L-band Signals Research Articles

L-Band Synthetic Aperture Radar and Its Application for Forest Parameter Estimation, 1972 to 2024: A Review.

Optical remote sensing can effectively capture 2-dimensional (2D) forest information, such as woodland area and percentage forest cover. However, accurately estimating forest vertical-structure relevant parameters such as height using optical images remains challenging, which leads to low accuracy of estimating forest stocks like biomass and carbon stocks. Thus, accurately obtaining vertical structure information of forests has become a significant bottleneck in the application of optical remote sensing to forestry. Microwave remote sensing such as synthetic aperture radar (SAR) and polarimetric SAR provides the capability to penetrate forest canopies with the L-band signal, and is particularly adept at capturing the vertical structure information of forests, which is an alternative ideal remote-sensing data source to overcome the aforementioned limitation. This paper utilizes the Citexs data analysis platform, along with the CNKI and PubMed databases, to investigate the advancements of applying L-band SAR technology to forest canopy penetration and structure-parameter estimation, and provides a comprehensive review based on 58 relevant articles from 1978 to 2024 in the PubMed database. The metrics, including annual publication numbers, countries/regions from which the publications come, institutions, and first authors, with the visualization of results, were utilized to identify development trends. The paper summarizes the state of the art and effectiveness of L-band SAR in addressing the estimation of forest height, moisture, and forest stocks, and also examines the penetration depth of the L-band in forests and highlights key influencing factors. This review identifies existing limitations and suggests research directions in the future and the potential of using L-band SAR technology for forest parameter estimation.

Quantitative analysis of the tropospheric delay differences for 1–300 GHz microwave signals with ground-based microwave radiometric profiles

Tropospheric delay is a significant source of error in various microwave measurement technologies. As the tropospheric delay differences associated with the signal frequency can be neglected for signals near the L band, the Global Navigation Satellite System (GNSS) is frequently used to assist other microwave measurements on tropospheric delay correction for its high precision and all-weather capabilities. However, when the signal frequency differences are significant, further analysis of tropospheric delay related to signal frequency is required for higher accuracy in long-distance propagation. This study quantitatively analyzed the tropospheric delay differences from L-band to millimeter band (1–300 GHz) affected by dry air, water vapor, and liquid water, based on Microwave Radiometer (MWR) measurement profiles and the Millimeter-wave Propagation Model93 (MPM93) at Shanghai. Relative to the GNSS L-band signal of 1.2 GHz, the RMS of tropospheric delay differences over 1–300 GHz varies from 0.033 mm to 9.436 mm, with the maximum tropospheric delay differences up to 18.03 mm at 300 GHz. Tropospheric delay differences strongly correlate with surface temperature and surface pressure, except for some of the atmosphere absorption bands. These quantitative analyses are helpful for the comprehensive application of GNSS to assist other microwave measurement techniques.

Ionospheric compensation in L-band InSAR time-series: Performance evaluation for slow deformation contexts in equatorial regions

Multi-temporal Synthetic Aperture Radar Interferometry (MT-InSAR) is the only geodetic technique allowing to measure ground deformation down to mm/yr over continuous areas. Vegetation cover in equatorial regions favors the use of L-band SAR data to improve interferometric coherence. However, the electron content of ionosphere, affecting the propagation of the SAR signal, shows particularly strong spatio-temporal variations near the equator, while the dispersive nature of the ionosphere makes its effect stronger on low-frequencies, such as L-band signals. To tackle this problem, range split-spectrum method can be implemented to compensate the ionospheric phase contribution. Here, we apply this technique for time-series of ALOS-PALSAR data, and propose optimizations for low-coherence areas. To evaluate the efficiency of this method to retrieve subtle deformation rates in equatorial regions, we compute time-series using four ALOS-PALSAR datasets in contexts of low to medium coherence, showing slow deformation rates (mm/yr to cm/yr). The processed tracks are located in Ecuador, Trinidad and Sumatra, and feature 15 to 19 acquisitions including very high, dominating ionospheric noise, corresponding to equivalent displacements of up to 2 m. The correction method performs well and allows to reduce drastically the noise level due to ionosphere, with significant improvement compared with a simple plane fitting method. This is due to frequent highly non-linear patterns of perturbation, characterizing equatorial TEC distribution. We use semivariograms to quantify the uncertainty of the corrected time-series, highlighting its dependence on spatial distance. Thus, using ALOS-PALSAR-like archive, one can expect a detection threshold on the Line-of-Sight velocity ranging between 3 and 6 mm/yr, depending on the spatial wavelength of the signal to be observed. These values are consistent with the accuracy derived from the comparison of velocities between two tracks in their overlapping area. In the case studies that we processed, the time-series corrected from ionosphere allows to retrieve accurately fault creep and volcanic signal but it is still too noisy for retrieving tiny long-wavelength signals such as slow (mm/yr) interseismic strain accumulation.

