Radiometric Microwave Indices for Remote Sensing of Land Surfaces
This work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils. Experimental results obtained with ground-based...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/10/12/1859 |
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| author | Simonetta Paloscia Paolo Pampaloni Emanuele Santi |
| author_facet | Simonetta Paloscia Paolo Pampaloni Emanuele Santi |
| author_sort | Simonetta Paloscia |
| collection | DOAJ |
| description | This work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils. Experimental results obtained with ground-based radiometers on different types of natural surfaces by the Microwave Remote Sensing Group of IFAC-CNR starting from ‘80s, are summarized and interpreted by means of theoretical models. It has been pointed out that, with respect to single frequency/polarization observations, microwave indices revealed a higher sensitivity to some significant parameters, which characterize the hydrological cycle, namely: soil moisture, vegetation biomass and snow depth or snow water equivalent. Electromagnetic models have then been used for simulating brightness temperature and microwave indices from land surfaces. As per vegetation covered soils, the well-known tau-omega (<i>τ</i>-<i>ω</i>) model based on the radiative transfer theory has been used, whereas terrestrial snow cover has been simulated using a multi-layer dense-medium radiative transfer model (DMRT). On the basis of these results, operational inversion algorithms for the retrieval of those hydrological quantities have been successfully implemented using multi-channel data from the microwave radiometric sensors operating from satellite. |
| first_indexed | 2024-12-20T15:36:37Z |
| format | Article |
| id | doaj.art-b1a2a09412434149b159745b9b604591 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T15:36:37Z |
| publishDate | 2018-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b1a2a09412434149b159745b9b6045912022-12-21T19:35:23ZengMDPI AGRemote Sensing2072-42922018-11-011012185910.3390/rs10121859rs10121859Radiometric Microwave Indices for Remote Sensing of Land SurfacesSimonetta Paloscia0Paolo Pampaloni1Emanuele Santi2Institute of Applied Physics “Nello Carrara” (IFAC-CNR), via Madonna del Piano, 10, 50019 Firenze, ItalyInstitute of Applied Physics “Nello Carrara” (IFAC-CNR), via Madonna del Piano, 10, 50019 Firenze, ItalyInstitute of Applied Physics “Nello Carrara” (IFAC-CNR), via Madonna del Piano, 10, 50019 Firenze, ItalyThis work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils. Experimental results obtained with ground-based radiometers on different types of natural surfaces by the Microwave Remote Sensing Group of IFAC-CNR starting from ‘80s, are summarized and interpreted by means of theoretical models. It has been pointed out that, with respect to single frequency/polarization observations, microwave indices revealed a higher sensitivity to some significant parameters, which characterize the hydrological cycle, namely: soil moisture, vegetation biomass and snow depth or snow water equivalent. Electromagnetic models have then been used for simulating brightness temperature and microwave indices from land surfaces. As per vegetation covered soils, the well-known tau-omega (<i>τ</i>-<i>ω</i>) model based on the radiative transfer theory has been used, whereas terrestrial snow cover has been simulated using a multi-layer dense-medium radiative transfer model (DMRT). On the basis of these results, operational inversion algorithms for the retrieval of those hydrological quantities have been successfully implemented using multi-channel data from the microwave radiometric sensors operating from satellite.https://www.mdpi.com/2072-4292/10/12/1859microwave radiometrymicrowave indicessoil moisture contentvegetation biomasssnow cover characteristics |
| spellingShingle | Simonetta Paloscia Paolo Pampaloni Emanuele Santi Radiometric Microwave Indices for Remote Sensing of Land Surfaces Remote Sensing microwave radiometry microwave indices soil moisture content vegetation biomass snow cover characteristics |
| title | Radiometric Microwave Indices for Remote Sensing of Land Surfaces |
| title_full | Radiometric Microwave Indices for Remote Sensing of Land Surfaces |
| title_fullStr | Radiometric Microwave Indices for Remote Sensing of Land Surfaces |
| title_full_unstemmed | Radiometric Microwave Indices for Remote Sensing of Land Surfaces |
| title_short | Radiometric Microwave Indices for Remote Sensing of Land Surfaces |
| title_sort | radiometric microwave indices for remote sensing of land surfaces |
| topic | microwave radiometry microwave indices soil moisture content vegetation biomass snow cover characteristics |
| url | https://www.mdpi.com/2072-4292/10/12/1859 |
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