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The rapid development of aircraft and unmanned aerial vehicles (UAV) increases their use, including in polar areas, which are characterized by their remoteness and rather harsh conditions. The dominant trends in airborne radar development are expanding their functionality and increasing the altitude of their applicability. Our study focuses on the functionality enhancement of airborne high-altitude conical scanning radars currently used for circular clouds and precipitation observations as well as for sea wind measurements. Recently, we showed how a semicircular observation scheme, instead of a circular one, can double the maximum applicable altitude of sea wind measurements made with such radars. Here we apply this approach to show how an airborne high-altitude conical scanning radar’s functionality can also be expanded for sea water/ice discrimination within a semicircular observation scheme, again doubling the maximum discrimination altitude compared to circular observations. The discrimination is performed in scatterometer mode using the minimum statistical distance of the measured normalized radar cross sections (NRCSs) to the geophysical model functions (GMFs) of the sea water and ice underlying surfaces. However, as no sea ice GMF is available for the considered horizontal transmit and receive polarization at the Ku band, we instead used a substitute sea ice GMF having the same azimuth isotropic property setting for its NRCSs as the averaged value of the measured azimuth NRCSs within the semicircular observations scheme. Our analysis found that incidence angles of 30°, 45°, and 60° are well suited to our sea water/ice discrimination method, and that incidence angles higher than 30° are preferable as they provide a higher difference in the statistical distance of the measured NRCSs to the sea ice and water GMFs, whereas an incidence angle of 30° provides the highest applicable altitude for sea water/ice discrimination and wind retrieval. We also demonstrated the ability of the sea water/ice discrimination procedure’s implementation for any airborne wind scatterometer or multimode radar operated in scatterometer mode over freezing seas to avoid entirely erroneous sea wind measurement results when a sea ice surface is observed. The obtained results can also be used for enhancing aircraft and UAV radars and for developing new remote sensing systems. Doi: 10.28991/ESJ-2024-08-02-07 Full Text: PDF

To make biologically useful interpretations of the echo signals from an entomological radar (a radar designed and operated to observe insects in flight), it is necessary to relate basic properties of insects (i.e. their mass, size, and form) to their radio-wave scattering characters – e.g. their radar cross-section (RCS) and its variation with aspect or beam polarization. Measurements of RCSs of live or freshly dead specimens in laboratory rigs have played an important role in establishing such relationships, but it is desirable to develop and validate methods employing numerical computation, using electromagnetic calculation software, as a more widely applicable and generalizable alternative. In such computations, the insect is represented by a model with specified size, form, and composition; composition appears as the complex relative permittivity, with both polarizability (real) and loss (imaginary) terms. As a preliminary to investigating how adequately different types of electromagnetic model perform, we have collected and analysed morphometric data on adult, flight-capable specimens of a wide range of insect species, including many known to be migratory and to fly at heights where they would be detectable by radar. Our analyses reveal that appropriate densities for prolate-spheroid models of flying insects are in the range 0.60–0.76 g cm−3, which is about half that measured for air-free samples of the solids and liquids from which insect bodies are formed. From this, appropriate permittivities for the material filling the model are found to be in the range 7–11 (real component) and 2.0–3.5 (imaginary); again, these are much lower than measured values for pure insect-body material. These results enable construction of simple electromagnetic models of insects in which both spatial dimensions and masses are accurate. Computation of model RCSs and their aspect and polarization variations, and comparison of these with laboratory measurements, will be the topic of a follow-up validation study. [ABSTRACT FROM AUTHOR]

Microwave remote sensing offers a powerful tool for monitoring the growth of short, dense vegetation such as soybeans. As the plants mature, changes in their biomass and 3-D structure impact the electromagnetic (EM) backscatter signal. This backscatter information holds valuable insights into crop health and yield, prompting the need for a comprehensive understanding of how structural and biophysical properties of soybeans as well as soil characteristics contribute to the overall backscatter signature. In this study, a full-wave model is developed for simulating L-band backscatter from soybean fields. Leveraging the ANSYS high-frequency structure simulator (HFSS) framework, the model solves for the scattering of EM waves from realistic 3-D structural models of soybean, explicitly incorporating the interplant scattering effects. The model estimates of backscatter match well with the field observations from the SMAPVEX16-MicroWEX and SMAPVEX12, with average differences of 1–2 dB for co-pol and less than 4 dB for cross-pol. Furthermore, the model effectively replicates the temporal dynamics of crop backscatter throughout the growing season. The HFSS analysis revealed that the stems, pods, and soil are the primary contributors to HH-pol backscatter, while the branches contribute to VV-pol, and leaves impact the cross-pol signatures. In addition, a sensitivity study with a 3-D bare soil surface resulted in an average variation of 8 dB in co- and cross-pol, even when the root-mean-square height and correlation length were held constant. These capabilities underscore the model's potential to provide insights into the underlying dynamics of the backscatter for growing vegetation.

The risk of oil spills in the Arctic is growing rapidly as anthropogenic activities increase due to climate-driven sea ice loss. Detecting and monitoring fuel spills in the marine environment is imperative for enacting an efficient response to mitigate the risk. Microwave radar systems can be used to address this issue; therefore, we examined the potential of C-band polarimetric radar for detecting diesel fuel in freezing seawater under windy environmental conditions. We present results from a mesocosm experiment, where we introduced diesel fuel to a seawater-filled cylindrical tub at the Sea-ice Environmental Research Facility (SERF), University of Manitoba. We characterized the temporal evolution of the diesel-contaminated seawater and sea ice by monitoring the normalized radar cross section (NRCS) and polarimetric parameters (i.e., copolarization ratio (Rco), cross-polarization ratio (Rxo), entropy (H), mean-alpha (α), conformity coefficient (μ), and copolarization correlation coefficient (ρco)) at 20° and 25° incidence angles. Three stages were identified, with notably different NRCS and polarimetric results, related to the thermophysical conditions. The transition from calm conditions to windy conditions was detected by the 25° incidence angle, whereas the transition from open water to sea ice was more apparent at 20°. The polarimetric analysis demonstrated that the conformity coefficient can have distinctive sensitivities to the presence of wind and sea ice at different incidence angles. The H versus α scatterplot showed that the range of distribution is dependent upon wind speed, incidence angle, and oil product. The findings of this study can be used to further improve the capability of existing and future C-band dual-polarization radar satellites or drone systems to detect and monitor potential diesel spills in the Arctic, particularly during the freeze-up season. [ABSTRACT FROM AUTHOR]

