Raab, Christoph

[["dc.bibliographiccitation.firstpage","901"],["dc.bibliographiccitation.lastpage","903"],["dc.bibliographiccitation.seriesnr","23"],["dc.contributor.author","Raab, C."],["dc.contributor.author","Riesch, F."],["dc.contributor.author","Tonn, B."],["dc.contributor.author","Meißner, M."],["dc.contributor.author","Balkenhol, N."],["dc.contributor.author","Isselstein, J."],["dc.contributor.editor","Horan, B."],["dc.contributor.editor","Hennessy, D."],["dc.contributor.editor","O’Donovan, M."],["dc.contributor.editor","Kennedy, E."],["dc.contributor.editor","McCarthy, B."],["dc.contributor.editor","Finn, J. A."],["dc.contributor.editor","O’Brien, B."],["dc.date.accessioned","2018-12-03T13:06:43Z"],["dc.date.available","2018-12-03T13:06:43Z"],["dc.date.issued","2018"],["dc.description.abstract","Spatially explicit mapping of grassland forage quality is of major interest for sustainable grazing management of NATURA 2000 areas, especially if those are large or have limited accessibility. Therefore, this study is concerned with the estimation of crude protein (CP) and organic acid detergent fiber (oADF) content at regional scale using Sentinel-2 and Landsat 8 remote sensing data. Field data were collected in the Grafenwoehr military training area in Bavaria, Germany. Different combinations of predictor variables were applied using cross-validated random forest regression, linear regression with lasso penalty and linear regression with ridge penalty models. The red-edge band of Sentinel-2, centered at 705 nm, as well as the shortwave infrared bands of both sensors and related vegetation indices contributed the most to the respective models. Linear regression with lasso penalty and Sentinel-2 data performed consistently better, compared to the other models. The results (CP (10.1 - 23.1%): max R2 0.53, RMSE 1.78%; oADF (22.7 - 39.5%): max R2 0.72, RMSE 2.3%) demonstrate the potential of remote sensing as an information tool in supporting the conservation management of grassland areas with limited access."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/57015"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","EGF"],["dc.publisher.place","Ireland"],["dc.relation.conference","27th General Meeting of the European Grassland Federation"],["dc.relation.crisseries","Grassland Science in Europe"],["dc.relation.eventend","2018-06-21"],["dc.relation.eventlocation","Cork, Ireland"],["dc.relation.eventstart","2018-06-17"],["dc.relation.isbn","978-1-84170-643-6"],["dc.relation.isbn","978-1-84170-644-3"],["dc.relation.ispartof","Sustainable meat and milk production from grasslands"],["dc.relation.ispartofseries","Grassland Science in Europe;23"],["dc.relation.orgunit","Abteilung Wildtierwissenschaften"],["dc.title","Methods for spatially explicit estimation of NATURA 2000 grassland forage quality using satellites"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","381"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Remote Sensing in Ecology and Conservation"],["dc.bibliographiccitation.lastpage","398"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Raab, Christoph"],["dc.contributor.author","Riesch, Friederike"],["dc.contributor.author","Tonn, Bettina"],["dc.contributor.author","Barrett, Brian"],["dc.contributor.author","Meißner, Marcus"],["dc.contributor.author","Balkenhol, Niko"],["dc.contributor.author","Isselstein, Johannes"],["dc.contributor.editor","He, Kate"],["dc.contributor.editor","Wegmann, Martin"],["dc.date.accessioned","2021-04-14T08:27:14Z"],["dc.date.available","2021-04-14T08:27:14Z"],["dc.date.issued","2020"],["dc.description.abstract","Abstract Semi‐natural grasslands represent ecosystems with high biodiversity. Their conservation depends on the removal of biomass, for example, through grazing by livestock or wildlife. For this, spatially explicit information about grassland forage quantity and quality is a prerequisite for efficient management. The recent advancements of the Sentinel satellite mission offer new possibilities to support the conservation of semi‐natural grasslands. In this study, the combined use of radar (Sentinel‐1) and multispectral (Sentinel‐2) data to predict forage quantity and quality indicators of semi‐natural grassland in Germany was investigated. Field data for organic acid detergent