Estimation of biophysical parameters in boreal forests from ERS and JERS SAR interferometry

The thesis describes investigations concerning the evaluation of ERS and JERS SAR images and repeat-pass interferometric SAR images for the retrieval of biophysical parameters in boreal forests. The availability of extensive data sets of images over several test sites located in Sweden, Finland and Siberia has allowed analysis of temporal dynamics of ERS and JERS backscatter and coherence, and of ERS interferometric phase. Modelling of backscatter, coherence and InSAR phase has been performed by means of the Water Cloud Model (WCM) and the Interferometric Water Cloud Model (IWCM); sensitivity analysis and implications for the retrieval of forest biophysical parameters have been thoroughly discussed. Model inversion has been carried out for stem volume retrieval using ERS coherence, ERS backscatter and JERS backscatter, whereas for tree height estimation the ERS interferometric phase has been used. Multi-temporal combination of ERS coherence images, and to a lesser extent of JERS backscatter images, can provide stem volume estimates comparable to stand-wise ground-based measurements. Since the information content of the interferometric phase is strongly degraded by phase noise and uncorrected atmospheric artefacts, the retrieved tree height shows large errors

Temporal Characteristics of Boreal Forest Radar Measurements

Radar observations of forests are sensitive to seasonal changes, meteorological variables and variations in soil and tree water content. These phenomena cause temporal variations in radar measurements, limiting the accuracy of tree height and biomass estimates using radar data. The temporal characteristics of radar measurements of forests, especially boreal forests, are not well understood. To fill this knowledge gap, a tower-based radar experiment was established for studying temporal variations in radar measurements of a boreal forest site in southern Sweden. The work in this thesis involves the design and implementation of the experiment and the analysis of data acquired. The instrument allowed radar signatures from the forest to be monitored over timescales ranging from less than a second to years. A purpose-built, 50 m high tower was equipped with 30 antennas for tomographic imaging at microwave frequencies of P-band (420-450 MHz), L-band (1240-1375 MHz) and C-band (5250-5570 MHz) for multiple polarisation combinations. Parallel measurements using a 20-port vector network analyser resulted in significantly shorter measurement times and better tomographic image quality than previous tower-based radars. A new method was developed for suppressing mutual antenna coupling without affecting the range resolution. Algorithms were developed for compensating for phase errors using an array radar and for correcting for pixel-variant impulse responses in tomographic images. Time series results showed large freeze/thaw backscatter variations due to freezing moisture in trees. P-band canopy backscatter variations of up to 10 dB occurred near instantaneously as the air temperature crossed 0⁰C, with ground backscatter responding over longer timescales. During nonfrozen conditions, the canopy backscatter was very stable with time. Evidence of backscatter variations due to tree water content were observed during hot summer periods only. A high vapour pressure deficit and strong winds increased the rate of transpiration fast enough to reduce the tree water content, which was visible as 0.5-2 dB backscatter drops during the day. Ground backscatter for cross-polarised observations increased during strong winds due to bending tree stems. Significant temporal decorrelation was only seen at P-band during freezing, thawing and strong winds. Suitable conditions for repeat-pass L-band interferometry were only seen during the summer. C-band temporal coherence was high over timescales of seconds and occasionally for several hours for night-time observations during the summer. Decorrelation coinciding with high transpiration rates was observed at L- and C-band, suggesting sensitivity to tree water dynamics.The observations from this experiment are important for understanding, modelling and mitigating temporal variations in radar observables in forest parameter estimation algorithms. The results also are also useful in the design of spaceborne synthetic aperture radar missions with interferometric and tomographic capabilities. The results motivate the implementation of single-pass interferometric synthetic aperture radars for forest applications at P-, L- and C-band

A Tower-Based Radar Study of Temporal Coherence of a Boreal Forest at P-, L-, and C-Bands and Linear Cross Polarization