We present new radar images and polarimetric data for the candidate landing sites of the Russian Luna-25 spacecraft near the Manzinus and Boguslawsky craters in the south polar region of the Moon. The images were obtained with the 64-m TNA-1500 antenna at the Bear Lakes Satellite Communications Center of the Special Design Bureau of the Moscow Power Engineering Institute and the 13.2-m RT-13 radio telescope at the Svetloe Observatory of the Institute of Applied Astronomy of the Russian Academy of Sciences in a bistatic configuration at a wavelength of 4.2 cm. At this wavelength the radar signals can penetrate into the lunar regolith to a depth up to 1 m and are sensitive to surface and suspended rocks with a diameter of about 1 cm or more. A spatial resolution m per pixel was achieved through the focused processing algorithm that avoids the radar image smearing at a long integration time. The receiving-system noise temperature measurements during the entire observation session provided a reliable estimate of the circular polarization ratio (CPR) of the echo signal. Analysis of the radar images obtained revealed regions with high radar backscatter and CPR. The number and distribution of rocks and irregularities with sizes comparable to the radar wavelength on the surface and in the near-surface layer of regolith were estimated. As a result of the radar data analysis, we conclude that the surface and the near-surface regolith layer of the main site are smoother than those of the reserved site, which makes it preferable for landing. Thus, the resulting new radar images and CPR maps can be used in planning future lunar missions. [ABSTRACT FROM AUTHOR]

The oil spill is one of the most impactful sources of marine pollution on the ocean surface, detected by the SAR sensors as dark areas, regions with low backscatter values. Due to the complex mixture of hydrophobic hydrocarbons, mineral oil spills change the water surface tension dampening the capillary gravity waves and provoking a specular reflection. In this work, we associated the geochemical oil characteristics, such as density, viscosity, API, and molecular composition with the backscatter values for each oil spill case. We identified the relationship between the oil weathering processes, with the changes in the backscattering values of ocean oil spills. The method designed zonal sections over the oil spills detected in the SAR images, to extract the backscatter values for each pixel along the section. The lowest backscatter average was observed by the heavy oil spill in the Corsica Island study (−29,99 dB). The highest level of weathering had the highest backscatter averages. Damping rates ranged between 4,12 and 7,07 dB and the backscatter values may be related to low oil layer thickness. Furthermore, low wind speeds may have reduced the contrast between water and oil spills, resulting in low damping ratios in all events. [ABSTRACT FROM AUTHOR]

Measuring the radar backscatter characteristics of glacier ice at different frequencies and incidence angles is fundamental to predicting the glacier mapping performance of a sensor. However, such measurements at 94 GHz do not exist. To address this knowledge gap, we collected 94 GHz radar backscatter data from the surface of Rhônegletscher in Switzerland using the All‐Weather Volcano Topography Imaging Sensor (AVTIS2) real‐aperture Frequency Modulated Continuous Wave radar. We determine the mean normalized radar cross section σmean0 $\left({\sigma }_{\text{mean}}^{0}\right)$ to be −9.9 dB. The distribution closely follows a log‐normal distribution with a high goodness of fit (R2 = 0.99) which suggests that radar backscatter is diffuse and driven by surface roughness. Further, we quantified the uncertainty of AVTIS2 3D point clouds to be 1.30–3.72 m, which is smaller than other ground‐based glacier surface mapping radars. These results demonstrate that glacier surfaces are an efficient scattering target at 94 GHz, hence demonstrating the suitability of millimeter‐wave radar for glacier monitoring. Plain Language Summary: Radar sensors map glacier surfaces by transmitting a signal at a specific frequency and measuring its return strength when reflected back. This returned signal strength, called radar backscatter, is determined by the characteristics of the glacier surface and varies with radar frequency and sensor viewing angle. Millimeter‐wave radars operating at 94 GHz can acquire high resolution measurements of glaciers in most weather conditions. However, there are currently no measurements of radar backscatter from glacier surfaces at this frequency. We therefore acquired the first ever measurements of 94 GHz radar backscatter from glacier ice. The results are consistent with those expected from randomly rough surfaces, hence we conclude that the roughness of the glacier surface is the primary driver of 94 GHz radar backscatter. We also show that 3D glacier surface mapping at this frequency is more accurate than other ground‐based radars that are employed to map glacier geometries. The results overall indicate that 94 GHz radar is an effective tool for glacier monitoring and thus opens up new possibilities for studying glacier processes. Key Points: 94 GHz radar backscatter from alpine glacier ice has been characterized for the first timeSurface roughness is the primary factor in 94 GHz radar backscatter from glacier iceThe uncertainty of 3D glacier mapping using 94 GHz radar has been quantified [ABSTRACT FROM AUTHOR]

ABSTRACT The oil spill is one of the most impactful sources of marine pollution on the ocean surface, detected by the SAR sensors as dark areas, regions with low backscatter values. Due to the complex mixture of hydrophobic hydrocarbons, mineral oil spills change the water surface tension dampening the capillary gravity waves and provoking a specular reflection. In this work, we associated the geochemical oil characteristics, such as density, viscosity, API, and molecular composition with the backscatter values for each oil spill case. We identified the relationship between the oil weathering processes, with the changes in the backscattering values of ocean oil spills. The method designed zonal sections over the oil spills detected in the SAR images, to extract the backscatter values for each pixel along the section. The lowest backscatter average was observed by the heavy oil spill in the Corsica Island study (−29,99 dB). The highest level of weathering had the highest backscatter averages. Damping rates ranged between 4,12 and 7,07 dB and the backscatter values may be related to low oil layer thickness. Furthermore, low wind speeds may have reduced the contrast between water and oil spills, resulting in low damping ratios in all events.