fibre concentration (oADF), crude protein concentration (CP), compressed sward height (CSH) and standing biomass dry weight (DM) collected between 2015 and 2017 were related to remote sensing data using the random forest regression algorithm. In total, 102 optical‐ and radar‐based predictor variables were used to derive an optimized dataset, maximizing the predictive power of the respective model. High R2 values were obtained for the grassland quality indicators oADF (R2 = 0.79, RMSE = 2.29%) and CP (R2 = 0.72, RMSE = 1.70%) using 15 and 8 predictor variables respectively. Lower R2 values were achieved for the quantity indicators CSH (R2 = 0.60, RMSE = 2.77 cm) and DM (R2 = 0.45, RMSE = 90.84 g/m²). A permutation‐based variable importance measure indicated a strong contribution of simple ratio‐based optical indices to the model performance. In particular, the ratios between the narrow near‐infrared and red‐edge region were among the most important variables. The model performance for oADF, CP and CSH was only marginally increased by adding Sentinel‐1 data. For DM, no positive effect on the model performance was observed by combining Sentinel‐1 and Sentinel‐2 data. Thus, optical Sentinel‐2 data might be sufficient to accurately predict forage quality, and to some extent also quantity indicators of semi‐natural grassland."],["dc.description.abstract","Radar (Sentinel‐1) and multispectral (Sentinel‐2) data were evaluated for mapping semi‐natural grassland forage quantity and quality indicators in Germany. The predictor dataset was optimized using permutation‐based variable importance, maximizing the predictive power of the random forest regression models. Simple ratios between the narrow near‐infrared and red‐edge region were among the most important variables. The model performance was only marginally increased by including Sentinel‐1 data. image"],["dc.description.sponsorship","Landwirtschaftliche Rentenbank"],["dc.identifier.doi","10.1002/rse2.149"],["dc.identifier.eissn","2056-3485"],["dc.identifier.issn","2056-3485"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17449"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82214"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.notes.intern","Merged from goescholar"],["dc.relation.eissn","2056-3485"],["dc.relation.issn","2056-3485"],["dc.relation.orgunit","Zentrum für Biodiversität und Nachhaltige Landnutzung"],["dc.relation.orgunit","Abteilung Wildtierwissenschaften"],["dc.rights","CC BY-NC 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by-nc/4.0/"],["dc.title","Target‐oriented habitat and wildlife management: estimating forage quantity and quality of semi‐natural grasslands with Sentinel‐1 and Sentinel‐2 data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Raab, C."],["dc.contributor.author","Tonn, B."],["dc.contributor.author","Meißner, M."],["dc.contributor.author","Isselstein, J."],["dc.date.accessioned","2019-07-31T07:21:49Z"],["dc.date.available","2019-07-31T07:21:49Z"],["dc.date.issued","2016"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62224"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.relation.conference","8. Rotwildsymposium - Der Hirsch als Naturschützer"],["dc.relation.eventend","2016-07-09"],["dc.relation.eventlocation","Kurhaus Casino, Baden-Baden, Germany"],["dc.relation.eventstart","2016-07-07"],["dc.relation.iserratumof","yes"],["dc.title","Erhalt von Offenlandschaften – wildlebende Rothirsche als Landschaftpfleger – Vegetation und Fernerkundung"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Meißner, M."],["dc.contributor.author","Raab, C."],["dc.contributor.author","Richter, L."],["dc.contributor.author","Riesch, F."],["dc.date.accessioned","2019-07-31T07:25:18Z"],["dc.date.available","2019-07-31T07:25:18Z"],["dc.date.issued","2016"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62225"],["dc.language.iso","de"],["dc.relation.conference","8. Rotwildsymposium - Der Hirsch als Naturschützer"],["dc.relation.date","2016-07"],["dc.relation.eventlocation","Kurhaus Casino, Baden-Baden, Germany"],["dc.title","Erhalt von Offenlandschaften durch zielgerichtetes Flächen- und Wildtiermanagement - wildlebende Rothirsche als Landschaftspfleger"],["dc.type","lecture"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","5638"],["dc.bibliographiccitation.issue","17"],["dc.bibliographiccitation.journal","International