@article{AtaeeMaghsoudiLatifietal.2019,
  author    = {Ataee, Mohammad Sadegh and Maghsoudi, Yasser and Latifi, Hooman and Fadaie, Farhad},
  title     = {Improving estimation accuracy of growing stock by multi-frequency SAR and multi-spectral data over Iran's heterogeneously-structured broadleaf Hyrcanian forests},
  series = {Forests},
  volume    = {10},
  journal   = {Forests},
  number    = {8},
  issn      = {1999-4907},
  doi       = {10.3390/f10080641},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197212},
  year      = {2019},
  abstract  = {Via providing various ecosystem services, the old-growth Hyrcanian forests play a crucial role in the environment and anthropogenic aspects of Iran and beyond. The amount of growing stock volume (GSV) is a forest biophysical parameter with great importance in issues like economy, environmental protection, and adaptation to climate change. Thus, accurate and unbiased estimation of GSV is also crucial to be pursued across the Hyrcanian. Our goal was to investigate the potential of ALOS-2 and Sentinel-1's polarimetric features in combination with Sentinel-2 multi-spectral features for the GSV estimation in a portion of heterogeneously-structured and mountainous Hyrcanian forests. We used five different kernels by the support vector regression (nu-SVR) for the GSV estimation. Because each kernel differently models the parameters, we separately selected features for each kernel by a binary genetic algorithm (GA). We simultaneously optimized R\(^2\) and RMSE in a suggested GA fitness function. We calculated R\(^2\), RMSE to evaluate the models. We additionally calculated the standard deviation of validation metrics to estimate the model's stability. Also for models over-fitting or under-fitting analysis, we used mean difference (MD) index. The results suggested the use of polynomial kernel as the final model. Despite multiple methodical challenges raised from the composition and structure of the study site, we conclude that the combined use of polarimetric features (both dual and full) with spectral bands and indices can improve the GSV estimation over mixed broadleaf forests. This was partially supported by the use of proposed evaluation criterion within the GA, which helped to avoid the curse of dimensionality for the applied SVR and lowest over estimation or under estimation.},
  language  = {en}
}
@article{MayrKuenzerGessneretal.2019,
  author    = {Mayr, Stefan and Kuenzer, Claudia and Gessner, Ursula and Klein, Igor and Rutzinger, Martin},
  title     = {Validation of earth observation time-series: a review for large-area and temporally dense land surface products},
  series = {Remote Sensing},
  volume    = {11},
  journal   = {Remote Sensing},
  number    = {22},
  issn      = {2072-4292},
  doi       = {10.3390/rs11222616},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193202},
  year      = {2019},
  abstract  = {Large-area remote sensing time-series offer unique features for the extensive investigation of our environment. Since various error sources in the acquisition chain of datasets exist, only properly validated results can be of value for research and downstream decision processes. This review presents an overview of validation approaches concerning temporally dense time-series of land surface geo-information products that cover the continental to global scale. Categorization according to utilized validation data revealed that product intercomparisons and comparison to reference data are the conventional validation methods. The reviewed studies are mainly based on optical sensors and orientated towards global coverage, with vegetation-related variables as the focus. Trends indicate an increase in remote sensing-based studies that feature long-term datasets of land surface variables. The hereby corresponding validation efforts show only minor methodological diversification in the past two decades. To sustain comprehensive and standardized validation efforts, the provision of spatiotemporally dense validation data in order to estimate actual differences between measurement and the true state has to be maintained. The promotion of novel approaches can, on the other hand, prove beneficial for various downstream applications, although typically only theoretical uncertainties are provided.},
  language  = {en}
}
@article{AbdullahiWesselHuberetal.2019,
  author    = {Abdullahi, Sahra and Wessel, Birgit and Huber, Martin and Wendleder, Anna and Roth, Achim and Kuenzer, Claudia},