Surface soil moisture has vital role in water energy balance, climate change and agriculture mainly for crop water requirements and irrigation scheduling. Microwave remote sensing with its unique characteristics of high penetration and sensitivity towards dielectric constant, has enabled the researchers to explore various techniques for soil moisture estimation. With the launch of Sentinel-1 (A&B) Synthetic Aperture Radar (SAR) satellites, the hindrance in accessing high spatial and temporal resolution data is eliminated. The current study focuses on surface soil moisture estimation for bare agricultural fields in the semi-arid region. Field soil moisture up to 5 cm depth using HydraGo Probe sensor and surface roughness synchronizing with satellite pass dates were collected from total 102 locations spanning four dates. Volumetric and sensor-based soil moisture are well correlated with R2 = 0.85. The Modified Dubois Model (MDM) was applied to obtain the relative permittivity of the soil for the backscattering coefficient (σ◦) for VV polarization, which is used as one of the inputs in universal Topp’s model for soil moisture calculation. Model derived soil moisture is well correlated with ground-based soil moisture for the entire range of the soil moisture (0.02-0.18 m3m-3) with R2 = 0.85 and RMSE=0.005. The entire soil moisture was categorized in three soil moisture ranges to evaluate the sensitivity. The highest correlation was observed for 0.06-0.1 m3m-3 with R2 = 0.73 and RMSE=0.003 followed by 0.015-0.6 m3m-3 with R2 = 0.81 and RMSE=0.001 and 0.11-0.18 m3m-3 with R2 = 0.48 and RMSE=0.019 which is significantly low. Performance accuracy of MDM is encouraging for bare soil moisture estimation for even the lower range of surface soil moisture.

Abstract Measuring the radar backscatter characteristics of glacier ice at different frequencies and incidence angles is fundamental to predicting the glacier mapping performance of a sensor. However, such measurements at 94 GHz do not exist. To address this knowledge gap, we collected 94 GHz radar backscatter data from the surface of Rhônegletscher in Switzerland using the All‐Weather Volcano Topography Imaging Sensor (AVTIS2) real‐aperture Frequency Modulated Continuous Wave radar. We determine the mean normalized radar cross section σmean0 to be −9.9 dB. The distribution closely follows a log‐normal distribution with a high goodness of fit (R2 = 0.99) which suggests that radar backscatter is diffuse and driven by surface roughness. Further, we quantified the uncertainty of AVTIS2 3D point clouds to be 1.30–3.72 m, which is smaller than other ground‐based glacier surface mapping radars. These results demonstrate that glacier surfaces are an efficient scattering target at 94 GHz, hence demonstrating the suitability of millimeter‐wave radar for glacier monitoring.

Surface soil organic carbon (SOC) content is among the first-order controls on the rate and extent of Arctic permafrost thaw. There is a large discrepancy in current SOC estimates in Arctic tundra, where sparse measurements are unable to capture SOC complexity over the vast tundra region. Synthetic aperture radar (SAR) data are sensitive to surface vegetation, roughness, and moisture conditions, and may provide useful information on surface SOC properties. Here, we investigated the potential of multitemporal Sentinel-1 C-band SAR data for regional SOC mapping in the Arctic tundra through principal component analysis (PCA). Multiple in situ SOC datasets in the Alaska North Slope were assembled to generate a consistent surface (0–10 cm) SOC and bulk density dataset (n = 97). The radar VV backscatter shows a strong correlation with surface SOC, but the correlation varies greatly with surface snow, moisture, and freeze/thaw conditions. However, the first principal component (PC1) of radar backscatter time series from different years shows spatial consistency representing dominant and persistent surface backscatter behavior. The PC1 also shows a strong linear correlation with surface SOC concentration (R = 0.65, pR = −0.65, pin situ data. Our analysis shows that it is possible to separate the effects of different factors on the radar backscatter response using PCA and multitemporal SAR data, which may lead to more effective satellite-based methods for Arctic SOC mapping.

The risk of oil spills in the Arctic is growing rapidly as anthropogenic activities increase due to climate-driven sea ice loss. Detecting and monitoring fuel spills in the marine environment is imperative for enacting an efficient response to mitigate the risk. Microwave radar systems can be used to address this issue; therefore, we examined the potential of C-band polarimetric radar for detecting diesel fuel in freezing seawater under windy environmental conditions. We present results from a mesocosm experiment, where we introduced diesel fuel to a seawater-filled cylindrical tub at the Sea-ice Environmental Research Facility (SERF), University of Manitoba. We characterized the temporal evolution of the diesel-contaminated seawater and sea ice by monitoring the normalized radar cross section (NRCS) and polarimetric parameters (i.e., copolarization ratio (Rco), cross-polarization ratio (Rxo), entropy (H), mean-alpha (α), conformity coefficient (μ), and copolarization correlation coefficient (ρco)) at 20° and 25° incidence angles. Three stages were identified, with notably different NRCS and polarimetric results, related to the thermophysical conditions. The transition from calm conditions to windy conditions was detected by the 25° incidence angle, whereas the transition from open water to sea ice was more apparent at 20°. The polarimetric analysis demonstrated that the conformity coefficient can have distinctive sensitivities to the presence of wind and sea ice at different incidence angles. The H versus α scatterplot showed that the range of distribution is dependent upon wind speed, incidence angle, and oil product. The findings of this study can be used to further improve the capability of existing and future C-band dual-polarization radar satellites or drone systems to detect and monitor potential diesel spills in the Arctic, particularly during the freeze-up season.

Mapping volcanic flow deposits can be achieved by considering backscattering characteristics as a metric of surface roughness. In this study, we developed an approach to extract a measure of surface roughness from dual-band airborne Synthetic Aperture Radar (ASAR) backscattering data to characterize and map various volcanic flow deposits—namely, debris avalanches, lahars, lava flows, and pyroclastic density currents. We employed ASAR and Indian Space Research Organization (ISRO) airborne SAR datasets, from a joint project (ASAR-ISRO), acquired in December 2019 at 2 m spatial resolution, to assess the role and importance of incorporating dual-band data, i.e., L-band and S-band, into surface roughness models. Additionally, we derived and analyzed surface roughness from a digital surface model (DSM) generated from unoccupied aircraft systems (UAS) acquisitions using Structure from Motion (SfM) photogrammetry techniques. These UAS-derived surface roughness outputs served as meter-scale calibration products to validate the radar roughness data over targeted areas. Herein, we applied our method to a region in the United States over the Mount St. Helens volcano in the Cascade Range of Washington state. Our results showed that dual-band systems can be utilized to characterize different types of volcanic deposits and range of terrain roughness. Importantly, we found that a combination of radar wavelengths (i.e., 9 and 24 cm), in tandem with high-spatial-resolution backscatter measurements, yields improved surface roughness maps, compared to single-band, satellite-based approaches at coarser resolution. The L-band (24 cm) can effectively differentiate small, medium, and large-scale structures, namely, blocks/boulders from fine-grained lahar deposits and hummocks from debris avalanche deposits. Additionally, variation in the roughness estimates of lahar and debris avalanche deposits can be identified and quantified individually. In contrast, the S-band (9 cm) can distinguish different soil moisture conditions across variable terrain; for example, identify wet active channels. In principle, this dual-band approach can also be employed with time series of various other SAR data of higher coherence (such as satellite SAR), using different wavelengths and polarizations, encompassing a wider range of surface roughness, and ultimately enabling additional applications at other volcanoes worldwide and even beyond volcanology. [ABSTRACT FROM AUTHOR]