Journal of Remote Sensing"],["dc.bibliographiccitation.lastpage","5659"],["dc.bibliographiccitation.volume","39"],["dc.contributor.author","Raab, Christoph"],["dc.contributor.author","Stroh, H. G."],["dc.contributor.author","Tonn, B."],["dc.contributor.author","Meißner, M."],["dc.contributor.author","Rohwer, N."],["dc.contributor.author","Balkenhol, N."],["dc.contributor.author","Isselstein, J."],["dc.date.accessioned","2018-11-29T14:13:08Z"],["dc.date.available","2018-11-29T14:13:08Z"],["dc.date.issued","2018"],["dc.description.abstract","Mapping semi-natural grassland has become increasingly important with regard to climate variability, invasive species, and the intensification of land use. At the same time, adequate field data collection is of pivotal importance for national and international reporting obligations, such as the European Habitats Directive. We present a remote-sensing-based monitoring framework for a Natura 2000 site with a heterogeneous composition of different grassland communities, using the Random Forest algorithm. Automated training data selection was successfully implemented based on the Random Forest proximity measure (Overall Accuracy ranging from 77.5–86.5%). RapidEye acquisitions originating from the onset of vegetation (prespring and first spring) and senescence (late summer and first autumn) were identified as important phenological phases for mapping semi-natural grassland communities. The derived probability maps of occurrences for each grassland class captured transitions between grassland communities and are therefore a better approximation of real-world conditions compared to classical, discrete maps."],["dc.identifier.doi","10.1080/01431161.2018.1504344"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/57003"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.orgunit","Zentrum für Biodiversität und Nachhaltige Landnutzung"],["dc.relation.orgunit","Abteilung Wildtierwissenschaften"],["dc.title","Mapping semi-natural grassland communities using multi-temporal RapidEye remote sensing data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.contributor.author","Raab, C."],["dc.contributor.author","Stroh, H.-G."],["dc.contributor.author","Tonn, B."],["dc.contributor.author","Meißner, M."],["dc.contributor.author","Rohwer, N."],["dc.contributor.author","Balkenhol, N."],["dc.contributor.author","Isselstein, J."],["dc.date.accessioned","2019-07-31T07:13:33Z"],["dc.date.available","2019-07-31T07:13:33Z"],["dc.date.issued","2018"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62222"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.relation.conference","10th International Conference on Ecological Informatics"],["dc.relation.eventend","2018-09-28"],["dc.relation.eventlocation","Jena"],["dc.relation.eventstart","2018-09-24"],["dc.relation.iserratumof","yes"],["dc.title","Using multi-temporal RapidEye remote sensing data to map semi-natural grassland communities"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","99"],["dc.bibliographiccitation.journal","Basic and Applied Ecology"],["dc.bibliographiccitation.lastpage","109"],["dc.bibliographiccitation.volume","43"],["dc.contributor.author","Richter, Laura"],["dc.contributor.author","Balkenhol, Niko"],["dc.contributor.author","Raab, Christoph"],["dc.contributor.author","Reinecke, Horst"],["dc.contributor.author","Meißner, Marcus"],["dc.contributor.author","Herzog, Sven"],["dc.contributor.author","Isselstein, Johannes"],["dc.contributor.author","Signer, Johannes"],["dc.date.accessioned","2020-12-10T14:22:33Z"],["dc.date.available","2020-12-10T14:22:33Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1016/j.baae.2020.02.002"],["dc.identifier.issn","1439-1791"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71647"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Zentrum für Biodiversität und Nachhaltige Landnutzung"],["dc.relation.orgunit","Abteilung Wildtierwissenschaften"],["dc.title","So close and yet so different: The importance of considering temporal dynamics to understand habitat selection"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"],["local.message.claim","2021-10-06T08:18:57.112+0000|||rp114797|||submit_approve|||dc_contributor_author|||None"]]