ML based approach for inverting penetration depth of SAR signals over large desert areas

Penetration depth of synthetic aperture radar (SAR) signals over a desert is a key parameter to understand the internal properties of the desert. Existing approaches for obtaining the penetration depth require good quality interferometric SAR (InSAR) data of very short temporal and long spatial baselines. Such data are often difficult to obtain in a highly dynamic desert. We propose a new machine learning (ML) based approach for inverting penetration depth of SAR signals over large desert areas by jointly using InSAR, polarimetric SAR (PolSAR) and optical remote sensing data. First, SAR scattering parameters and terrain properties are determined based on PolSAR and Landsat 5 TM multispectral data and a DEM. The penetration depth of SAR signals over a small desert area is obtained based on methods such as using a scattering model. A random forest model is then used to establish the relationship between the SAR scattering parameters and site features, and the penetration depth, and then is used to derive the penetration depth over a large desert area. The approach is applied to calculate the penetration depth of ALOS-1 PALSAR L-band signals for a large part of the Kufra Basin, an area of about 60, 000 km2. The penetration depths of four types of typical landforms in area (i.e., sandy plains, paleochannels, rocks and man-made features) are discussed in relation to the geological and climatic conditions. The average signal penetration depths over the paleochannels, sandy plains, and rocks and man-made features are 2.84 m, 1.97 m, 1.21 m, respectively. It is found that the backscattering coefficient, dielectric constant, surface roughness and mineral composition are the most important parameters in determining the signal penetration depths. An interesting point is that the existence of hematite in the sand can increase the dielectric dissipation of the sand medium and shorten the signal penetration depth.

Analysis of CYGNSS coherent reflectivity over land for the characterization of pan-tropical inundation dynamics

The monitoring of flood and wetland dynamics at global scale is hampered by several limitations, including a reduced data availability in tropical areas due to the presence of clouds affecting visible and infrared imagery, or low spatial and/or temporal resolutions affecting passive and active microwave Earth Observation (EO) data. As a consequence, surface water extent estimates and their temporal variations remain challenging especially in equatorial river basins. Global Navigation Satellite System Reflectometry (GNSS-R) L-band signals recorded onboard Cyclone GNSS (CYGNSS) mission, composed of 8 Low Elevation Orbit (LEO) satellites, provide information on surface properties at high temporal resolution from 2017 up to now. CYGNSS bistatic observations were analyzed for detecting permanent water and seasonal floodplains over the full coverage of the mission, from 40°S to 40°N. We computed CYGNSS reflectivity associated to the coherent component of the received power, that was gridded at 0.1° spatial resolution with a 7-day time sampling afterwards. Several statistical metrics were derived from CYGNSS reflectivity, including the weighted mean and standard deviation, the median and the 90th percentile (respectively Γmean,Γstd,Γmedian and Γ90%) in each pixel. These parameters were clustered using the K-means algorithm with an implementation of the Dynamic Time Warping (DTW) similarity measure. They were compared to static inundation maps, and to dynamic estimations of surface water extent both at the global and regional scales, using the Global Inundation Extent from Multi-Satellites (GIEMS) and MODIS-based products. The difference between Γ90% and Γmedian shows the best sensitivity to the presence of water. The river streams and lakes are correctly detected, and a strong seasonality is identified in CYGNSS reflectivity over the largest floodplains, with the exception of the Cuvette Centrale of Congo which is covered by dense vegetation. This seasonal reflectivity signal correlates well with inundation maps: Pearson’s correlation coefficient between Γmedian and surface water extent from both GIEMS and MODIS is over 0.8 in the largest floodplains. The spatial patterns of reflectivity are consistent with static inundation maps: at the time of maximum flooding extent, a spatial correlation coefficient around 0.75 with Γmedian is obtained for several basins. We also evaluated the dependence of CYGNSS-derived clusters and reflectivity on the dominant land cover type and on the density of Above Groud Biomass (AGB) in the pixel. On the one hand, misclassifications of flooded pixels were observed over vegetated regions, probably due to uncertainties related to the attenuation by the vegetation in both CYGNSS and reference datasets. On the other hand, flooded pixels with a mean AGB up to ∼300 Mg/ha were correctly detected with the clustering. High reflectivity values are also observed over rocky soils in arid regions and create false alarms. Finally, strong winds on large lakes cause surface roughness, and lower reflectivity values are observed in this case which weaken the detection of open water. While these constraints are to be taken in account and corrected in a future model, a pan-tropical mapping of surface water extent dynamics using CYGNSS can be envisaged.