  title     = {Estimating penetration-related X-band InSAR elevation bias: a study over the Greenland ice sheet},
  series = {Remote Sensing},
  volume    = {11},
  journal   = {Remote Sensing},
  number    = {24},
  issn      = {2072-4292},
  doi       = {10.3390/rs11242903},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193902},
  year      = {2019},
  abstract  = {Accelerating melt on the Greenland ice sheet leads to dramatic changes at a global scale. Especially in the last decades, not only the monitoring, but also the quantification of these changes has gained considerably in importance. In this context, Interferometric Synthetic Aperture Radar (InSAR) systems complement existing data sources by their capability to acquire 3D information at high spatial resolution over large areas independent of weather conditions and illumination. However, penetration of the SAR signals into the snow and ice surface leads to a bias in measured height, which has to be corrected to obtain accurate elevation data. Therefore, this study purposes an easy transferable pixel-based approach for X-band penetration-related elevation bias estimation based on single-pass interferometric coherence and backscatter intensity which was performed at two test sites on the Northern Greenland ice sheet. In particular, the penetration bias was estimated using a multiple linear regression model based on TanDEM-X InSAR data and IceBridge laser-altimeter measurements to correct TanDEM-X Digital Elevation Model (DEM) scenes. Validation efforts yielded good agreement between observations and estimations with a coefficient of determination of R\(^2\) = 68\% and an RMSE of 0.68 m. Furthermore, the study demonstrates the benefits of X-band penetration bias estimation within the application context of ice sheet elevation change detection.},
  language  = {en}
}
@article{TrappeKneisel2019,
  author    = {Trappe, Julian and Kneisel, Christof},
  title     = {Geophysical and sedimentological investigations of Peatlands for the assessment of lithology and subsurface water pathways},
  series = {Geosciences},
  volume    = {9},
  journal   = {Geosciences},
  number    = {3},
  doi       = {10.3390/geosciences9030118},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-201699},
  pages     = {118},
  year      = {2019},
  abstract  = {Peatlands located on slopes (herein called slope bogs) are typical landscape units in the Hunsrueck, a low mountain range in Southwestern Germany. The pathways of the water feeding the slope bogs have not yet been documented and analyzed. The identification of the different mechanisms allowing these peatlands to originate and survive requires a better understanding of the subsurface lithology and hydrogeology. Hence, we applied a multi-method approach to two case study sites in order to characterize the subsurface lithology and to image the variable spatio-temporal hydrological conditions. The combination of Electrical Resistivity Tomography (ERT) and an ERT-Monitoring and Ground Penetrating Radar (GPR), in conjunction with direct methods and data (borehole drilling and meteorological data), allowed us to gain deeper insights into the subsurface characteristics and dynamics of the peatlands and their catchment area. The precipitation influences the hydrology of the peatlands as well as the interflow in the subsurface. Especially, the geoelectrical monitoring data, in combination with the precipitation and temperature data, indicate that there are several forces driving the hydrology and hydrogeology of the peatlands. While the water content of the uppermost layers changes with the weather conditions, the bottom layer seems to be more stable and changes to a lesser extent. At the selected case study sites, small differences in subsurface properties can have a huge impact on the subsurface hydrogeology and the water paths. Based on the collected data, conceptual models have been deduced for the two case study sites.},
  language  = {en}
}
@phdthesis{Specht2019,
  author    = {Specht, Sebastian},
  title     = {Stratigraphie und Tektonik im Grossraum Massbach (Lauer) zwischen den Naturparks Bayerische Rh{\"o}n und Hassberge},
  doi       = {10.25972/OPUS-16302},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-163022},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2019},