Airborne scatterometer capability depends on not only the device's technical characteristics but also the scheme used for surface observations. Typically, a rotating-beam scatterometer uses a circular scheme for sampling normalized radar cross-sections (NRCS) at wind measurements over the sea. Here, we investigate wind retrieval using an updated semicircular scheme, providing the NRCS sampling at various combinations of incidence angles within the range 30° to 60°. The effectiveness of the wind retrieval using our semicircular sampling scheme was evaluated using Monte Carlo simulations, and we then developed corresponding wind algorithms that used a geophysical model function (GMF). As a result of the study, we found that a semicircular sampling scheme is well suited for wind retrieval over the sea using a rotating-beam scatterometer. We showed that a semicircular scheme can provide wind retrieval accuracies similar to those achievable with a conventional circular scheme, although the semicircular scheme requires approximately three times the number of NRCS samples integrated in each azimuth sector. Most importantly, however, the semicircular scheme enabled a maximum altitude for wind retrieval of twice the height possible with a circular scheme. In this study, we also demonstrate that the wind speed accuracy tends to increase with an increase in the incidence angle and similarly for the wind direction accuracy. Nonetheless, we then show that the simultaneous use of the NRCS sampling scheme at several incidence angles can increase the wind retrieval accuracy, especially when three or four incidence angles are used. The obtained results can be used to enhance airborne scatterometers and multimode radars operated in a scatterometer mode, including airborne high-altitude conical scanning radars, and can be applied to new remote sensing systems' development. [ABSTRACT FROM AUTHOR]

SAR data products for Sentinel-1 have been freely available and delivered operationally on behalf of the European Space Agency since the routine operation of Sentinel-1A in 2014. These products were delivered using the best knowledge at their processing time, in particular with respect to the radiometric calibration. As reprocessing of SAR data products is not foreseen in the nominal processing chain of Sentinel-1, changes of applied processing parameters impact the SAR data quality and can be a disturbing factor for long-term monitoring of radiometric features. In particular, antenna pattern updates produce artificial radiometric steps which are visible in radar backscatter time series, especially in case of monitoring radiometric stable reference targets. This paper introduces a method for correcting changes due to such updates without the need of reprocessing SAR data products. The method was applied to long-lasting time series of data acquisitions which are used to monitor the radiometric performance with reference targets at the DLR calibration site. It has been shown that artificial steps due to antenna pattern updates disappear in backscatter timelines after correct application. Furthermore, the derived absolute radiometric accuracy was improved for the joint observation period of S1A and S1B for almost five years until December 2021. [ABSTRACT FROM AUTHOR]

Mapping volcanic flow deposits can be achieved by considering backscattering characteristics as a metric of surface roughness. In this study, we developed an approach to extract a measure of surface roughness from dual-band airborne Synthetic Aperture Radar (ASAR) backscattering data to characterize and map various volcanic flow deposits—namely, debris avalanches, lahars, lava flows, and pyroclastic density currents. We employed ASAR and Indian Space Research Organization (ISRO) airborne SAR datasets, from a joint project (ASAR-ISRO), acquired in December 2019 at 2 m spatial resolution, to assess the role and importance of incorporating dual-band data, i.e., L-band and S-band, into surface roughness models. Additionally, we derived and analyzed surface roughness from a digital surface model (DSM) generated from unoccupied aircraft systems (UAS) acquisitions using Structure from Motion (SfM) photogrammetry techniques. These UAS-derived surface roughness outputs served as meter-scale calibration products to validate the radar roughness data over targeted areas. Herein, we applied our method to a region in the United States over the Mount St. Helens volcano in the Cascade Range of Washington state. Our results showed that dual-band systems can be utilized to characterize different types of volcanic deposits and range of terrain roughness. Importantly, we found that a combination of radar wavelengths (i.e., 9 and 24 cm), in tandem with high-spatial-resolution backscatter measurements, yields improved surface roughness maps, compared to single-band, satellite-based approaches at coarser resolution. The L-band (24 cm) can effectively differentiate small, medium, and large-scale structures, namely, blocks/boulders from fine-grained lahar deposits and hummocks from debris avalanche deposits. Additionally, variation in the roughness estimates of lahar and debris avalanche deposits can be identified and quantified individually. In contrast, the S-band (9 cm) can distinguish different soil moisture conditions across variable terrain; for example, identify wet active channels. In principle, this dual-band approach can also be employed with time series of various other SAR data of higher coherence (such as satellite SAR), using different wavelengths and polarizations, encompassing a wider range of surface roughness, and ultimately enabling additional applications at other volcanoes worldwide and even beyond volcanology.

The optimization of normalized radar cross-section (NRCS) sampling by a scatterometer allows an increase in the accuracy of the wind retrieval over the water surface and a decrease in the time of the measurement. Here, we investigate the possibility of improving wind vector measurement with an airborne rotating-beam scatterometer mounted under the fuselage. For this purpose, we investigated NRCS sampling at various incidence angles, and the possibility of using NRCS samples obtained during simultaneous measurement at different incidence angles to perform wind retrieval. The proposed wind algorithms are based on a geophysical model function (GMF). Sea wind retrieval was carried out using Monte Carlo simulations with consideration of a single incidence angle or combinations of several incidence angles. The incidence angles of interest were 30°, 35°, 40°, 45°, 50°, 55°, and 60°. The simulation showed that the wind speed error decreased with an increase in the incidence angle, and the wind direction error tended to decrease with an increase in the incidence angle. The single incidence angle case is characterized by higher maximum wind retrieval errors but allows for a higher maximum altitude of the wind retrieval method's applicability to be achieved. The use of several neighboring incidence angles allows a better wind vector retrieval accuracy to be achieved. The combinations of three and four incidence angles provided the lowest maximum wind speed and direction errors in the range of the incidence angles from 45° to 60° but, unfortunately, provide the lowest maximum altitude of applicability of the wind retrieval method. At the same time, the combination of two incidence angles is characterized by slightly higher maximum wind retrieval errors than in the cases of three and four incidence angles, but they are lower than in the case of the single incidence angle. Moreover, the two incidence angles' combination is a simpler way to decrease the wind retrieval errors, especially for measurement near an incidence angle of 30°, providing nearly the highest maximum altitude of the wind retrieval method applicability. The results obtained can be used to enhance existing airborne radars and in the development of new remote sensing systems. [ABSTRACT FROM AUTHOR]

