JabRef references

Araza A, Herold M, de Bruin S, Ciais P, Gibbs D, Harris N, Santoro M, Wigneron J-P, Yang H, Malaga N, Nesha K, Rodriguez-Veiga P, Brovkina O, Brown H, Chanev M, Dimitrov Z, Filchev L, Fridman J, Garcia M, Gikov A, Govaere L, Dimitrov P, Moradi F, Muelbert A, Novotny J, Pugh T, Schelhaas M-J, Schepaschenko D, Sterenczak K and Hein L (2023), "Past decade above-ground biomass change comparisons from four multi-temporal global maps", International Journal of Applied Earth Observation and Geoinformation. Vol. 118 Elsevier B.V..

[Abstract] [BibTeX] [DOI]

Abstract: Above-ground biomass (AGB) is considered an essential climate variable that underpins our knowledge and information about the role of forests in mitigating climate change. The availability of satellite-based AGB and AGB change (AGB) products has increased in recent years. Here we assessed the past decade net AGB derived from four recent global multi-date AGB maps: ESA-CCI maps, WRI-Flux model, JPL time series, and SMOS-LVOD time series. Our assessments explore and use different reference data sources with biomass re-measurements within the past decade. The reference data comprise National Forest Inventory (NFI) plot data, local AGB maps from airborne LiDAR, and selected Forest Resource Assessment country data from countries with well-developed monitoring capacities. Map to reference data comparisons were performed at levels ranging from 100 m to 25 km spatial scale. The comparisons revealed that LiDAR data compared most reasonably with the maps, while the comparisons using NFI only showed some agreements at aggregation levels <10 km. Regardless of the aggregation level, AGB losses and gains according to the map comparisons were consistently smaller than the reference data. Map-map comparisons at 25 km highlighted that the maps consistently captured AGB losses in known deforestation hotspots. The comparisons also identified several carbon sink regions consistently detected by all maps. However, disagreement between maps is still large in key forest regions such as the Amazon basin. The overall AGB map cross-correlation between maps varied in the range 0.11 0.29 (r). Reported AGB magnitudes were largest in the high-resolution datasets including the CCI map differencing (stock change) and Flux model (gain-loss) methods, while they were smallest according to the coarser-resolution LVOD and JPL time series products, especially for AGB gains. Our results suggest that AGB assessed from current maps can be biased and any use of the estimates should take that into account. Currently, AGB reference data are sparse especially in the tropics but that deficit can be alleviated by upcoming LiDAR data networks in the context of Supersites and GEO-Trees.

BibTeX:

@article{Araza2023,
  author = {Araza, A. and Herold, M. and de Bruin, S. and Ciais, P. and Gibbs, D.A. and Harris, N. and Santoro, M. and Wigneron, J.-P. and Yang, H. and Malaga, N. and Nesha, K. and Rodriguez-Veiga, P. and Brovkina, O. and Brown, H.C.A. and Chanev, M. and Dimitrov, Z. and Filchev, L. and Fridman, J. and Garcia, M. and Gikov, A. and Govaere, L. and Dimitrov, P. and Moradi, F. and Muelbert, A.E. and Novotny, J. and Pugh, T.A.M. and Schelhaas, M.-J. and Schepaschenko, D. and Sterenczak, K. and Hein, L.},
  title = {Past decade above-ground biomass change comparisons from four multi-temporal global maps},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  publisher = {Elsevier B.V.},
  year = {2023},
  volume = {118},
  doi = {10.1016/j.jag.2023.103274}
}

Bartsch A, Strozzi T and Nitze I (2023), "Permafrost Monitoring from Space", Surveys in Geophysics. Vol. 44(5), pp. 1579-1613. Springer Science and Business Media B.V..