  abstract  = {Diese Arbeit stellt die Ergebnisse der stratigraphischen und tektonischen Aufnahme des Blattes 5827 Maßbach vor. Sie erfolgte im Rahmen der geologischen Landesaufnahme von Bayern 1:25.000 sowie im Auftrag des Bayerischen Landesamts f{\"u}r Umwelt und beruht auf einer geologischen Detailkartierung im Maßstab 1:10.000. Die wesentlichen Ergebnisse sind folglich in der Geologischen Karte 1:25.000 und in der Strukturkarte 1:50.000 dargestellt. Zur Aufgabenstellung geh{\"o}rten ebenfalls eine moderne Erfassung und Darstellung der Schichtenfolge unter stratigraphischen und faziellen Gesichtspunkten sowie die Aufnahme und Interpretation geologischer Strukturen und deren Einbindung in den regionalen Rahmen (Anlage 7). Dieser Arbeit kommt somit nicht nur akademisches Interesse zu. Vielmehr ist sie auch f{\"u}r angewandte Fachbereiche wesentlich: u.a. f{\"u}r Hydrogeologie, Geothermie oder f{\"u}r Fragen der Raumplanung. Das Kartenblatt 5827 Maßbach liegt im nord{\"o}stlichen Unterfranken im Norden Bayerns. Die n{\"a}chstgr{\"o}ßere Stadt, s{\"u}dlich des Blattgebietes, ist Schweinfurt. Das Gebiet zeigt einen Ausschnitt des s{\"u}dwestdeutschen Schichtstufenlandes innerhalb der S{\"u}dwestdeutschen Großscholle sensu CARL{\´E} (1955). Geomorphologen rechnen es der Hochfl{\"a}che der „Schweinfurter Rh{\"o}n" zu. Ein naturr{\"a}umlicher {\"U}berblick {\"u}ber Geographie, Geologie, Hydrogeologie, Rohstoffgeologie und Bodenkunde sowie ein erdgeschichtlicher Abriss werden im ersten Teil der Arbeit (S. 2-15) gegeben. Die Kartierung erfolgte als Lesesteinkartierung; denn die Aufschlussverh{\"a}ltnisse waren schlecht. Auch existieren nur wenige auswertbare Bohrungen. Vor diesem Hintergrund stellt der zweite Teil der Arbeit die zu Tage ausstreichende mesozoische Schichtenfolge vor (S.16-76). Die Schichtenfolge geh{\"o}rt ausschließlich in die Trias, reicht vom Unteren Muschelkalk bis zum Unteren Gipskeuper und umfasst etwa 270 bis 280 Meter. Hinzu kommen verschiedene quart{\"a}re Sedimente geringer M{\"a}chtigkeit. Der dritte Teil der Arbeit (S. 77-95) befasst sich mit den Lagerungsverh{\"a}ltnissen und der tektonischen Zergliederung des Gebietes. Das tektonische Relief auf Blatt 5827 Maßbach misst etwa 260-270 m. Pr{\"a}gendes Element ist der Kissingen-Haßfurter Sattel, dessen Sattelachse das Blattgebiet von NW nach SE quert. Im SW-Quadranten ist die in S{\"u}dwestdeutschland bedeutsame Kissingen-Haßfurter-St{\"o}rungszone wirksam Im regionalen Rahmen verbinden sich eine Vielzahl von nachgewiesenen tektonischen Elementen zu sich {\"u}berlagernden tektonischen Strukturen. Deren Ausgestaltung verlief mehrphasig und sie erhielten ihre heute bestehende Form wohl durch die Fernwirkung der alpidischen Orogenese. Die Anlage der tektonischen Hauptelemente hingegen reicht wahrscheinlich bis in die ausgehende variszidische Gebirgsbildung zur{\"u}ck. Die zusammen-fassende Analyse und Darstellung der Ergebnisse f{\"u}hrt in dieser Arbeit zur Einarbeitung des Blattes 5827 Maßbach in den regionalen stratigraphischen wie tektonischen Rahmen der umliegenden Bl{\"a}tter der GK 25.},
  subject      = {Geologie},
  language  = {de}
}
@article{ReinermannGessnerAsametal.2019,
  author    = {Reinermann, Sophie and Gessner, Ursula and Asam, Sarah and Kuenzer, Claudia and Dech, Stefan},
  title     = {The Effect of Droughts on Vegetation Condition in Germany: An Analysis Based on Two Decades of Satellite Earth Observation Time Series and Crop Yield Statistics},
  series = {Remote Sensing},
  volume    = {11},
  journal   = {Remote Sensing},
  number    = {15},
  doi       = {10.3390/rs11151783},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-225165},
  pages     = {1783, 1-21},
  year      = {2019},
  abstract  = {Central Europe experienced several droughts in the recent past, such as in the year 2018, which was characterized by extremely low rainfall rates and high temperatures, resulting in substantial agricultural yield losses. Time series of satellite earth observation data enable the characterization of past drought events over large temporal and spatial scales. Within this study, Moderate Resolution Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) (MOD13Q1) 250 m time series were investigated for the vegetation periods of 2000 to 2018. The spatial and temporal development of vegetation in 2018 was compared to other dry and hot years in Europe, like the drought year 2003. Temporal and spatial inter- and intra-annual patterns of EVI