Ionospheric Sounding Based on Spaceborne PolSAR in P-Band

The signal of spaceborne low-frequency full-polarization synthetic aperture radar (full-pol SAR) contains abundant ionospheric information. Phased Array L-band Synthetic Aperture Radar (PALSAR) working in the L-band has been verified as an emerging ionospheric sounding technology. Aiming for a future P-band SAR system, this paper investigates the ability of the P-band SAR system in ionospheric one-dimensional and two-dimensional detection. First, considering different systematic error levels, the total electron content (TEC) retrieval in L/P-band is studied by using three typical full-pol SAR data sets based on a circular polarization algorithm. Second, the TEC data retrieved by SAR are fused with the ionosonde, and the joint retrieval of ionospheric electron density is performed. Results show that the P-band TEC retrieval is approximately twice as accurate as the L-band retrieval under the same conditions, and possesses excellent robustness. In addition, the TEC obtained by L/P-band SAR can be used to correct the electron density of the topside on the ionosonde. Results also show that compared with the topside correction accuracy of L-band SAR, that of the P-band SAR is improved by more than 20%. SAR has natural high-resolution characteristics and the P-band signal contains more obvious ionospheric information than the L-band signal. Therefore, future spaceborne P-band SAR has many advantages in two-dimensional fine ionospheric observation and one-dimensional electron density retrieval.

High-Throughput and Long-Distance Transmission With >120 nm S-, C- and L-Band Signal in a 125μm 4-Core Fiber

We investigate recirculating transmission of a wideband S-, C- and L-band signal in a 4-core fiber. We transmit 552 x 25 GHz spaced, 24.5 GBd channels, covering more than 120 nm bandwidth from 1487.8 nm to 1608.33 nm through each core of the multi-core fiber (MCF), which has the same 125μm cladding dimeter as standard single-mode fiber. We first use PDM-16QAM modulation and measure performance at distances up to 3001 km, corresponding to 43 spans of the 69.8 km MCF. At this distance we measure a decoded throughput of 319 Tb/s or 342 Tb/s when estimating from the generalised mutual information (GMI). Extending the transmission distance to 8027 km, a selection of PDM-QPSK modulated channels across the spectrum were received with an average GMI estimated data-rate of 83.7 Gb/s. These results show that wideband transmission including the S-band has the potential to increase data-rates in long-haul optical fiber transmission. Further, our experiment confirms that 125 μm diameter MCFs can multiply transmission capacity whilst offering benefits of resource sharing and integration, expected in SDM systems.

The Effects of Heavy Precipitation on Polarimetric Radio Occultation (PRO) Bending Angle Observations

Abstract Following the successful launch of the Spanish PAZ mission the proof of concept experiment “Radio Occultation and Heavy Precipitation with PAZ” (ROHP-PAZ) started operating in May 2018. The ROHP-PAZ observations demonstrated that precise measurements of the phase shift between horizontal and vertical polarizations from Global Navigation Satellite System (GNSS) L-band signals are sensitive to oriented hydrometeors along the ray paths. While this differential phase shift measurement as a function of time has proven very useful, the regular radio occultation (RO) intermediate products from different polarized channels, such as bending angle and phase retrievals on the domain of impact parameter, have never been exploited. In this research, we studied the characteristics of polarimetric phase and bending angle difference retrieved by the radio-holographic (RH) method to mitigate atmospheric multipath effect and to explore their use in data assimilation. To validate RH approach in polarimetric retrievals, we performed end-to-end simulations where the hydrometeors are modeled by the effective refractivity with different horizontal extents. The simulation results demonstrate that the strong precipitation (>15 mm h−1) with 40-km horizontal extent can be detected with the retrieved bending angle shift. The calibration process on the impact parameter domain has also been developed to extract the differential phase and bending angle shift from the actual polarimetric RO data. Statistics from the PAZ data shows that the mean retrieved RH polarimetric phase shift with various horizontal extent is approximately proportional to the tangent point location rain rate at a ratio of 0.02 rad (mm h−1)−1.