Soil moisture is an important variable in the agriculture system. Likewise, accurate information on soil moisture is needed for the effective modeling of many hydrological and climatological processes. Synthetic Aperture Radar (SAR) operates with the competence to acquire data in any weather condition, has been proved to be sensitive to surface soil moisture. This study has attempted to establish simple experimental relationships to estimate volumetric bare surface soil moisture (smv) using the SAR satellite-based radar backscatter values (σ°). In this study, the in-situ smv measurements of two study sites in the United States were obtained from the SoilSCAPE project whereas σ° data for the same study sites were obtained from the C-band Sentinel-1 satellite. Initially, four experiments were designed based on various radar configurations i.e., combination of polarization and incidence angle(s) at an individual or combined node(s) of each study site. Following this, the statistical analysis in each experiment was carried out using the high volume data i.e., the long-term time-series σ° and in-situ smv that were clustered in these radar configurations. Subsequently, the relationships were established on the basis of outcome of each experiment. Based on the detailed analysis, it was found that out of four experiments, only one experiment outcome in terms of correlations statistics, for a particular radar configuration and study site, was found to be significant and accepted for model development. The derived model was applied and validated over the demo farm located in Pune, India. The comparison between the estimated and in-situ smv measurements shows good agreement, with a mapping accuracy of about 8% observed with the radar configuration- vertical-vertical (VV) polarization with a 43° incidence angle. [ABSTRACT FROM AUTHOR]

Airborne scatterometer capability depends on not only the device’s technical characteristics but also the scheme used for surface observations. Typically, a rotating-beam scatterometer uses a circular scheme for sampling normalized radar cross-sections (NRCS) at wind measurements over the sea. Here, we investigate wind retrieval using an updated semicircular scheme, providing the NRCS sampling at various combinations of incidence angles within the range 30° to 60°. The effectiveness of the wind retrieval using our semicircular sampling scheme was evaluated using Monte Carlo simulations, and we then developed corresponding wind algorithms that used a geophysical model function (GMF). As a result of the study, we found that a semicircular sampling scheme is well suited for wind retrieval over the sea using a rotating-beam scatterometer. We showed that a semicircular scheme can provide wind retrieval accuracies similar to those achievable with a conventional circular scheme, although the semicircular scheme requires approximately three times the number of NRCS samples integrated in each azimuth sector. Most importantly, however, the semicircular scheme enabled a maximum altitude for wind retrieval of twice the height possible with a circular scheme. In this study, we also demonstrate that the wind speed accuracy tends to increase with an increase in the incidence angle and similarly for the wind direction accuracy. Nonetheless, we then show that the simultaneous use of the NRCS sampling scheme at several incidence angles can increase the wind retrieval accuracy, especially when three or four incidence angles are used. The obtained results can be used to enhance airborne scatterometers and multimode radars operated in a scatterometer mode, including airborne high-altitude conical scanning radars, and can be applied to new remote sensing systems’ development.

SAR data products for Sentinel-1 have been freely available and delivered operationally on behalf of the European Space Agency since the routine operation of Sentinel-1A in 2014. These products were delivered using the best knowledge at their processing time, in particular with respect to the radiometric calibration. As reprocessing of SAR data products is not foreseen in the nominal processing chain of Sentinel-1, changes of applied processing parameters impact the SAR data quality and can be a disturbing factor for long-term monitoring of radiometric features. In particular, antenna pattern updates produce artificial radiometric steps which are visible in radar backscatter time series, especially in case of monitoring radiometric stable reference targets. This paper introduces a method for correcting changes due to such updates without the need of reprocessing SAR data products. The method was applied to long-lasting time series of data acquisitions which are used to monitor the radiometric performance with reference targets at the DLR calibration site. It has been shown that artificial steps due to antenna pattern updates disappear in backscatter timelines after correct application. Furthermore, the derived absolute radiometric accuracy was improved for the joint observation period of S1A and S1B for almost five years until December 2021.

The accurate consideration of vegetation descriptors in water cloud model (WCM) is necessary for precise SM retrieval. Most of the vegetation descriptors are sourced from optical remote sensors. The acquisitions from optical sensors are largely hampered by bad weather conditions. For all-weather monitoring, Synthetic Aperture Radar (SAR) based vegetation descriptors are needed to identify and evaluate their performance for SM retrieval. The present study evaluates the various sources/combinations of SAR based vegetation descriptors in WCM to identify the better alternatives of optical-based vegetation descriptors. The performance of three radar-based vegetation descriptors, namely VH polarized backscattering coefficients, depolarization ratio and radar vegetation index (RVI) along with the one optical-based vegetation descriptor, namely leaf area index (LAI) from MODIS were utilized in WCM. The WCM for each vegetation descriptor has been performed using Sentinel-1 VV polarized backscattering coefficients and in-situ SM. The in-situ SM measurements were carried out in the fields around Varanasi District in India during the winter season sown with the wheat crop. The correlations coefficient (r), root mean square error (RMSE) and bias were used to evaluate the performances of vegetation descriptors in WCM for SM retrieval. The study showed that the depolarization ratio is the best for SM retrieval with accuracy of 0.096 ${m}^{3}{m}^{-3}$ followed by RVI, cross-polarized and LAI with 0.100 ${m}^{3}{m}^{-3}$ , 0.124 ${m}^{3}{m}^{-3}$ and 0.124 ${m}^{3}{m}^{-3}$ , respectively. Thus, the depolarization ratio can be used for the retrieval of SM using Sentinel-1 VV polarized backscattering coefficients over the wheat crop. [ABSTRACT FROM AUTHOR]

Currently, unmanned aerial vehicles (UAVs) are widely used due to their low cost and flexibility. In particular, they are used in remote sensing as airborne platforms for various instruments. Here, we investigate the capability of a conical scanning radar operated as a scatterometer mounted on a high-altitude UAV to perform sea surface wind retrieval based on an appropriate geophysical model function (GMF). Increasing the maximum altitude of the wind retrieval method’s applicability is an important problem for UAV or manned aircraft scatterometers. For this purpose, we consider the possibility of increasing the method’s maximum altitude by applying a semicircular scheme for azimuth normalized radar cross section (NRCS) sampling instead of a whole 360° circular scheme. We developed wind retrieval algorithms for both semicircular and circular NRCS sampling schemes and evaluated them using Monte Carlo simulations. The simulations showed that the semicircular scheme for azimuth NRCS sampling enables twice the maximum altitude for wind retrieval compared to a 360° circular scheme. At the same time, however, the semicircular scheme requires approximately three times the number of integrated NRCS samples in each azimuth sector to provide equivalent wind retrieval accuracy. Nonetheless, our results confirm that the semicircular azimuth NRCS sampling scheme is well-suited for wind retrieval, and any wind retrieval errors are within the typical range for scatterometer wind recovery. The obtained results can be used for enhancing existing UAV and aircraft radars, and for the development of new remote sensing systems.

