Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Daniel Carcereri"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 8334-8352 (2023)
Up-to-date canopy height model (CHM) estimates are of key importance for forest resource monitoring and disturbance analysis. In this article, we present a study on the potential of deep learning (DL) for the regression of forest height from TanDEM-X
Externí odkaz:
https://doaj.org/article/ae518d5f090d4bd998d9531e01bda763
Autor:
Paola Rizzoli, Luca Dell'Amore, Jose-Luis Bueso-Bello, Nicola Gollin, Daniel Carcereri, Michele Martone
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 3504-3518 (2022)
The bistatic interferometric coherence is affected by different sources of error, among which volume decorrelation, which quantifies the amount of noise caused by volume scattering mechanisms. This represents a key quantity not only for the performan
Externí odkaz:
https://doaj.org/article/a533dfe2da9a4dc486d31718c5656fb9
Autor:
Jose-Luis Bueso-Bello, Daniel Carcereri, Michele Martone, Carolina González, Philipp Posovszky, Paola Rizzoli
Publikováno v:
Remote Sensing, Vol 14, Iss 16, p 3981 (2022)
The TanDEM-X synthetic aperture radar (SAR) system allows for the recording of bistatic interferometric SAR (InSAR) acquisitions, which provide additional information to the common amplitude images acquired by monostatic SAR systems. More concretely,
Externí odkaz:
https://doaj.org/article/9df94c1f58644d67b553dc0a4b0bd30f
Autor:
Rizzoli, Jose-Luis Bueso-Bello, Daniel Carcereri, Michele Martone, Carolina González, Philipp Posovszky, Paola
Publikováno v:
Remote Sensing; Volume 14; Issue 16; Pages: 3981
The TanDEM-X synthetic aperture radar (SAR) system allows for the recording of bistatic interferometric SAR (InSAR) acquisitions, which provide additional information to the common amplitude images acquired by monostatic SAR systems. More concretely,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::266e431eef3e1bde36910db202336c6d
Autor:
Daniel Carcereri, Paola Rizzoli, Dino Ienco, Jose-Luis Bueso-Bello, Carolina Gonzalez, Stefano Puliti, Lorenzo Brurzone
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f3f5b0f5f7c7daf21fddbd15521cb89
https://doi.org/10.1109/igarss46834.2022.9884872
https://doi.org/10.1109/igarss46834.2022.9884872
Autor:
Paola Rizzoli, José-Luis Bueso-Bello, Ricardo Dal Molin, Daniel Carcereri, Carolina Gonzalez, Michele Martone, Luca Dell'Amore, Nicola Gollin, Pietro Milillo, Manfred Zink
Covering about 30 percent of the Earth’s surface, forests are of paramount importance for the Earth’s ecosystem. They act as effective carbon sinks, reducing the concentration of greenhouse gas in the atmosphere, and help mitigating climate chang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58d43b7305c1aed2dacd3d0535f73607
https://doi.org/10.5194/egusphere-egu22-935
https://doi.org/10.5194/egusphere-egu22-935
Publikováno v:
IGARSS
This paper presents an approach for large-scale precise mapping of agricultural fields based on the analysis of Satellite Image Time Series (SITS) acquired by ESA Sentinel-2 (S2) satellite constellation. The approach has been developed in the framewo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4fbb9d2c7fd7bd474fef34d8b9f9cfdc
https://doi.org/10.1109/igarss39084.2020.9323150
https://doi.org/10.1109/igarss39084.2020.9323150
Publikováno v:
Image and Signal Processing for Remote Sensing XXV.
Information regarding both the spatial distribution and the quantity of vegetation components is of great relevance in different fields. Of particular interest is the detection of Non-Photosynthetic Vegetation (NPV) against Photosynthetic Vegetation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af53a78ff8b7a23ae83f60dbdd988e78
https://doi.org/10.1117/12.2533761
https://doi.org/10.1117/12.2533761