학술논문

A simple framework to calibrate a soil water balance model with Sentinel-1 and Sentinel-2 observations over irrigated fields
Document Type
Conference
Source
2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) Metrology for Agriculture and Forestry (MetroAgriFor), 2023 IEEE International Workshop on. :205-210 Nov, 2023
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Geoscience
Robotics and Control Systems
Satellite constellations
Soil measurements
Moisture measurement
Soil moisture
European Space Agency
Calibration
Backscatter
water cloud model
soil water balance
soil moisture
Sentinel-1
NDVI
Language
Abstract
This study presents a framework to calibrate a combined soil water balance (SWB) model and Water Cloud Model (WCM) with Sentinel-1 backscatter observations. The SWB is coupled with WCM, which can simulate backscatter from soil moisture (SM) and Normalized Difference Vegetation Index (NDVI). The combined model, namely SWB(WCM), is calibrated by maximizing the Kling-Gupta Efficiency (KGE) between simulated backscattering values and observations from Sentinel-1. The procedure is carried out over data collected during a field campaign in 2017 at an experimental site in Budrio (BO), Italy, cultivated with tomato. The calibration scheme involves 7 parameters and presents good results in terms of backscatter calibration (KGE=0.69). To evaluate the overall performance of the model, SM estimates from the SWB model are compared with in-situ SM measurements from a Proximal Gamma Ray Station (PGRS), showing promising results (KGE=0.58) in the estimation of soil moisture, without requiring any in-situ soil moisture measurements for calibration.