Assessing interactions between crop biophysical parameters and X-band backscattering using empirical data and model sensitivity analysis

Active microwave remote sensing data at different frequencies can provide crucial information on crop morphology and conditions, thus effectively supporting agronomic management at different scales. In this work, we used variance-based global sensitivity analysis (GSA) as a quantitative framework for investigating the sensitivity of X-band backscattering to agronomic and morphological features typical of two different crops, maize and rice. To this end, we jointly exploited empirical data on crop status and growth, high-resolution TerraSAR-X data, and microwave radiative transfer model (RTM) simulations. Phenology-informed simulations allowed us to quantify the contributions of different scattering mechanisms for the two crops under varying observation setups, to assess the sensitivity of X-band backscattering to morpho-structural crop biophysical parameters (and their interactions), and to evaluate the effects of crop biomass on backscatter across growth stages.

Assessing interactions between crop biophysical parameters and X-band backscattering using empirical data and model sensitivity analysis

Active microwave remote sensing data at different frequencies can provide crucial information on crop morphology and conditions, thus effectively supporting agronomic management at different scales. In this work, we used variance-based global sensitivity analysis (GSA) as a quantitative framework for investigating the sensitivity of X-band backscattering to agronomic and morphological features typical of two different crops, maize and rice. To this end, we jointly exploited empirical data on crop status and growth, high-resolution TerraSAR-X data, and microwave radiative transfer model (RTM) simulations. Phenology-informed simulations allowed us to quantify the contributions of different scattering mechanisms for the two crops under varying observation setups, to assess the sensitivity of X-band backscattering to morpho-structural crop biophysical parameters (and their interactions), and to evaluate the effects of crop biomass on backscatter across growth stages.

Microwave single-scattering properties of non-spheroidal raindrops

Falling raindrops undergo a change in morphology as they grow in size and the fall speed increases. This change can lead to significant effects in passive and active microwave remote sensing measurements, typically in the form of a polarization signal. Because previous studies generally only considered either passive or active measurements and a limited set of frequencies, there exist no general guidelines on how and when to consider such raindrop effects in scientific and meteorological remote sensing. In an attempt to provide an overview on this topic, this study considered passive and active remote sensing simultaneously and a wider set of frequencies than in previous studies. Single-scattering property (SSP) data of horizontally oriented raindrops were calculated using the T-matrix method at a large set of frequencies (34 in total). The shapes of the raindrops were calculated assuming an aerodynamic equilibrium model, resulting in drops with flattened bases. The SSP data are published in an open-access repository in order to promote the usage of realistic microphysical assumptions in the microwave remote sensing community. Furthermore, the SSPs were employed in radiative transfer simulations of passive and active microwave rain observations, in order to investigate the impact of raindrop shape upon observations and to provide general guidelines on usage of the published database. Several instances of noticeable raindrop shape-induced effects could be identified. For instance, it was found that the flattened base of equilibrium drops can lead to an enhancement in back-scattering at 94.1 GHz of 1.5 dBZ at 10 mm h−1, and passive simulations showed that shape-induced effects on measured brightness temperatures can be at least 1 K.

Microwave single scattering properties of non-spheroidal rain drops

Falling rain drops undergo a change in morphology as they grow in size and the fall-speed increases. This change can lead to significant effects in passive and active microwave remote sensing measurements, typically in the form of a polarization signal. Because previous studies generally only considered either passive or active measurements and a limited set of frequencies, there exist no general guidelines on how and when to consider such rain drop effects in scientific and meteorological remote sensing. In an attempt to provide an overview on this topic, this study considered passive and active remote sensing simultaneously and a wider set of frequencies than in previous studies. Single scattering properties (SSP) data of horizontally oriented rain drops were calculated using the T-matrix method at a large set of frequencies (34 in total). The shapes of the rain drops were calculated assuming an aerodynamic equilibrium model, resulting in drops with flattened bases. The SSP data are published in an open-access repository in order to promote the usage of realistic microphysical assumptions in the microwave remote sensing community. Furthermore, the SSP were employed in radiative transfer simulations of passive and active microwave rain observations, in order to investigate the impact of rain drop shape upon observations and to provide general guidelines on usage of the published database. Several instances of significant rain drop shape-induced effects could be identified. For instance, it was found that the flattened base of equilibrium drops can lead to an enhancement in back-scattering at 94.1 GHz. The passive simulations showed shape induced effects of over 1 K at brightness temperatures below 150 GHz.

THE SENSITIVITY OF C-BAND HYBRID POLARIMETRIC RISAT-1 SAR DATA TO LEAF AREA INDEX OF PADDY CROP

<p><strong>Abstract.</strong> Active microwave remote sensing data has become an important source to retrieve crop biophysical parameters due to its unique sensitivity towards geometrical, structural and dielectric properties of various crop components. The temporal variability of various crop biophysical parameters during crop cycle has significant impact on the overall crop yield. In this study, two RISAT-1 hybrid polarimetric temporal SAR datasets at &amp;sim;32&amp;deg; incidence angle were acquired during 2015 Kharif season. The in-situ leaf area index (LAI) values from seventeen paddy fields were measured in synchrony to the satellite passes during both the campaigns. Analysis observed the decreasing trend of backscattering coefficients (&amp;sigma;&amp;deg;_RH, &amp;sigma;&amp;deg;_RV) with increase in LAI. Results indicate that the sensitivity of hybrid polarimetric parameters towards LAI, also depends on the change in crop structure due to crop growth. This study investigate the sensitivity of backscattering coefficients (σ&amp;deg;_RH, σ&amp;deg;_RV) and polarimetric parameters (even bounce, odd bounce and volume component) generated from m-&amp;delta;, m-&amp;chi; and m-&amp;alpha; space decompositions towards LAI using empirical analysis. An increase of 0.16 in R² (from 0.63 to 0.79) clearly indicates that the polarimetric parameters (even bounce, odd bounce and volume component) are more sensitive to LAI of paddy crop than the backscattering coefficients (&amp;sigma;&amp;deg;_RH, &amp;sigma;&amp;deg;_RV). It has been identified that the combined use of backscattering coefficients as well as polarimetric parameters (even bounce, odd bounce and volume component) in the model, can significantly improve the accuracy of the LAI estimation.</p>

Space borne Active Microwave Remote Sensing of Soil Moisture: A Review

Space-borne active microwave remote sensing is an efficient technique to acquire knowledge of land surface soil moisture (SM). Several studies have reported comparable results of surface SM using space-borne scatterometer responses to backscattering from soil layer. However, detection and measuring of SM using these techniques require an appropriate filtering of data, site-specific calibration of surface roughness parameters, prior knowledge of the study area, specific research purpose, careful selection of model, different suitable datasets with appropriate time series, etc. Reported success studies are very site-, data- and situation-specific and show uncertainty in SM estimations therefore, insufficient to reach global conclusions and applications. Scientific challenge before the community is to develop or modify models and appropriate datasets for SM estimations with simplification and high precision with global applicability for complex bio-physical units. The field is new, active, attractive, challenging and interesting area of research for sustainable land and climate change management.