Development of Soil Moisture Inversion Model for Bare Soil Using Navigation With Indian Constellation (NavIC)

This letter aims to develop an inversion model to estimate soil moisture using Navigation with Indian Constellation (NavIC) L-band signal. Several research works suggest that microwave signal property gets affected after reflecting from the soil surface. The nature of the reflected microwave signal depends on the signal’s penetration depth, which is the factor of water content present in the soil surface. NavIC multipath signal can be used for the estimation of soil moisture using this property. The carrier to noise ratio <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(C/N_{\mathrm {o}})$ </tex-math></inline-formula> of NavIC signal is used for this purpose. The model proposed in the letter is based on the relationship of estimated multipath phase value with the volumetric moisture content present in the soil surface. The output of the developed model is highly encouraging. A linear relation relationship with a high correlation coefficient value of 0.902 and root mean square error (RMSE) of 4.03% is obtained between ground truth soil moisture and retrieved soil moisture from developed algorithm.

Retrieving Freeze/Thaw Surface State From CYGNSS Measurements

Freeze/Thaw (F/T) surface state retrieval is important to further understand hydrological patterns and climate change. This article investigates the use of Earth-reflected Global Positioning System (GPS) L-band signals as collected by the National Aeronautics and Space Administration NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission for F/T surface state retrieval over a target area in South America, covering the Andes Mountains and the Argentinian Pampas. In the study, CYGNSS responsiveness to changes in surface permittivity is leveraged to detect transitions of F/T surface state, at an improved spatio-temporal sampling as compared to traditional Remote Sensing missions. A Seasonal-Threshold Algorithm (STA) is developed and validated using surface temperature data as provided by the European Centre for Medium-Range Weather Forecast (ECMWF) ERA5-Land numerical reanalysis model. Then, the monthly evolution of CYGNSS-derived F/T surface state maps is evaluated and an inter-comparison with the Soil Moisture Active Passive (SMAP) F/T data product is performed.

A Physics-Based Algorithm to Couple CYGNSS Surface Reflectivity and SMAP Brightness Temperature Estimates for Accurate Soil Moisture Retrieval

Remotely sensed soil moisture (SM) with high accuracy and high spatial&#x2013;temporal resolution is crucial to meteorological, agricultural, hydrological, and environmental applications. The Cyclone Global Navigation Satellite System (CYGNSS) is the first constellation that uses the L-band signal transmitted by the GNSS satellites to develop daily SM data products. In this study, a physics-based algorithm is proposed to couple CYGNSS surface reflectivity (SR) and Soil Moisture Active Passive (SMAP) brightness temperature estimates for accurate SM retrieval. The algorithm is based on the radiative transfer model and the SMAP data to derive a combined parameter of the vegetation optical depth (<inline-formula> <tex-math notation="LaTeX">$\tau$ </tex-math></inline-formula>) and the surface roughness parameter (<inline-formula> <tex-math notation="LaTeX">$h$ </tex-math></inline-formula>). The CYGNSS L1 Version 2.1 data of the years 2017&#x2013;2018 and 2019&#x2013;2020 are used for calibration and validation, respectively. The SM estimates agree and correlate well with the SMAP SM and <i>in situ</i> SM data on a global scale (<inline-formula> <tex-math notation="LaTeX">$R =0.679$ </tex-math></inline-formula>, RMSE <inline-formula> <tex-math notation="LaTeX">$=0.051\,\,\text{m}^{3}\text{m}^{-3}$ </tex-math></inline-formula>, and MAE <inline-formula> <tex-math notation="LaTeX">$=0.045\,\,\text{m}^{3}\text{m}^{-\mathrm {3}}$ </tex-math></inline-formula> against SMAP SM; <inline-formula> <tex-math notation="LaTeX">$R = 0.729$ </tex-math></inline-formula> against <i>in situ</i> SM). The proposed algorithm makes contributions from two aspects. First, the proposed algorithm provides a physics-based algorithm using SMAP brightness temperature to calibrate the attenuation due to vegetation and surface roughness on the CYGNSS-derived SR. Unlike attenuation models that have been explored previously in the context of CYGNSS, this algorithm executes the calibration without relying on observations of <inline-formula> <tex-math notation="LaTeX">$h$ </tex-math></inline-formula> or vegetation biophysical parameters as inputs but with the SMAP brightness temperature as the only observations. Second, the proposed algorithm provides a new way for the combined usage of CYGNSS and SMAP to improve the temporal and spatial coverages of global SM with temporal coverage increased by 38.2&#x0025; and spatial coverage increased by 31.6&#x0025;.

