@article{EmmertKneisel2017, author = {Emmert, Adrian and Kneisel, Christof}, title = {Internal structure of two alpine rock glaciers investigated by quasi-3-D electrical resistivity imaging}, series = {The Cryosphere}, volume = {11}, journal = {The Cryosphere}, doi = {10.5194/tc-11-841-2017}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157569}, pages = {841-855}, year = {2017}, abstract = {Interactions between different formative processes are reflected in the internal structure of rock glaciers. Therefore, the detection of subsurface conditions can help to enhance our understanding of landform development. For an assessment of subsurface conditions, we present an analysis of the spatial variability of active layer thickness, ground ice content and frost table topography for two different rock glaciers in the Eastern Swiss Alps by means of quasi-3-D electrical resistivity imaging (ERI). This approach enables an extensive mapping of subsurface structures and a spatial overlay between site-specific surface and subsurface characteristics. At Nair rock glacier, we discovered a gradual descent of the frost table in a downslope direction and a constant decrease of ice content which follows the observed surface topography. This is attributed to ice formation by refreezing meltwater from an embedded snow bank or from a subsurface ice patch which reshapes the permafrost layer. The heterogeneous ground ice distribution at Uertsch rock glacier indicates that multiple processes on different time domains were involved in the development. Resistivity values which represent frozen conditions vary within a wide range and indicate a successive formation which includes several advances, past glacial overrides and creep processes on the rock glacier surface. In combination with the observed topography, quasi-3-D ERI enables us to delimit areas of extensive and compressive flow in close proximity. Excellent data quality was provided by a good coupling of electrodes to the ground in the pebbly material of the investigated rock glaciers. Results show the value of the quasi-3-D ERI approach but advise the application of complementary geophysical methods for interpreting the results.}, language = {en} } @article{FaOliveroRealetal.2015, author = {Fa, John E. and Olivero, Jes{\´u}s and Real, Raimundo and Farf{\´a}n, Miguel A. and M{\´a}rquez, Ana L. and Vargas, J. Mario and Ziegler, Stefan and Wegmann, Martin and Brown, David and Margetts, Barrie and Nasi, Robert}, title = {Disentangling the relative effects of bushmeat availability on human nutrition in central Africa}, series = {Scientific Reports}, volume = {5}, journal = {Scientific Reports}, number = {8168}, doi = {10.1038/srep08168}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-144110}, year = {2015}, abstract = {We studied links between human malnutrition and wild meat availability within the Rainforest Biotic Zone in central Africa. We distinguished two distinct hunted mammalian diversity distributions, one in the rainforest areas (Deep Rainforest Diversity, DRD) containing taxa of lower hunting sustainability, the other in the northern rainforest-savanna mosaic, with species of greater hunting potential (Marginal Rainforest Diversity, MRD). Wild meat availability, assessed by standing crop mammalian biomass, was greater in MRD than in DRD areas. Predicted bushmeat extraction was also higher in MRD areas. Despite this, stunting of children, a measure of human malnutrition, was greater in MRD areas. Structural equation modeling identified that, in MRD areas, mammal diversity fell away from urban areas, but proximity to these positively influenced higher stunting incidence. In DRD areas, remoteness and distance from dense human settlements and infrastructures explained lower stunting levels. Moreover, stunting was higher away from protected areas. Our results suggest that in MRD areas, forest wildlife rational use for better human nutrition is possible. By contrast, the relatively low human populations in DRD areas currently offer abundant opportunities for the continued protection of more vulnerable mammals and allow dietary needs of local populations to be met.}, language = {en} } @article{FakhriLatifi2021, author = {Fakhri, Seyed Arvin and Latifi, Hooman}, title = {A consumer grade UAV-based framework to estimate structural attributes of coppice and high oak forest stands in semi-arid regions}, series = {Remote Sensing}, volume = {13}, journal = {Remote Sensing}, number = {21}, issn = {2072-4292}, doi = {10.3390/rs13214367}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248469}, year = {2021}, abstract = {Semi-arid tree covers, in both high and coppice growth forms, play an essential role in protecting water and soil resources and provides multiple ecosystem services across fragile ecosystems. Thus, they require continuous inventories. Quantification of forest structure in these tree covers provides important measures for their management and biodiversity conservation. We present a framework, based on consumer-grade UAV photogrammetry, to separately estimate primary variables of tree height (H) and crown area (A) across diverse coppice and high stands dominated by Quercus brantii Lindl. along the latitudinal gradient of Zagros mountains of western Iran. Then, multivariate linear regressions were parametrized with H and A to estimate the diameter at breast height (DBH) of high trees because of its importance to accelerate the existing practical DBH inventories across Zagros Forests. The estimated variables were finally applied to a model tree aboveground biomass (AGB) for both vegetative growth forms by local allometric equations and Random Forest models. In each step, the estimated variables were evaluated against the field reference values, indicating practically high accuracies reaching root mean square error (RMSE) of 0.68 m and 4.74 cm for H and DBH, as well as relative RMSE < 10\% for AGB estimates. The results generally suggest an effective framework for single tree-based attribute estimation over mountainous, semi-arid coppice, and high stands.