Schlund, Michael

[["dc.bibliographiccitation.firstpage","3947"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Global Change Biology"],["dc.bibliographiccitation.lastpage","3964"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Wedeux, Béatrice"],["dc.contributor.author","Dalponte, Michele"],["dc.contributor.author","Schlund, Michael"],["dc.contributor.author","Hagen, Stephen"],["dc.contributor.author","Cochrane, Mark"],["dc.contributor.author","Graham, Laura"],["dc.contributor.author","Usup, Aswin"],["dc.contributor.author","Thomas, Andri"],["dc.contributor.author","Coomes, David"],["dc.date.accessioned","2021-04-14T08:26:36Z"],["dc.date.available","2021-04-14T08:26:36Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1111/gcb.15108"],["dc.identifier.eissn","1365-2486"],["dc.identifier.issn","1354-1013"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82009"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1365-2486"],["dc.relation.issn","1354-1013"],["dc.title","Dynamics of a human‐modified tropical peat swamp forest revealed by repeat lidar surveys"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","111814"],["dc.bibliographiccitation.journal","Remote Sensing of Environment"],["dc.bibliographiccitation.volume","246"],["dc.contributor.author","Schlund, Michael"],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2020-05-11T13:20:54Z"],["dc.date.available","2020-05-11T13:20:54Z"],["dc.date.issued","2020"],["dc.description.abstract","The potential of time series metrics based on optical sensors for monitoring of crops and their phenological stages has long been recognized. SAR (synthetic aperture radar) sensors such as Sentinel-1 can provide dense time series, but their potential for retrieving time series metrics is to date underexplored. The backscatter coefficient in VH (vertical-horizontal) and VV (vertical-vertical) polarization as well as the interferometric coherence of Sentinel-1 was retrieved in a German agricultural area in order to obtain a time series with a temporal resolution of 6 days. The backscatter coefficient ratio of VH and VV polarization was also calculated. Local extrema and breakpoints were detected in the locally smoothed time series data in wheat fields for the years 2017, 2018 and 2019. Breakpoints in the VH/VV ratio time series have high potential for detecting the date of shooting and harvesting of the studied wheat fields. The root mean squared differences between detected date and in situ observed date were 4.6 days in 2017, 5.3 days in 2018 and 9.5 days in 2019 for the shooting and 5.1 days in 2017, 8.2 days in 2018 and 10.4 days in 2019 for the harvest. Ripeness stages could not be detected with a high degree of accuracy. The results suggest that the VH/VV ratio has a high potential for monitoring the phenological stages of wheat fields, which can be used for large-scale crop productivity monitoring and risk assessment in agricultural cropping systems."],["dc.identifier.doi","10.1016/j.rse.2020.111814"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65034"],["dc.language.iso","en"],["dc.relation.issn","0034-4257"],["dc.title","Sentinel-1 time series data for monitoring the phenology of winter wheat"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","367"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","IEEE Geoscience and Remote Sensing Letters"],["dc.bibliographiccitation.lastpage","371"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Schlund, Michael"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Scipal, Klaus"],["dc.date.accessioned","2020-12-10T18:26:15Z"],["dc.date.available","2020-12-10T18:26:15Z"],["dc.date.issued","2020"],["dc.description.abstract","The potential of interferometric synthetic aperture radar (InSAR) heights from TanDEM-X for vegetation canopy height and aboveground biomass (AGB) estimation has long been recognized. Penetration of X-band into the canopy affects these estimations. Thus, the canopy height and AGB retrieval from InSAR are typically biased and cannot be compared directly to estimates from other data sources. The objective of this letter was to apply a penetration depth model to compensate for height biases in TanDEM-X InSAR heights. The resulting canopy height estimates are subsequently converted to AGB estimates using regression models. The uncorrected InSAR heights of the forest canopy are biased due to the penetration of the signal into the canopy and differ substantially to light detection and ranging (LiDAR) canopy height estimates. The application of the penetration depth compensation results in unbiased forest canopy height estimates and AGB regression models that are comparable between InSAR and LiDAR. These results indicate that TanDEM-X InSAR and LiDAR technologies can be used to estimate AGB in complex tropical forests suggesting a synergistic use of these fundamentally different observation concepts."],["dc.identifier.doi","10.1109/LGRS.2019.2925901"],["dc.identifier.eissn","1558-0571"],["dc.identifier.issn","1545-598X"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76009"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.eissn","1558-0571"],["dc.relation.issn","1545-598X"],["dc.title","Comparison of Aboveground Biomass Estimation From InSAR and