The TropiSCAT experiment aims to characterize vegetation using multi-frequency polarimetric SAR data. Preliminary experiments using a light setup validated the feasibility. The full experiment is now installed in French Guiana, measuring backscattering, coherence over timescales from minutes to years. Initial results show high coherence on the tower validating measurements, and differences between bands and polarizations over diurnal cycles. Future work includes comparing measurements to models and deforestation/regeneration.
Hv uav multispectral compared to hyperspectral finalTerraLab srl
Assessing the robustness of Vegetation Indices (VIs) to estimate Durum Wheat grown (precision agriculture).
Comparing satellite remote sensing (multispectral reflectance) and hyperspectral measurements (first year)
Comparing UAV multispectral vs field hyperspectral data collection (second year)
Working in progress for environmental applications
Researchers at the Desert Research Institute (DRI) are exploring ways in which unmanned aircraft systems are increasingly being used in civilian government work as well as the private sector for use in applications as diverse as cloud seeding to fighting forest fires.
Hv uav multispectral compared to hyperspectral finalTerraLab srl
Assessing the robustness of Vegetation Indices (VIs) to estimate Durum Wheat grown (precision agriculture).
Comparing satellite remote sensing (multispectral reflectance) and hyperspectral measurements (first year)
Comparing UAV multispectral vs field hyperspectral data collection (second year)
Working in progress for environmental applications
Researchers at the Desert Research Institute (DRI) are exploring ways in which unmanned aircraft systems are increasingly being used in civilian government work as well as the private sector for use in applications as diverse as cloud seeding to fighting forest fires.
Presented by Dadang Hilman (ICCC) on ICCC Coffee Morning on Climate Change series on Drivers of Forest Fires: Identification of Comprehensive Solution, April 15, 2014 at Indonesia National Council on Climate Change, Jakarta, Indonesia.
Sentinel-1 satellites, ESA’s Synthetic Aperture Radar (SAR) mission, provide continuous data from the Earth surface in weekly to biweekly time intervals. This data availability provides an unprecedented opportunity to continuously monitor the Earth surface motion in areas prone to geohazards; such as regions of high seismic and volcanic activities, with the end goal of supporting the Early Warning Systems. However, the great challenge is to derive insights from Terabytes of satellite image sequences, in a computationally-efficient and time-critical manner. We’ve risen to this challenge by designing innovative signal processing and deep learning algorithms to efficiently mine this invaluable wealth of data. This talk gives on overview of our designed solutions, as well as a demonstration of these solutions in the Tectonic and Volcanic monitoring of South America (TecVolSA) project.
On the Use of Satellite Remote Sensing Data to Characterize and Map Fuel TypesBeniamino Murgante
On the Use of Satellite Remote Sensing Data to Characterize and Map Fuel Types
Antonio Lanorte, Rosa Lasaponara - Institute of Methodologies for Environmental Analysis, National Research Council, Italy
Presented by Dadang Hilman (ICCC) on ICCC Coffee Morning on Climate Change series on Drivers of Forest Fires: Identification of Comprehensive Solution, April 15, 2014 at Indonesia National Council on Climate Change, Jakarta, Indonesia.
Sentinel-1 satellites, ESA’s Synthetic Aperture Radar (SAR) mission, provide continuous data from the Earth surface in weekly to biweekly time intervals. This data availability provides an unprecedented opportunity to continuously monitor the Earth surface motion in areas prone to geohazards; such as regions of high seismic and volcanic activities, with the end goal of supporting the Early Warning Systems. However, the great challenge is to derive insights from Terabytes of satellite image sequences, in a computationally-efficient and time-critical manner. We’ve risen to this challenge by designing innovative signal processing and deep learning algorithms to efficiently mine this invaluable wealth of data. This talk gives on overview of our designed solutions, as well as a demonstration of these solutions in the Tectonic and Volcanic monitoring of South America (TecVolSA) project.
On the Use of Satellite Remote Sensing Data to Characterize and Map Fuel TypesBeniamino Murgante
On the Use of Satellite Remote Sensing Data to Characterize and Map Fuel Types
Antonio Lanorte, Rosa Lasaponara - Institute of Methodologies for Environmental Analysis, National Research Council, Italy
Advanced weather forecasting for RES applications: Smart4RES developments tow...Leonardo ENERGY
Recording at: https://youtu.be/45Zpjog95QU
This is the 3rd Smart4RES webinar that will address technological and market challenges in RES prediction and will introduce the Smart4RES strategy to improve weather forecasting models with high resolution.
Through wind and solar applications, Innovative Numerical Weather Prediction and Large-Eddy Simulation approaches will be presented.
La red de telescopios robóticos BOOTES y el proyecto GLORIAcampusmilenio
Bootes es el primer observatorio astronómico robótico ubicado en España para complementar desde Tierra la observación de fuentes celestes estudiadas en altas energías (rayos X y gamma) desde el espacio. En 1998 comienza a funcionar en Huelva, en 2001 en Málaga, y en 2009 se produce la internacionalización del proyecto con Bootes-3 en Nueva Zelanda.
Ponente: Alberto Castro Tirado (España) es licenciado en Físicas por la Universidad de Granada Doctor en Astrofísica por la Universidad de Copenhague. Es Investigador Científico del C.S.I.C desde 2007 y es el Investigador Principal del proyecto Bootes en el Instituto de Astrofísica de Andalucía (IAA). Es miembro de la IAU y ha publicado más de 190 artículos en revistas especializadas como Nature, Science, de divulgación sobre Astronomía y prensa.
2. TropiSCAT : A MULTI-FREQUENCY POLINSAR DATA CAMPAIGN OF ACQUISITION FOR VEGETATION CHARACTERIZATION Clément ALBINET – Office National d’Etudes et de Recherches Aérospatiales (ONERA) Pierre BORDERIES – Office National d’Etudes et de Recherches Aérospatiales (ONERA) Thierry KOLECK – Centre National d’Etudes Spatiales (CNES) Fabio ROCCA – Politecnico di Milano (POLIMI) Stefano TEBALDINI – Politecnico di Milano (POLIMI) Thuy LE TOAN – Centre d’Etudes Spatiales de la BIOsphère (CESBIO) Ludovic VILLARD – Centre d’Etudes Spatiales de la BIOsphère (CESBIO) Stéphane MERMOZ – Centre d’Etudes Spatiales de la BIOsphère (CESBIO) Dinh HO TONG MINH – Politecnico di Milano (POLIMI) IGARSS 2011 VANCOUVER – Tuesday, July 26 – TU4.T05 SAR/Lidar Sensing
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20. TropiSCAT : A MULTI-FREQUENCY POLINSAR DATA CAMPAIGN OF ACQUISITION FOR VEGETATION CHARACTERIZATION Thank you for your attention. (360° panorama from the top of the tower) [email_address]