Cross-polarized temporal coherence observations of a boreal forest, acquired using a tower-based radar, are presented in this article. Temporal coherence is analyzed with respect to frequency, temporal baseline, time of day of observation, season, meteorological variables, and biophysical variables. During the summer, P- and L-band temporal coherence exhibited diurnal cycles, which appeared to be due to high rates of transpiration and convective winds during the day. During the winter, freeze-thaw cycles and precipitation resulted in decorrelation. At temporal baselines of seconds to hours, a high temporal coherence was observed even at C-band. The best observation times of the day were midnight and dawn. Temporal coherence is the main limitation of accuracy in interferometric and tomographic forest applications. The observations from this experiment will allow for better spaceborne SAR mission designs for forest applications, better temporal decorrelation modeling, and more accurate forest parameter estimation algorithms using interferometric and tomographic SAR data

Remote Sensing of Snow Cover Using Spaceborne SAR: A Review

The importance of snow cover extent (SCE) has been proven to strongly link with various natural phenomenon and human activities; consequently, monitoring snow cover is one the most critical topics in studying and understanding the cryosphere. As snow cover can vary significantly within short time spans and often extends over vast areas, spaceborne remote sensing constitutes an efficient observation technique to track it continuously. However, as optical imagery is limited by cloud cover and polar darkness, synthetic aperture radar (SAR) attracted more attention for its ability to sense day-and-night under any cloud and weather condition. In addition to widely applied backscattering-based method, thanks to the advancements of spaceborne SAR sensors and image processing techniques, many new approaches based on interferometric SAR (InSAR) and polarimetric SAR (PolSAR) have been developed since the launch of ERS-1 in 1991 to monitor snow cover under both dry and wet snow conditions. Critical auxiliary data including DEM, land cover information, and local meteorological data have also been explored to aid the snow cover analysis. This review presents an overview of existing studies and discusses the advantages, constraints, and trajectories of the current developments

Assessment of L-Band SAOCOM InSAR coherence and its comparison with C-Band: A case study over managed forests in Argentina

The objective of this work is to analyze the behavior of short temporal baseline interferomet ric coherence in forested areas for L-band spaceborne SAR data. Hence, an exploratory assessment of the impacts of temporal and spatial baselines on coherence, with emphasis on how these effects vary between SAOCOM-1 L-band and Sentinel-1 C-band data is presented. The interferometric coherence is analyzed according to different imaging parameters. In the case of SAOCOM-1, the impacts of the variation of the incidence angle and the ascending and descending orbits over forested areas are also assessed. Finally, short-term 8-day interferometric coherence maps derived from SAOCOM-1 are especially addressed, since this is the first L-band spaceborne mission that allows us to acquire SAR images with such a short temporal span. The analysis is reported over two forest-production areas in Argentina, one of which is part of the most important region in terms of forest plantations at the national level. In the case of SAOCOM, interferometric configurations are characterized by a lack of control on the spatial baseline, so a zero-baseline orbital tube cannot be guaranteed. Nevertheless, this spatial baseline variability is crucial to exploit volume decorrelation for forest monitoring. The results from this exploratory analysis demonstrates that SAOCOM-1 short temporal baseline interferograms, 8 to 16 days, must be considered in order to mitigate temporal decorrelation effects and to be able to experiment with different spatial baseline configurations, in order to allow appropriate forest monitoring.This research was funded by the project INTERACT PID2020-114623RB-C32 funded by the Spanish MCIN /AEI /10.13039 /501100011033.Peer ReviewedPostprint (published version

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission

Temporal survey of P- A nd L-band polarimetric backscatter in boreal forests

Environmental conditions and seasonal variations affect the backscattered radar signal from a forest. This potentially causes errors in a biomass retrieval scheme using data from the synthetic aperture radar (SAR) data. A better understanding of these effects and the electromagnetic scattering mechanisms in forests is required to improve biomass estimation algorithms for current and upcoming P- A nd L-band SAR missions. In this paper, temporal changes in HH-, VV-, and HV-polarized P- A nd L-band radar backscatter and temporal coherence from a boreal forest site are analyzed in relation to environmental parameters. The radar data were collected from a stand of mature Norway spruce ( Picea abies (L.) Karst.) with an above-ground biomass of approximately 250 tons/ha at intervals of 5 min from January to August 2017 using the BorealScat tower-based scatterometer. It was observed that subzero temperatures during the winters cause large variations (4 to 10 dB) in P- A nd L-band backscatter, for which the HH/VV backscatter ratio offered some mitigation. High wind speeds were also seen to cause deviations in the average backscatter at P-band due to decreased double-bounce scattering. Severe temporal decorrelation was observed at L-band over timescales of days or more, whereas the P-band temporal coherence remained high (> 0.9) for at least a month neglecting windy periods. Temporal coherence at P-band was highest during night times when wind speeds are low

