distinguish ground surface open water from vegetation, which is often mistakenly identified as water. To achieve this, the study utilized Sentinel-1 synthetic aperture radar (SAR) data due to its high reliability, short revisit time, and free availability. A total of 159 sites were selected and surveyed, including 78 water sites and 81 non-water sites, located between Brookings, SD and Sioux Falls, SD, USA. The SAR data were preprocessed at both VV and VH polarizations for both water and non-water sites. In previous work, we used maximum likelihood estimation (MLE) of the density functions with a shifted Rayleigh distribution. In this paper, a Neyman-Pearson test for SAR data classification is developed using the Rayleigh priors at the dual-polarization. The developed method demonstrates good performance in distinguishing between water and non-water sites, providing an alternative approach to ground water detection that is important for precision agriculture, hydrologic and environmental studies.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Songxin Tan "Neyman-Pearson detection of ground water and nonwater sites using Sentinel-1 SAR data", Proc. SPIE 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV, 1272709 (17 October 2023); https://doi.org/10.1117/12.2674915

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