GNSS Ocean Bistatic Statistical Scattering in the Time-Varying Regime: Simulation and Model Validation

This work develops around the problem of modeling statistics and correlation properties of the GNSS L-band signal scattered by the moving ocean surface, presented in the previous paper [1]. The modeling work is here completed by deriving an effective method for simulation of the received signal as well as by making a validation study based on simulated and real data. The simulation of the stochastic process embedding the design statistical properties, the temporal correlation model and the system and surface parameters is intricate, in general, and provides a useful tool for researchers interested in modeling and simulation of GNSS reflected signals from a time evolving sea surface. The GNSS received waveforms after 1 ms coherent integration are simulated and the correlation properties of the specular and near-specular points are compared to the theoretical model and to results from real data. Real raw data were collected during an aircraft mission in the Gulf of Finland and in a spaceborne scenario with CYGNSS satellites. Comparisons show good agreement among simulations, model and real data, and demonstrate that the estimated correlation time of the GNSS-R signal, fits real data with higher accuracy with respect to the case in which sea correlation is not accounted, especially when the receiving platform velocity is moderate.

Investigation of the impact of Ionospheric Scintillation on GNSS Performance over East Africa

In recent decades, the reliance on Global Navigation Satellite System (GNSS) applications is gaining ground in the East African region. This region lies within the low geomagnetic latitudes where signal scintillation events due to ionospheric irregularities are frequent. Signal scintillation events pose a considerable challenge to the carrier tracking loop of a Global Positioning System (GPS) receiver’s phase locked loop (PLL) and can result in cycle slips or even a total loss-of-lock. The cycle slips can degrade and disrupt satellite-based navigation systems, leading to significant positioning errors. In this study, data from the International GNSS Service (IGS) and SCIntillation Network and Decision Aid (SCINDA) for the year 2011 was used to statistically analyse the effects of ionospheric scintillation on satellite-based navigation over the East African region. Results obtained show that signal scintillation events follow a seasonal pattern with a higher percentage occurrence of amplitude scintillation events over phase scintillation events. Using the method of phase combinations, cycle slips were identified on GPS L-band signals. It was observed that the frequency of occurrence of cycle slips is higher on L2-frequency than on L1-frequency of the L-band. Furthermore, results showed that the presence of signal scintillation events in signal ray paths increased the errors in GPS receiver position measurement by up to about 10 m. This can compromise the reliability and accuracy of GPS applications in navigation.

Variations of GSM Path Loss Exponent with Propagation Distance at L-Band Frequencies in Different Microcellular Environment of Southwestern Nigeria

Propagation path loss exponent is an important component of system design, and knowing the values helps to avoid surprises when the actual service begins. The path loss exponent is known to be critical in establishing the coverage of any new cellular network. Estimating the path loss exponent of any environment requires raising new data sets, which can be accomplished by conducting experiments. With this objective, the present study reports the L-band signal RSS level measurements of 6 GSM base stations in the urban, suburban and rural environments of Ondo and Ekiti States in the Southwestern region of Nigeria. Using a Sony Ericsson TEMS phone monitoring device—connected to a laptop equipped with TEMS software and base station cell reference—and a GPS device, RSS measurements were performed in each sector of the base station up to 1200 m, employing a single sector verification method. The values of path loss exponents were computed from the deduced values of path loss at 50 m intervals up to distances of 1200 m. Close to the base station, the following exponent values were observed—between 2.0 and 3.8 in the urban environment, 2.0 to 2.8 in the suburban environment while for the rural environment, 1.5 to 2.6 we're observed. After the breakpoint distance, higher path loss exponent values of up to 6 was recorded in the urban environment, exponent value of up to 4.3 was observed in the suburban environment and up to 3.5 exponent value in the rural environment. It was also observed that the rural environment presented the longest breakpoint distance of 500 m. The high path loss exponents observed, especially in the urban environment, could cause GSM operators to rethink the margins they have provided. This study is useful for the design of upcoming network systems in these regions and in similar regions.