The optimization of normalized radar cross-section (NRCS) sampling by a scatterometer allows an increase in the accuracy of the wind retrieval over the water surface and a decrease in the time of the measurement. Here, we investigate the possibility of improving wind vector measurement with an airborne rotating-beam scatterometer mounted under the fuselage. For this purpose, we investigated NRCS sampling at various incidence angles, and the possibility of using NRCS samples obtained during simultaneous measurement at different incidence angles to perform wind retrieval. The proposed wind algorithms are based on a geophysical model function (GMF). Sea wind retrieval was carried out using Monte Carlo simulations with consideration of a single incidence angle or combinations of several incidence angles. The incidence angles of interest were 30°, 35°, 40°, 45°, 50°, 55°, and 60°. The simulation showed that the wind speed error decreased with an increase in the incidence angle, and the wind direction error tended to decrease with an increase in the incidence angle. The single incidence angle case is characterized by higher maximum wind retrieval errors but allows for a higher maximum altitude of the wind retrieval method’s applicability to be achieved. The use of several neighboring incidence angles allows a better wind vector retrieval accuracy to be achieved. The combinations of three and four incidence angles provided the lowest maximum wind speed and direction errors in the range of the incidence angles from 45° to 60° but, unfortunately, provide the lowest maximum altitude of applicability of the wind retrieval method. At the same time, the combination of two incidence angles is characterized by slightly higher maximum wind retrieval errors than in the cases of three and four incidence angles, but they are lower than in the case of the single incidence angle. Moreover, the two incidence angles’ combination is a simpler way to decrease the wind retrieval errors, especially for measurement near an incidence angle of 30°, providing nearly the highest maximum altitude of the wind retrieval method applicability. The results obtained can be used to enhance existing airborne radars and in the development of new remote sensing systems.

Forest clear-cut detection would be valuable for forest management, if it could be done routinely in near-real-time with a spaceborne synthetic aperture radar (SAR) system, which provides data all year and all-weather. In Sentinel-1 (S-1) time-series data, a forest clearing will lead to reduced backscatter intensity and increased interferometric SAR (InSAR) coherence magnitude. A time-series of 108 interferomtric wide (IW) Single look complex (SLC) S-1 images collected in 2016, 2017, and 2018 are used to study the potential for mapping clear-cut areas in eastern Ireland. We combined multitemporal InSAR coherence and backscatter intensity for the detection. This is an extension of previous studies that used either backscatter intensity or InSAR coherence magnitude, while we show the added value of both together. Coherence magnitude was the strongest predictor of the two. [ABSTRACT FROM AUTHOR]

Glacial lakes pose a serious threat to downstream areas and significantly impact glacier melt. The number and area of lakes has grown in most regions during the last decades due to the ongoing atmospheric warming and retreating glaciers. It is therefore important to identify and monitor these lakes. However, mapping of glacial lakes in alpine regions is challenged by many factors. These factors include the small size of glacial lakes, cloud cover in optical satellite images, cast shadows from mountains and clouds, seasonal snow in satellite images, varying degrees of turbidity amongst glacial lakes, and frozen glacial lake surfaces. In our study, we have developed a fully automated method for mapping glacial lakes across alpine regions including the Python package called “GLakeMap”. The method uses multi-source data such as Sentinel-1 Synthetic Aperture Radar and Sentinel-2 Multi-spectral Instrument data, a digital elevation model, and a random forest classifier model. We use multi-source datasets as inputs for rule-based segmentation of images, mainly aiming at extracting glacial lake objects from satellite images using a set of rules. Segmented objects are then classified either as glacial lake or non-glacial lake objects by the random forest classifier model. The method was tested in eight sites across alpine regions mainly located in High Mountain Asia but also in the Alps and the Andes. We show that the proposed method overcomes a majority of the aforementioned challenges to detect and delineate glacial lakes. The method performs efficiently irrespective of geographic, geologic, and climatic conditions of glacial lakes.

We address surface wave breaking caused by oceanic Internal Solitary Waves (ISWs) and how ISWs are manifested in the SAR altimeter onboard Sentinel-3A and -3B satellites by means of their effects in Significant Wave Height (SWH). Two different regions of the ocean are selected, namely the tropical Atlantic Ocean off the Amazon shelf and the Banda Sea in the Indian Ocean, where there are scenes of Sentinel-3 OLCI acquired simultaneously with an along-track SAR mode altimeter, which include signatures of large amplitude ISWs. New data of unfocused SAR (UF-SAR 20 Hz) and fully focused SAR (FF-SAR 160 Hz) modes are analyzed, which are retracked in full range and over a reduced range of bins (truncation carried out dynamically ten gates away from the estimated epoch position). At first order, in scales of 1–3 km, a strong decrease in the normalized radar cross section (NRCS) over the rough part of the ISWs is observed followed by a small increase in the smooth part relative to the unperturbed ocean background. A second order ISW signature, in scales of 20 km, is noted: the SWH is attenuated after the passage of an ISW, considering length scales of about 10 km before and after the ISW crest. The SWH signatures are unique in showing that the surface wave energy does not return to its unperturbed level after the passage of an ISW, admittedly because intense meter-scale wave breaking results in surface wave energy dissipation. Furthermore, Sentinel-2 MSI images are analyzed and provide insights into this same phenomenon: white-capping resulting in a radiance increase at all (visible) wavelengths. Modulation of breaking waves owing to ISWs is demonstrated by estimates of the fraction of breaking waves in the presence of internal waves.

Extension of the existing airborne radars’ applicability is a perspective approach to the remote sensing of the environment. Here we investigate the capability of the rotating-beam radar installed over the fuselage for the sea surface wind measurement based on the comparison of the backscatter with the respective geophysical model function (GMF). We also consider the robustness of the proposed approach to the partial shading of the underlying water surface by the aircraft nose, tail, and wings. The wind retrieval algorithms have been developed and evaluated using Monte-Carlo simulations. We find our results promising both for the development of new remote sensing systems as well as the functional enhancement of existing airborne radars.