}, language = {en} } @article{FekriLatifiAmanietal.2021, author = {Fekri, Erfan and Latifi, Hooman and Amani, Meisam and Zobeidinezhad, Abdolkarim}, title = {A training sample migration method for wetland mapping and monitoring using Sentinel data in Google Earth Engine}, series = {Remote Sensing}, volume = {13}, journal = {Remote Sensing}, number = {20}, issn = {2072-4292}, doi = {10.3390/rs13204169}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248542}, year = {2021}, abstract = {Wetlands are one of the most important ecosystems due to their critical services to both humans and the environment. Therefore, wetland mapping and monitoring are essential for their conservation. In this regard, remote sensing offers efficient solutions due to the availability of cost-efficient archived images over different spatial scales. However, a lack of sufficient consistent training samples at different times is a significant limitation of multi-temporal wetland monitoring. In this study, a new training sample migration method was developed to identify unchanged training samples to be used in wetland classification and change analyses over the International Shadegan Wetland (ISW) areas of southwestern Iran. To this end, we first produced the wetland map of a reference year (2020), for which we had training samples, by combining Sentinel-1 and Sentinel-2 images and the Random Forest (RF) classifier in Google Earth Engine (GEE). The Overall Accuracy (OA) and Kappa coefficient (KC) of this reference map were 97.93\% and 0.97, respectively. Then, an automatic change detection method was developed to migrate unchanged training samples from the reference year to the target years of 2018, 2019, and 2021. Within the proposed method, three indices of the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and the mean Standard Deviation (SD) of the spectral bands, along with two similarity measures of the Euclidean Distance (ED) and Spectral Angle Distance (SAD), were computed for each pair of reference-target years. The optimum threshold for unchanged samples was also derived using a histogram thresholding approach, which led to selecting the samples that were most likely unchanged based on the highest OA and KC for classifying the test dataset. The proposed migration sample method resulted in high OAs of 95.89\%, 96.83\%, and 97.06\% and KCs of 0.95, 0.96, and 0.96 for the target years of 2018, 2019, and 2021, respectively. Finally, the migrated samples were used to generate the wetland map for the target years. Overall, our proposed method showed high potential for wetland mapping and monitoring when no training samples existed for a target year.}, language = {en} } @article{FisserKhorsandiWegmannetal.2022, author = {Fisser, Henrik and Khorsandi, Ehsan and Wegmann, Martin and Baier, Frank}, title = {Detecting moving trucks on roads using Sentinel-2 data}, series = {Remote Sensing}, volume = {14}, journal = {Remote Sensing}, number = {7}, issn = {2072-4292}, doi = {10.3390/rs14071595}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267174}, year = {2022}, abstract = {In most countries, freight is predominantly transported by road cargo trucks. We present a new satellite remote sensing method for detecting moving trucks on roads using Sentinel-2 data. The method exploits a temporal sensing offset of the Sentinel-2 multispectral instrument, causing spatially and spectrally distorted signatures of moving objects. A random forest classifier was trained (overall accuracy: 84\%) on visual-near-infrared-spectra of 2500 globally labelled targets. Based on the classification, the target objects were extracted using a developed recursive neighbourhood search. The speed and the heading of the objects were approximated. Detections were validated by employing 350 globally labelled target boxes (mean F\(_1\) score: 0.74). The lowest F\(_1\) score was achieved in Kenya (0.36), the highest in Poland (0.88). Furthermore, validated at 26 traffic count stations in Germany on in sum 390 dates, the truck detections correlate spatio-temporally with station figures (Pearson r-value: 0.82, RMSE: 43.7). Absolute counts were underestimated on 81\% of the dates. The detection performance may differ by season and road condition. Hence, the method is only suitable for approximating the relative truck traffic abundance rather than providing accurate absolute counts. However, existing road cargo monitoring methods that rely on traffic count stations or very high resolution remote sensing data have limited global availability. The proposed moving truck detection method could fill this gap, particularly where other information on road cargo traffic are sparse by employing globally and freely available Sentinel-2 data. It is inferior to the accuracy and the temporal detail of station counts, but superior in terms of spatial coverage.}, language = {en} } @article{ForkuorHounkpatinWelpetal.2017, author = {Forkuor, Gerald and Hounkpatin, Ozias K.L. and Welp, Gerhard and Thiel, Michael}, title = {High resolution mapping of soil properties using remote sensing variables in south-western Burkina Faso: a comparison of machine learning and multiple linear regression models}, series = {PLOS One}, volume = {12}, journal = {PLOS One}, number = {1}, doi = {10.1371/journal.pone.0170478}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-180978}, pages = {21}, year = {2017}, abstract = {Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.