Interferomeetriline tehisavaradar kui vahend turbaalade pinna dünaamika jälgimiseks

Väitekirja elektrooniline versioon ei sisalda publikatsiooneSood on unikaalsed ökosüsteemid, kus turba ladestumise käigus seotakse pikaajaliselt süsinikku. Üleilmselt on soodes seotud süsiniku kogus, mis võrdub peaaegu poolega hetkel atmosfääris olevast. Tasakaalu süsiniku sidumise ja lendumise vahel mõjutab soodes kõige enam veetase, mistõttu veerežiimi muutudes võivad sood muutuda süsiniku talletajast kasvuhoonegaaside õhku paiskajaks. Tehisavaradar (SAR) on aktiivne mikrolainealas töötav kaugseiresüsteem, mille kasutamine võimaldaks turbaalade ülemaailmset seiret. SAR näeb läbi pilvede, katab korraga suure ala, on hea ruumilise lahutuse ja tiheda ajalise katvusega. Interferomeetriline SAR (InSAR) on uudne meetod, mis võimaldab mõõta maapinna kõrgusmuutusi, tuginedes radarisignaali pool läbitava teekonna pikkusete erinevusele kahest samast kohast, aga eri aegadel tehtud pildi vahel. Tulemuseks on kõrgusmuutuse pilt (interferogramm), kõrvalsaaduseks on koherentsuse pilt, mis kirjeldab võrreldavate piltide ruumimustrite sarnasust. Meetodi kitsaskohaks on suurte kõrgusmuutuste õigesti hindamine. Töö eesmärk oli katsetada InSAR meetodi kasutusvõimaluse piire ja rakendada uusi teadmisi rabade seirel. Uurisin: 1) raba veetaseme mõju koherentsusele; 2) freesturba tootmisega kaasnevat pinna muutuse mõju koherentsusele; 3) InSAR meetodi usaldusväärsust raba pinna kõrguse muutuse hindamisel. Tulemused näitavad, et koherentsustest on kasu soode veerežiimi uurimisel, kuid see ei sobi pinnase niiskuse otseseks mõõtmiseks. Koherentsust saab kasutada turba tootmise seireks, võttes arvesse SAR-ist ja turba tootmise protsessist tulenevaid piiranguid. Töös on visandatud seiremetoodika, mis võimaldab eristada aktiivseid turbatootmisalasid kasutuses välja jäänud aladest ja jälgida turba tootmise intensiivsust, edendamaks tõhusamat ressursikasutust. InSAR meetodil maapinna kõrguse mõõtmised tavapärase 5,6 sentimeetrise lainepikkuse juures ei ole rabas usaldusväärsed. Katsetatud InSAR meetodid ei suutnud kiiresti toimuvaid suuri kõrgusmuutusi õigesti hinnata. Sarnaselt varasematele uuringutele oleks selline viga jäänud avastamata, kui meil poleks võrdluseks olnud maapealseid kõrgusandmeid. Tõenäoliselt võiks soos maapinna kõrguse muutuse hindamiseks paremini sobida lähitulevikku planeeritud pikalainelised (24 cm) radarsatelliidi missioonid.  Peatlands are significant in regard to climate change because peatlands may switch from being a net carbon sink to an emitter of greenhouse gases. The delicate carbon balance in peatlands is controlled by the peatland water table. Peatland soils contain globally nearly as much carbon as a half of what is currently in the atmosphere. Synthetic Aperture Radar (SAR) is an active microwave remote sensing system which has potential for global peatland monitoring. SAR can penetrate through clouds, covers simultaneously a vast area at high spatial resolution and has a short revisit cycle. Interferometric SAR (InSAR) is an emerging technique to measure surface height changes utilising the difference in the path length that the signal travels between SAR acquisitions of the same target from the same orbital position at different times. The resultant deformation image does not show the absolute change in the path length but the result is ambiguously wrapped in cycles corresponding to half of the signal wavelength, complicating estimation of larger changes. A co-product of InSAR processing is the coherence image, describing the similarity of the spatial patterns in the images. The objective of my dissertation is testing the limits of InSAR and, built on it, improving peatland monitoring. It was studied: 1) coherence response to the water table in raised bogs; 2) coherence response to peat surface alteration caused by the milled peat production; 3) reliability of InSAR deformation estimates in open bogs. Based on the results, coherence could be used as aid to understanding of hydrologic conditions in bogs but it is unsuitable for direct moisture retrieval. Coherence can be used to monitor peat extraction, considering intrinsic limitations posed by the SAR and the peat extraction process. The ambiguity problem makes displacement measurements at the conventional 5.6 cm wavelength unreliable in bogs. A solution could be the planned long wavelength (24 cm) SAR missions.https://www.ester.ee/record=b550580

