A Semi-Empirical SNR Model for Soil Moisture Retrieval Using GNSS SNR Data
نویسندگان
چکیده
منابع مشابه
A Semi-Empirical SNR Model for Soil Moisture Retrieval Using GNSS SNR Data
The Global Navigation Satellite System-Interferometry and Reflectometry (GNSS-IR) technique on soil moisture remote sensing was studied. A semi-empirical Signal-to-Noise Ratio (SNR) model was proposed as a curve-fitting model for SNR data routinely collected by a GNSS receiver. This model aims at reconstructing the direct and reflected signal from SNR data and at the same time extracting freque...
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This work aims to estimate soil moisture and vegetation characteristics from Global Navigation Satellite System (GNSS) Signal to Noise Ratio (SNR) data using direct and reflected signals by the land surface surrounding a ground-based antenna. Observations are collected over a rainfed wheat field in southwestern France. The retrievals are compared with two independent reference datasets: in situ...
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This paper presents a case study applying GNSS signals, which were reflected on the ground surface (soil, vegetation surface) to derive soil moisture and vegetation height data over a wheat crop field. The GPS antenna was installed at a height of 2.51 m. Soil moisture was retrieved as long as the vegetation height was lower than ∼20 cm. However, with a further increase in plant height, it was n...
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Water vapour, one of the dominant greenhouse gases, is a highly variable constituent of the Earth's atmosphere with a high latent heat. These two factors give it a key role in the development of atmospheric dynamics. Knowledge of the behaviour and distribution of water vapour in the atmosphere is crucial for understanding and predicting weather and climate. Unfortunately, atmospheric water vapo...
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This study reports on the use of PALSAR data to retrieve soil moisture content over agricultural areas. An algorithm transforming temporal series of PALSAR data into soil moisture content by using a constrained minimization technique, integrating a priori information on soil parameters, is presented. The algorithm applies to winter wheat and has been assessed on simulated and experimental data ...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2018
ISSN: 2072-4292
DOI: 10.3390/rs10020280