Webinar – Drones in Geographical Applications
Do not miss the Webinar organised by Drones MDPI on Drones in Geographical Applications!!! Webinar will be coordinated by George P. Petropoulos and it will include the following talks: Unmanned…
Detection of Surface Water and Floods with Multispectral Satellites
The use of multispectral satellite imagery for water monitoring is a fast and cost-effective method that can benefit from the growing availability of medium–high-resolution and free remote sensing data. Since…
Satellite flood detection integrating hydrogeomorphic and spectral indices
Satellite remote sensing is a highly valuable data source useful in the monitoring of surface water dynamics and an essential tool in flood risk management although several factors can interfere…
Flood Susceptibility Mapping Using a Deep Neural Network Model: The Case Study of Southern Italy
This study suggests a rapid methodology to delineate areas prone to flood using machine learning techniques. Based on available historically flooded areas, the model employs and combines globally collectible and…
VIdeo StabilisatION for image velocimetry analysis in rivers
VISION is open-source software written in MATLAB for video stabilisation using automatic features detection. It can be applied for any use, but it has been developed mainly for image velocimetry…
Best Paper Award Remote Sensing 2022
I’m proud to announce that our recent paper “Current Practices in UAS-based Environmental Monitoring” has been awarded with the Best Paper Award 2022 by Remote Sensing MDPI. This paper has…
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…
Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
Ecosystem complexity is among the important drivers of biodiversity and ecosystem functioning, and unmanned aerial systems (UASs) are becoming an important tool for characterizing vegetation patterns and processes. The variety…
Special Issue “Global Gridded Soil Information Based on Machine Learning”
Dear Colleagues, Recent technological advances in both remote sensing and soil mapping approaches and progress in establishing harmonized soil profile datasets have opened up the potential to derive global gridded…
An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources
The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens of kilometer scales.…
Quantifying Long-term Land Surface and Root Zone Soil Moisture over Tibetan Plateau
It is crucial to monitor the dynamics of soil moisture over the Tibetan Plateau, while considering its important role in understanding the land-atmosphere interactions and their influences on climate systems…
Soil Moisture Monitoring in Iran by Implementing Satellite Data into the Root-Zone SMAR Model
Monitoring Surface Soil Moisture (SSM) and Root Zone Soil Moisture (RZSM) dynamics at the regional scale is of fundamental importance to many hydrological and ecological studies. This need becomes even…
Emerging earth observing platforms offer new insights into hydrological processes
Data, and its timely delivery, presents one of the major constraints in advancing the hydrological sciences. Traditional monitoring techniques are time consuming, expensive, and discontinuous in space and time. Moreover,…
Data Fusion Through Bayesian Methods for Flood Monitoring from Remotely Sensed Data
Producing high-precision flood maps requires integrating and correctly classifying information coming from heterogeneous sources. Methods to perform such integration have to rely on different knowledge bases. A useful tool to…