4D Characterization of Short- and Long-term Height-varying Decorrelated Forest SAR Backscattering

Pol-InSAR and 3D multibaseline SAR Tomography (Tomo-SAR) can extract rich information on complex scenarios with multiple scatterers mapped in the SAR cell, in particular for forest remote sensing. However, forest scenarios are characterized by a temporal decorrelating volume canopy scatterer, and a set of related open problems exists, in particular for Tomo-SAR techniques to be applied to spaceborne monitoring of biomass. Multipass 4D Differential Tomography (Diff-Tomo) is a promising advancement, furnishing space (height)-time signatures of multiple scatterer dynamics in the SAR cell, originally with urban applications. In this paper, to better characterize forest decorrelation phenomena impacting Tomo-SAR/Pol-InSAR, experimental results are presented of the extension of Diff-Tomo methods for analyzing vegetated scenes, to extract jointly geometric and dynamic information of forest layers, at both the long and short time scale. The Diff-Tomo enabled functionality of separation in the height dimension of different temporal coherence levels (“coherence profilingâ€) that are mixed (undiscriminated) in classical total coherence analyses is extensively applied to airborne P-band multipolarimetric data, and results of this investigation are shown. Also, first ground-based radar results are presented of an innovative profiling along the height dimension of the short-term coherence, in particular aiming to characterize the magnitudes of short-term coherence times. Their expected variability along the tree structures is confirmed for the first time

Land cover and forest mapping in boreal zone using polarimetric and interferometric SAR data

Remote sensing offers a wide range of instruments suitable to meet the growing need for consistent, timely and cost-effective monitoring of land cover and forested areas. One of the most important instruments is synthetic aperture radar (SAR) technology, where transfer of advanced SAR imaging techniques from mostly experimental small test-area studies to satellites enables improvements in remote assessment of land cover on a global scale. Globally, forests are very suitable for remote sensing applications due to their large dimensions and relatively poor accessibility in distant areas. In this thesis, several methods were developed utilizing Earth observation data collected using such advanced SAR techniques, as well as their application potential was assessed. The focus was on use of SAR polarimetry and SAR interferometry to improve performance and robustness in assessment of land cover and forest properties in the boreal zone. Particular advances were achieved in land cover classification and estimating several key forest variables, such as forest stem volume and forest tree height. Important results reported in this thesis include: improved polarimetric SAR model-based decomposition approach suitable for use in boreal forest at L-band; development and demonstration of normalization method for fully polarimetric SAR mosaics, resulting in improved classification performance and suitable for wide-area mapping purposes; establishing new inversion procedure for robust forest stem volume retrieval from SAR data; developing semi-empirical method and demonstrating potential for soil type separation (mineral soil, peatland) under forested areas with L-band polarimetric SAR; developing and demonstrating methodology for simultaneous retrieval of forest tree height and radiowave attenuation in forest layer from inter-ferometric SAR data, resulting in improved accuracy and more stable estimation of forest tree height