anomalies were analyzed for all of Germany and for its cropland, forest, and grassland areas individually. While vegetation development in spring 2018 was above average, the summer months of 2018 showed negative anomalies in a similar magnitude as in 2003, which was particularly apparent within grassland and cropland areas in Germany. In contrast, the year 2003 showed negative anomalies during the entire growing season. The spatial pattern of vegetation status in 2018 showed high regional variation, with north-eastern Germany mainly affected in June, north-western parts in July, and western Germany in August. The temporal pattern of satellite-derived EVI deviances within the study period 2000-2018 were in good agreement with crop yield statistics for Germany. The study shows that the EVI deviation of the summer months of 2018 were among the most extreme in the study period compared to other years. The spatial pattern and temporal development of vegetation condition between the drought years differ.},
  language  = {en}
}
@article{WeigandWurmDechetal.2019,
  author    = {Weigand, Matthias and Wurm, Michael and Dech, Stefan and Taubenb{\"o}ck, Hannes},
  title     = {Remote sensing in environmental justice research—a review},
  series = {ISPRS International Journal of Geo-Information},
  volume    = {8},
  journal   = {ISPRS International Journal of Geo-Information},
  number    = {1},
  issn      = {2220-9964},
  doi       = {10.3390/ijgi8010020},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-196950},
  year      = {2019},
  abstract  = {Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people's physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using "essentially aspatial" data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of 'big earth data' for future environmental justice analyses.},
  language  = {en}
}
@article{KhareLatifiRossietal.2019,
  author    = {Khare, Siddhartha and Latifi, Hooman and Rossi, Sergio and Ghosh, Sanjay Kumar},
  title     = {Fractional cover mapping of invasive plant species by combining very high-resolution stereo and multi-sensor multispectral imageries},
  series = {Forests},
  volume    = {10},
  journal   = {Forests},
  number    = {7},
  issn      = {1999-4907},
  doi       = {10.3390/f10070540},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197250},
  year      = {2019},
  abstract  = {Invasive plant species are major threats to biodiversity. They can be identified and monitored by means of high spatial resolution remote sensing imagery. This study aimed to test the potential of multiple very high-resolution (VHR) optical multispectral and stereo imageries (VHRSI) at spatial resolutions of 1.5 and 5 m to quantify the presence of the invasive lantana (Lantana camara L.) and predict its distribution at large spatial scale using medium-resolution fractional cover analysis. We created initial training data for fractional cover analysis by classifying smaller extent VHR data (SPOT-6 and RapidEye) along with three dimensional (3D) VHRSI derived digital surface model (DSM) datasets. We modelled the statistical relationship between fractional cover and spectral reflectance for a VHR subset of the study area located in the Himalayan region of India, and finally predicted the fractional cover of lantana based on the spectral reflectance of Landsat-8 imagery of a larger spatial extent. We classified SPOT-6 and RapidEye data and used the outputs as training data to create continuous field layers of Landsat-8 imagery. The area outside the overlapping region was predicted by fractional cover analysis due to the larger extent of Landsat-8 imagery compared with VHR datasets. Results showed clear discrimination of understory lantana from upperstory vegetation with 87.38\% (for SPOT-6), and 85.27\% (for RapidEye) overall accuracy due to the presence of additional VHRSI derived DSM information. Independent validation for lantana fractional cover estimated root-mean-square errors (RMSE) of 11.8\% (for RapidEye) and 7.22\% (for SPOT-6), and R\(^2\) values of 0.85 and 0.92 for RapidEye (5 m) and SPOT-6 (1.5 m), respectively. Results suggested an increase in predictive accuracy of lantana within forest areas along with increase in the spatial resolution for the same Landsat-8 imagery. The variance explained at 1.5 m spatial resolution to predict lantana was 64.37\%, whereas it decreased by up to 37.96\% in the case of 5 m spatial resolution data. This study revealed the high potential of combining small extent VHR and VHRSI- derived 3D optical data with larger extent, freely available satellite data for identification and mapping of invasive species in mountainous forests and remote regions.},