The Chinese HY-2D satellite was launched on 19 May 2021, carrying a Ku-band scatterometer. Together with the operating scatterometers onboard the HY-2B and HY-2C satellites, the HY-2 series scatterometer constellation was built, constituting different satellite orbits and hence opportunity for mutual intercomparison and intercalibration. To achieve intercalibration of backscatter measurements for these scatterometers, this study presents and performs three methods including: (1) direct comparison using collocated measurements, in which the nonlinear calibrations can also be derived; (2) intercalibration over the Amazon rainforest; (3) and the double-difference technique based on backscatter simulations over the global oceans, in which a geophysical model function and numerical weather prediction (NWP) model winds are needed. The results obtained using the three methods are comparable, i.e., the differences among them are within 0.1 dB. The intercalibration results are validated by comparing the HY-2 series scatterometer wind speeds with NWP model wind speeds. The curves of wind speed bias for the HY-2 series scatterometers are quite similar, particularly in wind speeds ranging from 4 to 20 m/s. Based on the well-intercalibrated backscatter measurements, consistent sea surface wind products from HY-2 series scatterometers can be produced, and greatly benefit data applications.

The coastline environment and urban areas of Peru overlooking the Pacific Ocean are among the most affected by El Niño-Southern Oscillation (ENSO) events, and its cascading hazards such as floods, landslides and avalanches. In this work, the complete archives of the European Space Agency (ESA)'s European Remote-Sensing (ERS-1/2) missions and European Commission's Copernicus Sentinel-1 constellation were screened to select synthetic aperture radar (SAR) images covering the most severe and recent ENSO-related flooding events that affected Lima, the capital and largest city of Peru, in 1997–1998 and 2017–2018. Based on SAR backscatter color composites and ratio maps retrieved from a series of pre-, cross- and post-event SAR pairs, flooded areas were delineated within the Rímac River watershed. These are mostly concentrated along the riverbanks and plain, where low-lying topography and gentle slopes (≤5°), together with the presence of alluvial deposits, also indicate greater susceptibility to flooding. A total of 409 areas (58.50 km2) revealing change were mapped, including 197 changes (32.10 km2) due to flooding-related backscatter variations (flooded areas, increased water flow in the riverbed, and riverbank collapses and damage), and 212 (26.40 km2) due to other processes (e.g., new urban developments, construction of river embankments, other engineering works, vegetation changes). Urban and landscape changes potentially contributing, either detrimentally or beneficially, to flooding susceptibility were identified and considered in the overall assessment of risk. The extent of built-up areas within the basin was mapped by combining information from the 2011 Global Urban Footprint (GUF) produced by the German Aerospace Center (DLR), the Open Street Map (OSM) accessed from the Quantum GIS (QGIS) service, and 2011–2019 very high-resolution optical imagery from Google Earth. The resulting flooding risk map highlights the sectors of potential concern along the Rímac River, should flooding events of equal severity as those captured by SAR images occur in the future. [ABSTRACT FROM AUTHOR]

Abandoned agricultural land (AAL) is a European problem and phenomenon when agricultural land is gradually overgrown with shrubs and forest. This wood biomass has not yet been systematically inventoried. The aim of this study was to experimentally prove and validate the concept of the satellite-based estimation of woody above-ground biomass (AGB) on AAL in the Western Carpathian region. The analysis is based on Sentinel-1 and -2 satellite data, supported by field research and airborne laser scanning. An improved AGB estimate was achieved using radar and optical multi-temporal data and polarimetric coherence by creating integrated predictive models by multiple regression. Abandonment is represented by two basic AAL classes identified according to overgrowth by shrub formations (AAL1) and tree formations (AAL2). First, an allometric model for AAL1 estimation was derived based on empirical material obtained from blackthorn stands. AAL2 biomass was quantified by different procedures related to (1) mature trees, (2) stumps and (3) young trees. Then, three satellite-based predictive mathematical models for AGB were developed. The best model reached R2 = 0.84 and RMSE = 41.2 t·ha−1 (35.1%), parametrized for an AGB range of 4 to 350 t·ha−1. In addition to 3214 hectares of forest land, we identified 992 hectares of shrub–tree formations on AAL with significantly lower wood AGB than on forest land and with simple shrub composition.

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• A change detection algorithm was applied to disaggregate PALS soil moisture retrievals by using UAVSAR radar data. • The algorithm was developed on the linear relationship between change in soil moisture and radar backscatter coefficient. • The disaggregated results show good agreement validated using ground measurements collected in SMAPVEX12 campaign. The SMAPVEX12 (Soil Moisture Active Passive (SMAP) Validation Experiment 2012) experiment was conducted during June-July 2012 in Manitoba, Canada with the goal of collecting remote sensing data and ground measurements for the development and testing of soil moisture retrieval algorithms under varying vegetation and soil conditions for the SMAP satellite. The aircraft based soil moisture data provided by the passive/active microwave sensor PALS (Passive and Active L-band System) has a nominal spatial resolution of 1600 m. However, this resolution is not compatible with agricultural, meteorological and hydrological studies that require high spatial resolutions and this issue can be solved by soil moisture disaggregation. The soil moisture disaggregation algorithm integrates radiometer soil moisture retrievals and high-resolution radar observations and it can provide soil moisture estimates at a finer scale than the radiometer data alone. In this study, a change detection algorithm was used for disaggregation of coarse resolution passive microwave soil moisture retrievals with radar backscatter coefficients obtained from the higher spatial resolution UAVSAR (Unmanned Air Vehicle Synthetic Aperture Radar) at crop field scale. The accuracy of the disaggregated change in soil moisture was evaluated using ground based soil moisture measurements collected during SMAPVEX12 campaign. The results showed that soil moisture spatial variabilities were better characterized by the disaggregated change in soil moisture estimates at 5 m/800 m resolution as well as a good agreement between disaggregated estimates and in situ measurements. It also showed that VWC (Vegetation Water Content) did not have a big impact on disaggregation algorithm performance, with R2 of the disaggregated results ranging 0.628–0.794. The 5 m and 800 m resolution disaggregated soil moisture did no show significant difference in statistical performance variables. [ABSTRACT FROM AUTHOR]

Following the mission science plan of EPS/Metop-SG C-band scatterometer for 2023–2044, we consider the potential application of the sea ice/water discrimination method based on the minimum statistical distance of the measured normalized radar cross sections (NRCS) to the geophysical model functions (GMF) of the sea ice and water, respectively. The application of the method is considered for the classical spacecraft scatterometer geometry with three fixed fan-beam antennas and the hypothetical prospective scatterometer geometry with the five fixed fan-beam antennas. Joint vertical (VV) and horizontal (HH) transmit and receive polarization are considered for the spaceborne scatterometer geometries. We show explicitly that the hypothetical five fixed fan-beam antenna geometry combined with the dual VV and HH polarization for all antennas provides better estimates of the sea wind speed and direction as well as sea ice/water discrimination during single spacecraft pass. The sea ice/water discrimination algorithms developed for each scatterometer geometry and dual VV/HH polarization are presented. The obtained results can be used to optimize the design of new spaceborne scatterometers and will be beneficial to the forthcoming satellite missions.