[Abstract] [BibTeX] [DOI]

Abstract: Permafrost is a sub-ground phenomenon and therefore cannot be directly observed from space. It is an Essential Climate Variable and associated with climate tipping points. Multi-annual time series of permafrost ground temperatures can be, however, derived through modelling of the heat transfer between atmosphere and ground using landsurface temperature, snow- and landcover observations from space. Results show that the northern hemisphere permafrost ground temperatures have increased on average by about one degree Celsius since 2000. This is in line with trends of permafrost proxies observable from space: surface water extent has been decreasing across the Arctic; the landsurface is subsiding continuously in some regions indicating ground ice melt; hot summers triggered increased subsidence as well as thaw slumps; rock glaciers are accelerating in some mountain regions. The applicability of satellite data for permafrost proxy monitoring has been demonstrated mostly on a local to regional scale only. There is still a lack of consistency of acquisitions and of very high spatial resolution observations. Both are needed for implementation of circumpolar monitoring of lowland permafrost. In order to quantify the impacts of permafrost thaw on the carbon cycle, advancement in wetland and atmospheric greenhouse gas concentration monitoring from space is needed. Â© 2023, The Author(s).

BibTeX:

@article{Bartsch20231579,
  author = {Bartsch, A. and Strozzi, T. and Nitze, I.},
  title = {Permafrost Monitoring from Space},
  journal = {Surveys in Geophysics},
  publisher = {Springer Science and Business Media B.V.},
  year = {2023},
  volume = {44},
  number = {5},
  pages = {1579-1613},
  doi = {10.1007/s10712-023-09770-3}
}

Bernhard P, Haener D and Frey O (2023), "Persistent Scatterer Interferometry to Detect Railway Track Anomalies using TerraSAR-X Observations", In Proc. IEEE Int. Geosci. Remote Sens. Symp.. , pp. 1838-1841. IEEE.

[Abstract] [BibTeX] [DOI]

Abstract: This study investigates the potential of space-borne SyntheticAperture Radar Interferometry for efficient detection of trackanomalies using the Swiss Federal Railways (SBB) railway network as an example. The condition of the ballast substructure is crucial for track service life, and moisture accumulation is a primary cause of deterioration and can manifest itself by subsidence. Current operational methods for track condition assessment have limitations, and remote sensing techniques offer a promising alternative. Using a time-series of TerraSAR-X observations, we performed a persistent scatterer interferometry (PSI) analysis to estimate surface deformations and further analysed the deformation rates and variability along a 22 km track section in Switzerland. The study explores the hypothesis that the variability of PSI-derived deformation estimates along the railway track can be related to longitudinal height measurements from track geometry vehicles. When compared with chord-based measurements from SBB, our preliminary results showed a promising correlation,suggesting that the variability in deformation measurement scan indeed be linked to longitudinal height measurements obtained from track geometry vehicles. If proven effective, a satellite-based evaluation method could significantly reduce resources required for railway infrastructure maintenance.

BibTeX:

@inproceedings{bernhardHaenerFreyIGARSS2023PSIbasedDetectionOfRailwayTrackAnomalies,
  author = {Bernhard, Philipp and Haener, David and Frey, Othmar},
  title = {Persistent Scatterer Interferometry to Detect Railway Track Anomalies using TerraSAR-X Observations},
  booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
  publisher = {IEEE},
  year = {2023},
  pages = {1838-1841},
  doi = {10.1109/IGARSS52108.2023.10283221}
}

Borlaf-Mena I, Garcia-Duro J, Santoro M, Villard L, Badea O and Tanase M (2023), "Seasonality and directionality effects on radar backscatter are key to identify mountain forest types with Sentinel-1 data", Remote Sensing of Environment. Vol. 296 Elsevier Inc..