Study of ionospheric scintillation during geomagnetic storms at equatorial anomaly region Bhopal

GPS L-band signals get affected by ionospheric scintillation; as a result, satellite navigation too gets affected. The most extreme scintillation activity is expected to occur near the equatorial region during geomagnetic storms. The behavior and morphology of low-latitude ionosphere are different from the other latitudes. The space weather conditions in low latitude show different nature because of the geomagnetic field. Due to penetration of soft, high energetic particles, the plasma density increases, which is the main source of generation of ionospheric irregularities scintillation. GPS scintillation at low latitudes is primarily associated with equatorial spread F. Equatorial spread F is caused by ionospheric irregularities with a spatial spectrum extending from 100 km to less than 1 m. When GPS signals encounter the ionospheric irregularities of various sizes produced during high geomagnetic and solar activity, they undergo drastic changes in their phase and amplitude scintillation indices. The accuracy and reliability of GPS system get affected by scintillation. Also the atmosphere air molecule’s content and deviation of electrons, protons, neutrons according to flow rate are observed. In the present paper, we have studied the scintillation activity at low-latitude station Bhopal.

Double pass remotely pumped L-band EDFA with the integration of Raman amplification using multiwavelength dispersion compensator

We demonstrate a remotely pumped L-band erbium-doped fiber amplifier for long-haul transmission system that consists of a multiwavelength dispersion compensator. In this proposed amplifier, the L-band signals experience double pass amplification using the multiwavelength dispersion compensator as signal reflector. In addition, the distributed Raman amplification helps to improve the gain flatness of the propagated signals that is pumped by a 1497 nm fiber laser. High average transmission gain of 20.64 dB with low gain flatness of 2.64 dB is attained when the input signal power is at 0 dB m with wavelength ranging from 1570.45 to 1604.92 nm. The proposed amplifier structure offers better transmission gain flatness for multiwavelength systems.

Detection of Thunderstorm Using Indian Navigation Satellite NavIC

Navigation satellites provide a good opportunity to monitor both ionospheric and tropospheric conditions by using propagation delays in the L-band signal. However, the availability of S-band frequency in the Indian Regional Navigation Satellite System, Navigation with Indian Constellation (NavIC), provides a unique opportunity to utilize signal strength for monitoring thunderstorms. This article, for the first time, demonstrates that NavIC satellite signal strength measurements can be used to detect thunderstorms. A dynamic time warping technique has been used to detect the presence of thunderstorm cloud systems. The method has been tested with several case studies in Kolkata using one-year measurements. The results indicate suitability of such techniques for monitoring and forecasting of thunderstorms using a navigation satellite.

Challenges of predicting low-latitude ionospheric scintillations

Two regions of the globe that are most affected by ionospheric scintillations are the auroral region and the low-latitude region encompassing the dip equator. Our present-day dependence on satellite-based communication and navigation has led to a resurgence of interest in the prediction of ionospheric scintillations, which degrade the performance of such systems. In the low-latitude ionosphere, the genesis of intermediate-scale (∼100 m to a few km) irregularities, which cause the most severe scintillations on VHF to L-band trans-ionospheric radio signals, is in the growth of the Rayleigh-Taylor (R-T) plasma instability on the bottom-side of the post-sunset equatorial F layer. Theoretical developments and observations by various ground-based instruments, as well as in-situ measurements by instruments onboard rockets and satellites, have identified several parameters of the ambient ionosphere that play key roles in the occurrence of these irregularities over the dip equator. However, the presence of basic conditions for the linear growth of the Rayleigh-Taylor instability fails to explain the large day-to-day variability in the characteristics of these irregularities, which determines the latitudinal distribution and strength of scintillations, and is a result of the nonlinear evolution of the Rayleigh-Taylor instability. In this paper, the present status of the efforts at prediction of low-latitude scintillations on the basis of a multitude of observations and numerical simulation of the development of the Rayleigh-Taylor instability in the equatorial ionosphere are reviewed. In particular, this review describes how observations of ionospheric scintillations may be used to obtain information about the nonlinear evolution of the Rayleigh-Taylor instability under different ambient conditions, which is yet to be explored through numerical simulation of the phenomenon. Such studies have pointed out important gaps in our knowledge about the evolution of equatorial ionospheric irregularities that are responsible for producing scintillations on L-band signals recorded in the equatorial and low-latitude regions around the globe.