The coastline environment and urban areas of Peru overlooking the Pacific Ocean are among the most affected by El Niño-Southern Oscillation (ENSO) events, and its cascading hazards such as floods, landslides and avalanches. In this work, the complete archives of the European Space Agency (ESA)’s European Remote-Sensing (ERS-1/2) missions and European Commission’s Copernicus Sentinel-1 constellation were screened to select synthetic aperture radar (SAR) images covering the most severe and recent ENSO-related flooding events that affected Lima, the capital and largest city of Peru, in 1997–1998 and 2017–2018. Based on SAR backscatter color composites and ratio maps retrieved from a series of pre-, cross- and post-event SAR pairs, flooded areas were delineated within the Rímac River watershed. These are mostly concentrated along the riverbanks and plain, where low-lying topography and gentle slopes (≤5°), together with the presence of alluvial deposits, also indicate greater susceptibility to flooding. A total of 409 areas (58.50 km2) revealing change were mapped, including 197 changes (32.10 km2) due to flooding-related backscatter variations (flooded areas, increased water flow in the riverbed, and riverbank collapses and damage), and 212 (26.40 km2) due to other processes (e.g., new urban developments, construction of river embankments, other engineering works, vegetation changes). Urban and landscape changes potentially contributing, either detrimentally or beneficially, to flooding susceptibility were identified and considered in the overall assessment of risk. The extent of built-up areas within the basin was mapped by combining information from the 2011 Global Urban Footprint (GUF) produced by the German Aerospace Center (DLR), the Open Street Map (OSM) accessed from the Quantum GIS (QGIS) service, and 2011–2019 very high-resolution optical imagery from Google Earth. The resulting flooding risk map highlights the sectors of potential concern along the Rímac River, should flooding events of equal severity as those captured by SAR images occur in the future.

Radiometric calibration adjusts the measured pixel intensity to a physical property, the radar cross section (RCS). After calibration, this relationship is defined over the entire backscatter range: from low image power (near noise) up to high reflections (below saturation). Based on a proper radiometric calibration, the measured radar backscatter for the Sentinel-1 synthetic aperture radar (SAR) satellite constellation is validated over a wide backscatter range using different target types. Therefore, the RCS derived from point targets and radar brightness from distributed targets are compared between Sentinel-1A (S-1A) and Sentinel-1B (S-1B) acquisitions over the same observation area for regions where a stable target backscatter is expected for a certain period of time. Low differences (in the order of 0.3 dB) are found between S-1A and S-1B for high and medium backscatter derived from point targets or rainforest regions, but higher differences for low backscattering regions like ice areas and lakes. For comparing radar brightness containing low backscatter targets, an accurate derived noise level has to be taken into account. In addition to the measured lower noise equivalent beta zero (NEBZ) level, higher transmit power was detected for S-1B compared to S-1A. The higher antenna gain of S-1B leads finally to a higher sensitivity for low backscattering areas of S-1B compared to S-1A and explains the found differences.

We consider sea ice and water microwave backscatter features at the C-band with vertical transmit and receive polarization and present a method for sea ice/water discrimination using a multiple fixed fan-beam satellite scatterometer. The method is based on the criterion of the minimum statistical distance of measured backscatter values to the sea ice and water (CMOD7) geophysical model functions. Implementation of the method is considered both for a typical three fan-beam geometry as well as for a potential five fan-beam geometry of a satellite scatterometer. By using computer simulations, we show explicitly that the number of looks at the same cell from different azimuthal directions needs to be increased to provide better (unambiguous) retrieval of the wind vector and sea ice/water discrimination. The algorithms for sea ice/water discrimination are described, and the results obtained are also discussed along with recommendations for the number of different azimuthal looks (beams) at the same cell from the point of view of sea ice/water discrimination as well as unambiguous wind direction retrieval during the satellite’s single pass.

Abstract: The concept of isohydry/anisohydry describes the degree to which plants regulate their water status, operating from isohydric with strict regulation to anisohydric with less regulation. Though some species level measures of isohydry/anisohydry exist at a few locations, ecosystem‐scale information is still largely unavailable. In this study, we use diurnal observations from active (Ku‐Band backscatter from QuikSCAT) and passive (X‐band vegetation optical depth (VOD) from Advanced Microwave Scanning Radiometer on EOS Aqua) microwave satellite data to estimate global ecosystem isohydry/anisohydry. Here diurnal observations from both satellites approximate predawn and midday plant canopy water contents, which are used to estimate isohydry/anisohydry. The two independent estimates from radar backscatter and VOD show reasonable agreement at low and middle latitudes but diverge at high latitudes. Grasslands, croplands, wetlands, and open shrublands are more anisohydric, whereas evergreen broadleaf and deciduous broadleaf forests are more isohydric. The direct validation with upscaled in situ species isohydry/anisohydry estimates indicates that the VOD‐based estimates have much better agreement than the backscatter‐based estimates. The indirect validation with prior knowledge suggests that both estimates are generally consistent in that vegetation water status of anisohydric ecosystems more closely tracks environmental fluctuations of water availability and demand than their isohydric counterparts. However, uncertainties still exist in the isohydry/anisohydry estimate, primarily arising from the remote sensing data and, to a lesser extent, from the methodology. The comprehensive assessment in this study can help us better understand the robustness, limitation, and uncertainties of the satellite‐derived isohydry/anisohydry estimates. The ecosystem isohydry/anisohydry has the potential to reveal new insights into spatiotemporal ecosystem response to droughts. [ABSTRACT FROM AUTHOR]