  language  = {en}
}
@article{NaeschenDiekkruegerEversetal.2019,
  author    = {N{\"a}schen, Kristian and Diekkr{\"u}ger, Bernd and Evers, Mariele and H{\"o}llermann, Britta and Steinbach, Stefanie and Thonfeld, Frank},
  title     = {The impact of land use/land cover change (LULCC) on water resources in a tropical catchment in Tanzania under different climate change scenarios},
  series = {Sustainability},
  volume    = {11},
  journal   = {Sustainability},
  number    = {24},
  issn      = {2071-1050},
  doi       = {10.3390/su11247083},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193825},
  year      = {2019},
  abstract  = {Many parts of sub-Saharan Africa (SSA) are prone to land use and land cover change (LULCC). In many cases, natural systems are converted into agricultural land to feed the growing population. However, despite climate change being a major focus nowadays, the impacts of these conversions on water resources, which are essential for agricultural production, is still often neglected, jeopardizing the sustainability of the socio-ecological system. This study investigates historic land use/land cover (LULC) patterns as well as potential future LULCC and its effect on water quantities in a complex tropical catchment in Tanzania. It then compares the results using two climate change scenarios. The Land Change Modeler (LCM) is used to analyze and to project LULC patterns until 2030 and the Soil and Water Assessment Tool (SWAT) is utilized to simulate the water balance under various LULC conditions. Results show decreasing low flows by 6-8\% for the LULC scenarios, whereas high flows increase by up to 84\% for the combined LULC and climate change scenarios. The effect of climate change is stronger compared to the effect of LULCC, but also contains higher uncertainties. The effects of LULCC are more distinct, although crop specific effects show diverging effects on water balance components. This study develops a methodology for quantifying the impact of land use and climate change and therefore contributes to the sustainable management of the investigated catchment, as it shows the impact of environmental change on hydrological extremes (low flow and floods) and determines hot spots, which are critical for environmental development.},
  language  = {en}
}
@article{LatifiValbuena2019,
  author    = {Latifi, Hooman and Valbuena, Ruben},
  title     = {Current trends in forest ecological applications of three-dimensional remote sensing: Transition from experimental to operational solutions?},
  series = {Forests},
  volume    = {10},
  journal   = {Forests},
  number    = {10},
  issn      = {1999-4907},
  doi       = {10.3390/f10100891},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193282},
  year      = {2019},
  abstract  = {The alarming increase in the magnitude and spatiotemporal patterns of changes in composition, structure and function of forest ecosystems during recent years calls for enhanced cross-border mitigation and adaption measures, which strongly entail intensified research to understand the underlying processes in the ecosystems as well as their dynamics. Remote sensing data and methods are nowadays the main complementary sources of synoptic, up-to-date and objective information to support field observations in forest ecology. In particular, analysis of three-dimensional (3D) remote sensing data is regarded as an appropriate complement, since they are hypothesized to resemble the 3D character of most forest attributes. Following their use in various small-scale forest structural analyses over the past two decades, these sources of data are now on their way to be integrated in novel applications in fields like citizen science, environmental impact assessment, forest fire analysis, and biodiversity assessment in remote areas. These and a number of other novel applications provide valuable material for the Forests special issue "3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function", which shows the promising future of these technologies and improves our understanding of the potentials and challenges of 3D remote sensing in practical forest ecology worldwide.},
  language  = {en}
}