L-Band response to freeze/thaw in a boreal forest stand from ground- and tower-based radiometer observations

The extent, timing and duration of seasonal freeze/thaw (FT) state exerts dominant control on boreal forest carbon, water and energy cycle processes. Recent and on-going L-Band (≈1.4 GHz) spaceborne missions have the potential to provide enhanced information on FT state over large geographic regions with rapid revisit time. However, the low spatial resolution of these spaceborne observations (≈45 km) makes it difficult to isolate the primary contributions (soil, vegetation, snow) to the FT signal in boreal forest. To better quantify these controls, two L-Band radiometers were deployed (September 2016 to July 2017) at a black spruce (Picea mariana) dominated boreal forest site; one unit above and one unit on the ground surface below the canopy to disentangle the microwave contributions of overstory canopy, and the ground surface on the FT brightness temperature (TB) signal. Bi-weekly multi-angular measurements from both units were combined in order to estimate effective scattering albedo (ω) and the microwave vegetative optical depth (τ), using the τ-ω microwave vegetation radiative transfer model. Soil moisture probes were inserted in the trunk of two black spruce and one larch (Larix laricina) trunks located in the footprint of the above-canopy radiometer to measure tree trunk relative dielectric constant (RDCtree). Results showed a strong relationship between RDCtree and tree skin temperature (Ttree) under freezing temperature conditions, which led to a gradual decrease of τ in winter. During the spring thawing period in April and May, τ remained relatively stable. In contrast, it increased substantially in June, most likely in relation to the growing season onset. Overall, τ was related to the seasonal RDCtree cycle (r = 0.76). Regarding ω, a value of 0.086 (±0.029) was obtained, but no dependency on Ttree or RDCtree was observed. Despite the observed impact of FT on vegetation L-Band signals, results from continuous TB observations spanning from 14 September 2016 to 25 May 2017, indicated that the main contribution to the observed L-Band TB freeze-up signal in the fall originated from the ground surface. The above-canopy unit showed some sensitivity to overstory canopy FT, yet the sensitivity was lower compared to the signal induced by the ground FT. In April and May, L-Band radiometer FT retrieval agreed closely to the melt onset detection using RDCtree but it was likely related to the coincident presence of liquid water in the snow. Our findings have important applications to L-Band spaceborne FT algorithm development and validation across the boreal forest. More specifically, our findings allow better quantification of the potential effect of frozen ground on various biogeophysical and biogeochemical processes in boreal forests.

Estimation of forest leaf area index and clumping index from the Global Positioning System (GPS) satellite carrier-to-noise-density ratio (C/N0)

ABSTRACTForest leaf area index (LAI) and clumping index (CI) are critical structural parameters to study the biomass, biogeochemical cycles, ecological simulation, and radiation transfer in a forest system. The ground-based measurements by traditional methods are costly, time-consuming, and are sensitive to variations in solar illumination conditions. Global Positioning System (GPS) satellites transfer L-band signals, and the presence of the forest canopy leads to an increase in noise. The GPS satellite’s signal strength is generally described by the carrier-to-noise-density ratio (C/N0). This study explores the potential of using the GPS satellite C/N0 to estimate forest canopy structural parameters. We performed experiments at 16 forest plots in northeastern China. LAI, CI, and canopy closure were estimated by digital hemispherical photography (DHP) using the CAN_EYE software. The GPS satellite C/N0 was recorded with a modified smartphone application, GPSTest. The relationship between the forest canopy structural parameters and satellite C/N0 was analyzed for those observations with satellite elevation angle (SEA) > 30°. The results show that both the true LAI and the effective LAI have strong linear and polynomial correlation with C/N0 and the coefficient of determination (R2) is larger than 0.7. CI is linearly related to C/N0(R2 = 0.56). The linear relationship between the canopy closure and C/N0 is much lower (R2= 0.28). Accounting for the SEA effect, LAI can be estimated with R2 > 0.8, and CI with R2 = 0.6. LAI and CI can be well estimated from C/N0 when the SEA effect is accounted for. In general, the GPS C/N0 provides an alternative method to estimate forest canopy structural parameters.