Use of Drones for Environmental Monitoring
The book “Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments” is the result of five years of intense activities carried out within the context of the COST Action…
HESS Opinions: Towards a common vision for the future of hydrological observatories
The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to gain a deep understanding of the complex hydrologic processes occurring within…
HS1.2.1 – Innovative Technologies and Approaches in Hydrological Monitoring
Co-organized by ESSI4, co-sponsored by IAHS Convener: Salvatore Manfreda Co-conveners: Khim Cathleen SaddiECS, Francesca Uguagliati, Nick van de Giesen, Konstantinos Soulis Effective and enhanced hydrological monitoring is essential for understanding…
Generation of root zone soil moisture from the integration of an all-weather satellite surface soil moisture estimates and an analytical model: A preliminary result in China
In addition to surface soil moisture (SSM) data, root zone soil moisture (RZSM) is particularly significant for irrigation decision-making and agricultural drought warnings since water uptake generally occurs through the…
How Can Seasonality Influence the Performance of Recent Microwave Satellite Soil Moisture Products?
In addition to technical issues related to the instruments used, differences between soil moisture (SM) measured using ground-based methods and microwave remote sensing (RS) can be related to the main…
BIP – Advanced Technologies for Hydrological Monitoring
As part of the Erasmus+ program, the University of Naples (UNINA), Helmholtz Centre for Environmental Research (UFZ), Carinthia University of Applied Sciences (CUAS), University of Debrecen (UD), Politehnica University Timisoara…
Ensemble of optimised machine learning algorithms for predicting surface soil moisture content at a global scale
Accurate information on surface soil moisture (SSM) content at a global scale under different climatic conditions is important for hydrological and climatological applications. Machine-learning-based systematic integration of in situ hydrological…
SMAR: Soil moisture analytical relationship
Code for the application of the SMAR model (Manfreda et al., 2014) and its calibration when root-zone soil moisture data are available for parameter calibration. Available on Zenodo References Manfreda,…
Intercomparison of recent Microwave satellite Soil Moisture Products on European Ecoregions
The study centered on the comprehensive assessment of satellite-based microwave soil moisture (SM) products across Europe, taking into account crucial variables including geographical diversity, climate dynamics, and land cover variations.…
World’s Top 2% Scientists
Seven of the accomplished authors who have made significant contributions to our latest Book on Unmanned Aerial Systems (https://lnkd.in/d67imFHS) have achieved a remarkable milestone in 2023 by being recognized as…
Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environment
The book, “Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environment”, provides a comprehensive exploration of the applications, technologies, and methodologies related to the use of unmanned aerial systems…
Special Issue “Integrating Remote Sensing and Geospatial Big Data for Soil Moisture Estimation”
Dear Colleagues, Soil Moisture (SM) is a vital element in the hydrological cycle and land–atmosphere interactions. Quantification of SM and its spatiotemporal variability is valuable for understanding water availability in…
Estimation of soil moisture from UAS platforms using RGB and thermal imaging sensors in arid and semi-arid regions
Soil moisture (SM) is a connective hydrological variable between the Earth’s surface and atmosphere and affects various climatological processes. Surface soil moisture (SSM) is a key component for addressing energy…
In Situ Observation-Constrained Global Surface Soil Moisture Using Random Forest Model
The inherent biases of different long-term gridded surface soil moisture (SSM) products, unconstrained by the in situ observations, implies different spatio-temporal patterns. In this study, the Random Forest (RF) model…
Planning the future of Harmonious
The Department of Topography and Cartography of the Technical University of Madrid hosted our work group meeting of COST Action – HARMONIOUS from 27 up to the 30 of October.…