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...

Full description

Bibliographic Details
Main Authors: Simonetta Paloscia, Paolo Pampaloni, Emanuele Santi
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/10/12/1859
id doaj-b1a2a09412434149b159745b9b604591
record_format Article
spelling doaj-b1a2a09412434149b159745b9b6045912020-11-24T21:35:10ZengMDPI 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 &#8216;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>&#964;</i>-<i>&#969;</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
collection DOAJ
language English
format Article
sources DOAJ
author Simonetta Paloscia
Paolo Pampaloni
Emanuele Santi
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
author_facet Simonetta Paloscia
Paolo Pampaloni
Emanuele Santi
author_sort Simonetta Paloscia
title Radiometric Microwave Indices for Remote Sensing of Land Surfaces
title_short 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_sort radiometric microwave indices for remote sensing of land surfaces
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2018-11-01
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 &#8216;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>&#964;</i>-<i>&#969;</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.
topic microwave radiometry
microwave indices
soil moisture content
vegetation biomass
snow cover characteristics
url https://www.mdpi.com/2072-4292/10/12/1859
work_keys_str_mv AT simonettapaloscia radiometricmicrowaveindicesforremotesensingoflandsurfaces
AT paolopampaloni radiometricmicrowaveindicesforremotesensingoflandsurfaces
AT emanuelesanti radiometricmicrowaveindicesforremotesensingoflandsurfaces
_version_ 1725946279870070784