[Abstract] [BibTeX] [DOI]

Abstract: Systematic Sentinel-1 acquisitions provide an unprecedented stream of SAR data which allows to describe forest temporal dynamics in detail, a powerful tool for phenological studies and forest type classification. Several studies have explored the temporal variation of backscatter intensity in this context, but none considered that scattering directionality of canopies may vary. Said directionality is related to target-sensor geometry (incidence angle), forest height, and optical depth, associated with leaf dynamics. This study explicitly models backscatter dependance on incidence angle by fitting a regression model for each Sentinel-1 image and forest type. Residuals are accumulated across the time series and used to classify pixels into the most likely forest type using the smallest accumulated residual. This modelling and classification strategy has been applied over a North-South transect across the Carpathian Mountains, including forests with different physiognomies, from deciduous broadleaf forest, to mixed broadleaf-needleleaf and pure perennial needleleaf forests. These forests were classified with increasing detail, assessing the results against in-situ forest stand data and satellite-based land cover classification products (Copernicus Forest type layer). The accuracy of our classification was K > 0.8, OA > 90% when separating broadleaf from needleleaf forest types. The accuracy decreased (K > 0.6, OA > 79%) when also separating mixed forest types. Our results suggest that incorporating directional effects into classification models can improve SAR-based forest classification of temperate forest over mountainous terrain. Furthermore, models fitted between backscatter and incidence angle provide an estimate of n, a parameter related to optical depth that has been shown to vary with leaf dynamics. ncould be used to improve image normalization in studies aiming at the estimation of biomass, or to aid the estimation of fast-changing parameters such as leaf area index or leaf moisture content. Â© 2023 Elsevier Inc.

BibTeX:

@article{Borlaf-Mena2023,
  author = {Borlaf-Mena, I. and Garcia-Duro, J. and Santoro, M. and Villard, L. and Badea, O. and Tanase, M.A.},
  title = {Seasonality and directionality effects on radar backscatter are key to identify mountain forest types with Sentinel-1 data},
  journal = {Remote Sensing of Environment},
  publisher = {Elsevier Inc.},
  year = {2023},
  volume = {296},
  doi = {10.1016/j.rse.2023.113728}
}

Brun F, King O, Reveillet M, Amory C, Planchot A, Berthier E, Dehecq A, Bolch T, Fourteau K, Brondex J, Dumont M, Mayer C, Leinss S, Hugonnet R and Wagnon P (2023), "Everest South Col Glacier did not thin during the period 1984-2017", Cryosphere. Vol. 17(8), pp. 3251-3268. Copernicus Publications.

[Abstract] [BibTeX] [DOI]

Abstract: The South Col Glacier is a small body of ice and snow (approx. 0.2Äâ¬Â¯km2) located at the very high elevation of 8000Äâ¬Â¯mÄâ¬Â¯a.s.l. (above sea level) on the southern ridge of Mt. Everest. A recent study by proposed that South Col Glacier is rapidly losing mass. This is in contradiction to our comparison of two digital elevation models derived from aerial photographs taken in December 1984 and a stereo PlÃ©iades satellite acquisition from March 2017, from which we estimate a mean elevation change of 0.01Äâ¬Â¯Â±Äâ¬Â¯0.05Äâ¬Â¯mÄâ¬Â¯a-1. To reconcile these results, we investigate some aspects of the surface energy and mass balance of South Col Glacier. From satellite images and a simple model of snow compaction and erosion, we show that wind erosion has a major impact on the surface mass balance due to the strong seasonality in precipitation and wind and that it cannot be neglected. Additionally, we show that the melt amount predicted by a surface energy and mass balance model is very sensitive to the model structure and implementation. Contrary to previous findings, melt is likely not a dominant ablation process on this glacier, which remains mostly snow-covered during the monsoon. Â© Copyright:

BibTeX:

@article{Brun20233251,
  author = {Brun, F. and King, O. and Reveillet, M. and Amory, C. and Planchot, A. and Berthier, E. and Dehecq, A. and Bolch, T. and Fourteau, K. and Brondex, J. and Dumont, M. and Mayer, C. and Leinss, S. and Hugonnet, R. and Wagnon, P.},
  title = {Everest South Col Glacier did not thin during the period 1984-2017},
  journal = {Cryosphere},
  publisher = {Copernicus Publications},
  year = {2023},
  volume = {17},
  number = {8},
  pages = {3251-3268},
  doi = {10.5194/tc-17-3251-2023}
}