LiDAR Canopy Height Models in Tropical Forests"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","232"],["dc.bibliographiccitation.journal","ISPRS Journal of Photogrammetry and Remote Sensing"],["dc.bibliographiccitation.lastpage","241"],["dc.bibliographiccitation.volume","147"],["dc.contributor.author","Schlund, Michael"],["dc.contributor.author","Baron, Daniel"],["dc.contributor.author","Magdon, Paul"],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2018-12-18T11:04:32Z"],["dc.date.accessioned","2020-05-11T13:15:46Z"],["dc.date.available","2018-12-18T11:04:32Z"],["dc.date.available","2020-05-11T13:15:46Z"],["dc.date.issued","2019"],["dc.description.abstract","The potential of X-band interferometric synthetic aperture radar (InSAR) heights (e.g. from the TanDEM-X mission) for vegetation canopy height estimation has long been recognized. However, the penetration of the X-band into the canopy results in a height bias and substantially affects this estimation. The aim of the study was to apply a physical model to compensate the penetration depth (i.e. height bias) in canopy height estimation and evaluate its performance. We applied a penetration depth model on different TanDEM-X data in three German forests. This model is based on the volume coherence and imaging geometry of the InSAR acquisitions. We extracted the volume coherence from the TanDEM-X data and retrieved the height bias based on the penetration depth compared to actual surface heights. The modeled height bias was used to compensate the height bias in InSAR heights. The corrected TanDEM-X heights were evaluated with LiDAR data. In general, the penetration depth compensation in the InSAR heights improved the performance compared to the original InSAR heights resulting in elevations with a lower root mean squared error and the mean error decreased to less than 1m with the LiDAR heights used as reference. This suggested that the height bias was accurately modeled for temperate forests, which can be of high relevance when InSAR heights are used for canopy height estimation or used in multi-temporal analysis such as forest growth, degradation and deforestation monitoring."],["dc.identifier.doi","10.1016/j.isprsjprs.2018.11.021"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65010"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.relation.issn","0924-2716"],["dc.title","Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","101904"],["dc.bibliographiccitation.journal","International Journal of Applied Earth Observation and Geoinformation"],["dc.bibliographiccitation.volume","82"],["dc.contributor.author","Schlund, Michael"],["dc.contributor.author","Magdon, Paul"],["dc.contributor.author","Eaton, Brian"],["dc.contributor.author","Aumann, Craig"],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2020-05-12T08:30:55Z"],["dc.date.available","2020-05-12T08:30:55Z"],["dc.date.issued","2019"],["dc.description.abstract","Various semi-empirical models for linking PolInSAR data (polarimetric synthetic aperture radar interferometry) to canopy height of vegetation exist. However, only single-polarized data were used during the TanDEM-X mission in order to create a global digital elevation model (DEM). Therefore, simplifications of the semi-empirical models have to be applied to use the PolInSAR models for canopy height estimation with single-polarized TanDEM-X data. We extracted the volume coherence from TanDEM-X acquisitions and used a linear as well as a sinc model for the estimation of canopy height, which are based on the semi-empirical Random Volume over Ground model (RVoG). Both, the linear as well as the sinc model, were applied in temperate forests of Germany and boreal forests of Canada. The estimated canopy height was validated with LiDAR based canopy height models. In general, the sinc model resulted in higher coefficients of determination R2 from 0.08 to 0.64 and lower root mean squared errors (RMSE) between 4.8 m and 12.5 m compared to the linear model with R2 values between 0.08 and 0.62 (RMSE = 5.4 m to 13.5 m). Higher accuracies were generally achieved in winter and with higher height of ambiguity."],["dc.identifier.doi","10.1016/j.jag.2019.101904"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65130"],["dc.language.iso","en"],["dc.relation.issn","0303-2434"],["dc.title","Canopy height estimation with TanDEM-X in temperate and boreal forests"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3538"],["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"],["dc.bibliographiccitation.lastpage","3547"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Schlund, Michael"],["dc.contributor.author","Scipal, Klaus"],["dc.contributor.author","Quegan, Shaun"],["dc.date.accessioned","2020-12-10T18:26:15Z"],["dc.date.available","2020-12-10T18:26:15Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1109/JSTARS.2018.2866868"],["dc.identifier.eissn","2151-1535"],["dc.identifier.issn","1939-1404"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76008"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Assessment of a Power Law Relationship Between P-Band SAR Backscatter and Aboveground Biomass and Its Implications for BIOMASS Mission Performance"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]