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 soil information. This has been possible because worldwide researchers have gained a growing experience in building standardized soil profile datasets with measured physical, chemical data and taxonomical information; filling data gaps; using Earth observation data for soil mapping; optimizing soil sampling strategy; processing big data; applying machine learning algorithms; and assessing uncertainty; which support the preparation of global soil maps with increasing accuracy and spatiotemporal resolution.
Data-intensive computing solutions to process and analyze the exploding amount of environmental information are continuously updated. Machine learning algorithms are among the most frequently used tools for data preprocessing and describing the complex relationship between soil properties and environmental covariates with the ability to assess the uncertainty of the predictions. One of the greatest challenges in deriving global gridded soil information is to make the most of the predictive power of machine learning algorithms with the continuously increasing amount of environmental information. This Special Issue is dedicated to machine learning-based methods in:
proximal and digital global mapping of soil properties (e.g., basic, hydraulic, thermal, functional, ecosystem services);
computing systems/algorithms/approaches using Earth observation data to derive global gridded soil datasets;
preprocessing Earth observation data to feed into global soil mapping;
data-intensive computing methods for incorporating Earth observation data for predictive soil mapping;
optimizing temporal resolution to globally track the changes of soil properties,
uncertainty assessment of the derived gridded soil information;
specifying algorithms to local soil specificities in, e.g., proximal soil mapping;
the engagement of remote sensing data with digital soil mapping;
downscaling of large-scale soil feature;
other related topics.
Review contributions on the abovementioned topics are welcomed as well.Dr. Brigitta Szabó (Tóth) Prof.Dr. Eyal Ben-Dor Dr. Yijian Zeng Prof.Dr. Salvatore Manfreda Dr. Madlene Nussbaum Guest Editors
This is the questionnaire developed by HARMONIOUS aimed at identifying the most urgent and important challenges drone-based science will probably face in the near future. All UAS users are encouraged to participate on this short survey.
SINTESI: Il testo offre spunti ed approfondimenti sui processi idrologici superficiali e con particolare riferimento all’interazione acqua-suolo tenendo in considerazione anche le esigenze di carattere tecnico-pratico del lettore. Per tale motivo, oltre a proporre dei contenuti di carattere generale sul tema dell’idrologia superficiale, vengono riportate informazioni utili alla caratterizzazione idrologica in differenti contesti del territorio nazionale.
Qui di seguito si riportano i risultati dell’esonero svolto in data 21/01/2020 sostenuto dagli studenti di Architettura e PAVU. La registrazione avrà luogo il giorno 05/02/2020 alle ore 12:00 presso lo studio del docente.
Gli studenti di PAVU sono pregati di presentarsi con le esercitazioni del corso per la discussione finale.
HARMONIOUS Training Course 2020 – Villach, 26.-29.2 2020
COST Action HARMONIOUS is organizing a Training Course on UAS-based moitoring of Natural and Agricultural Ecosystems.
Preprocessing of the UAS data
Flight planning and data preprocessing
3D reconstruction with UAS (Photogrammetry)
Quality assessment of the UAS-products
UAS Vegetation Monitoring
Explaining the theory and methods, hand on activities on the case studies
Monitoring Natural Ecosystems – plant composition/change and forest structure
Monitoring Agricultural Ecosystems – plant stress and soil moisture monitoring
Subgroup Activities on the case studies proposed by trainers (each participant chooses either natural or agricultural topic, students will work in small groups on the sample data provided with the help of material provided and tutors)
Carinthia University of Applied Sciences (CUAS)
Spatial Information Management, Europastrasse 4, A-9524 Villach, Austria
CUAS Campus in Villach/St. Magdalen
Free of charge, accommodation and travel will be supported by the COST Action HARMONIOUS – Harmonization of UAS techniques for agricultural and natural ecosystems monitoring. Selected students will receive an economical support of 800€.
Small Unmanned Aircraft Systems can access hazardous or inaccessible areas during disaster events and provide rapid response. This is the first book that brings together the best practices of sUAS applied to a broad range of issues in high spatial resolution mapping projects. The case studies included in this book are sUAS based projects.
• Focuses on small UAS based data acquisition and processing into high spatial resolution map products;
• Introduces practical guidance on choosing small UAS hardware, sensors, and software utilized for geospatial mapping;
• Includes a broad range of recently developed case studies lead by highly experienced academics;
• Provides a holistic overview of scientific data acquisition and processing issues and approaches for applications in natural resources, urban environment, disaster response, socio-economic and socio-cultural domains;
• Explains FAA regulations and highlights the different approaches required for mission planning and data analysis.
Il monitoraggio rappresenta la principale fonte di conoscenza nelle scienze ambientali. I recenti progressi nelle tecnologie nell’ambito dell’Osservazione della Terra offrono molteplici possibilità per il monitoring e la tutela ambientale. I Sistemi Aeromobili a Pilotaggio Remoto (SAPR), noti anche con la denominazione di droni, consentono di effettuare una nuova gamma di rilievi ambientali ad altissima risoluzione. Una delle caratteristiche chiave dei sistemi SAPR deriva dalla possibilità di operare come piattaforma multi-sensore, offrendo una visuale estesa dallo spettro del visibile a quello dell’infrarosso termico.
In questo articolo, vengono presentate le principali attività di monitoraggio ambientale svolte dal gruppo di ricerca HydroLAB dell’Università della Basilicata.
Manfreda, S., S.F. Dal Sasso, L. Mita, Il ruolo dei droni nella tutela del territorio ed il monitoraggio ambientale, Knowledge Transfer Review, n. 5, 110-115, 2019. [link]
It is with great pleasure that we invite you to contribute to a Special Issue in the journal Remote Sensing is dedicated to UAS-based studies focusing on environmental monitoring. Particularly, we welcome contributions with:
Added value of UAS data in environmental monitoring;
Methods and procedures for UAS data processing;
Use of UAS in precision farming;
Innovative applications of UAS data for rapid environmental mapping and change detection;
Advanced applications of UAS data for monitoring vegetation state, crop production, soil water content, river evolution, and stream flow;
Potential of different sensors and algorithms for environmental variables.
The deadline for manuscript submission is December 31, 2019.
Detailed information about the special issue as well as information and guidelines for abstract submission can be found here