Deeb EJ, Meehan TG, O'Neel S, Keskinen Z, Werner C, Forster R, Frey O and LeWinter A (2023), "Investigations of ground-based mobile L-band InSAR phase response to the application of soil moisture on a high-desert grassland", In Proc. IEEE Int. Geosci. Remote Sens. Symp.. Pasadena, July, 2023. , pp. 2691-2692. IEEE.

[Abstract] [BibTeX] [DOI]

Abstract: In an agricultural river valley in central Idaho, USA, weconducted a case study to investigate interferometric synthetic aperture (InSAR) coherence and phase response as an indication of soil moisture change. Throughout a 3-day observational campaign, repeated observations were acquired from a mobile vehicle with a multi-polarization L-band (1.6GHz) InSAR system, first prior to controlled irrigation and then during a dry-out period. Here, we present results that show the time series of coherence and phase in coordination with in-situ soil moisture observations at two depths over the three days of the controlled experiment. During the subsequent dry out period, the time series of interferometric coherence shows an immediate degradation of the signal with a subsequent improvement. The in-situ soil moisture observations highlight this transition of controlled irrigation to subsequent drying out of the soils. We anticipate future work to include investigation of the interferometric times series of phase change as it relates to quantitative changes in soil moisture.

BibTeX:

@inproceedings{deebEtAl2023CarborneLBandSARSoilMoisture,
  author = {Deeb, Elias J. and Meehan, Tate G. and O'Neel, Shad and Keskinen, Zachary and Werner, Charles and Forster, Richard and Frey, Othmar and LeWinter, Adam},
  title = {Investigations of ground-based mobile L-band InSAR phase response to the application of soil moisture on a high-desert grassland},
  booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
  publisher = {IEEE},
  year = {2023},
  pages = {2691-2692},
  doi = {10.1109/IGARSS52108.2023.10282878}
}

Fan N, Santoro M, Besnard S, Cartus O, Koirala S and Carvalhais N (2023), "Implications of the steady-state assumption for the global vegetation carbon turnover", Environmental Research Letters. Vol. 18(10) Institute of Physics.

[Abstract] [BibTeX] [DOI]

Abstract: Vegetation carbon turnover time (Ï) is a central ecosystem property to quantify the global vegetation carbon dynamics. However, our understanding of vegetation dynamics is hampered by the lack of long-term observations of the changes in vegetation biomass. Here we challenge the steady state assumption of Ï by using annual changes in vegetation biomass that derived from remote-sensing observations. We evaluate the changes in magnitude, spatial patterns, and uncertainties in vegetation carbon turnover times from 1992 to 2016. We found the robustness in the steady state assumption for forest ecosystems at large spatial scales, contrasting with local larger differences at the grid cell level between Ï under steady state and Ï under non-steady state conditions. The observation that terrestrial ecosystems are not in a steady state locally is deemed crucial when studying vegetation dynamics and the potential response of biomass to disturbance and climatic changes. Â© 2023 The Author(s). Published by IOP Publishing Ltd

BibTeX:

@article{Fan2023,
  author = {Fan, N. and Santoro, M. and Besnard, S. and Cartus, O. and Koirala, S. and Carvalhais, N.},
  title = {Implications of the steady-state assumption for the global vegetation carbon turnover},
  journal = {Environmental Research Letters},
  publisher = {Institute of Physics},
  year = {2023},
  volume = {18},
  number = {10},
  doi = {10.1088/1748-9326/acfb22}
}

Freihardt J and Frey O (2023), "Assessing riverbank erosion in Bangladesh using time series of Sentinel-1 radar imagery in the Google Earth Engine", Nat. Hazards Earth Syst. Sci.,. Vol. 23, pp. 751-770.