}, language = {en} } @article{ForkuorUllmannGriesbeck2020, author = {Forkuor, Gerald and Ullmann, Tobias and Griesbeck, Mario}, title = {Mapping and monitoring small-scale mining activities in Ghana using Sentinel-1 time series (2015-2019)}, series = {Remote Sensing}, volume = {12}, journal = {Remote Sensing}, number = {6}, issn = {2072-4292}, doi = {10.3390/rs12060911}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-203204}, year = {2020}, abstract = {Illegal small-scale mining (galamsey) in South-Western Ghana has grown tremendously in the last decade and caused significant environmental degradation. Excessive cloud cover in the area has limited the use of optical remote sensing data to map and monitor the extent of these activities. This study investigated the use of annual time-series Sentinel-1 data to map and monitor illegal mining activities along major rivers in South-Western Ghana between 2015 and 2019. A change detection approach, based on three time-series features — minimum, mean, maximum — was used to compute a backscatter threshold value suitable to identify/detect mining-induced land cover changes in the study area. Compared to the mean and maximum, the minimum time-series feature (in both VH and VV polarization) was found to be more sensitive to changes in backscattering within the period of investigation. Our approach permitted the detection of new illegal mining areas on an annual basis. A backscatter threshold value of +1.65 dB was found suitable for detecting illegal mining activities in the study area. Application of this threshold revealed illegal mining area extents of 102 km\(^2\), 60 km\(^2\) and 33 km\(^2\) for periods 2015/2016-2016/2017, 2016/2017-2017/2018 and 2017/2018-2018/2019, respectively. The observed decreasing trend in new illegal mining areas suggests that efforts at stopping illegal mining yielded positive results in the period investigated. Despite the advantages of Synthetic Aperture Radar data in monitoring phenomena in cloud-prone areas, our analysis revealed that about 25\% of the Sentinel-1 data, mostly acquired in March and October (beginning and end of rainy season respectively), were unusable due to atmospheric effects from high intensity rainfall events. Further investigation in other geographies and climatic regions is needed to ascertain the susceptibility of Sentinel-1 data to atmospheric conditions.}, language = {en} } @article{FrimmelChakravartiBasei2022, author = {Frimmel, Hartwig E. and Chakravarti, Rajarshi and Basei, Miguel A. S.}, title = {Detrital zircon ages from Archaean conglomerates in the Singhbhum Craton, eastern India: implications on economic Au-U potential}, series = {Mineralium Deposita}, volume = {57}, journal = {Mineralium Deposita}, number = {8}, issn = {0026-4598}, doi = {10.1007/s00126-022-01121-3}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324084}, pages = {1499-1514}, year = {2022}, abstract = {New U-Pb age and Hf isotope data obtained on detrital zircon grains from Au- and U-bearing Archaean quartz-pebble conglomerates in the Singhbhum Craton, eastern India, specifically the Upper Iron Ore Group in the Badampahar Greenstone Belt and the Phuljhari Formation below the Dhanjori Group provide insights into the zircon provenance and maximum age of sediment deposition. The most concordant, least disturbed \(^{207}\)Pb/\(^{206}\)Pb ages cover the entire range of known magmatic and higher grade metamorphic events in the craton from 3.48 to 3.06 Ga and show a broad maximum between 3.38 and 3.18 Ga. This overlap is also mimicked by Lu-Hf isotope analyses, which returned a wide range in \(_{εHf}\)(t) values from + 6 to - 5, in agreement with the range known from zircon grains in igneous and metamorphic rocks in the Singhbhum Craton. A smaller but distinct age peak centred at 3.06 Ga corresponds to the age of the last major magmatic intrusive event, the emplacement of the Mayurbhanj Granite and associated gabbro, picrite and anorthosite. Thus, these intrusive rocks must form a basement rather than being intrusive into the studied conglomerates as previously interpreted. The corresponding detrital zircon grains all have a subchondritic Hf isotopic composition. The youngest reliable zircon ages of 3.03 Ga in the case of the basal Upper Iron Ore Group in the east of the craton and 3.00 Ga for the Phuljhari Formation set an upper limit on the age of conglomerate sedimentation. Previously published detrital zircon age data from similarly Au-bearing conglomerates in the Mahagiri Quartzite in the Upper Iron Ore Group in the south of the craton gave a somewhat younger maximum age of sedimentation of 2.91 Ga. There, the lower limit on sedimentation is given by an intrusive relationship with a c. 2.8 Ga granite. The time window thus defined for conglomerate deposition on the Singhbhum Craton is almost identical to the age span established for the, in places, Au- and U-rich conglomerates in the Kaapvaal Craton of South Africa: the 2.98-2.78 Ga Dominion Group and Witwatersrand Supergroup in South Africa. Since the recognition of first major concentration of gold on Earth's surface by microbial activity having taken place at around 2.9 Ga, independent of the nature of the hinterland, the above similarity in age substantially increases the potential for discovering Witwatersrand-type gold and/or uranium deposits on the Singhbhum Craton. Further age constraints are needed there, however, to distinguish between supposedly less fertile (with respect to Au) > 2.9 Ga and more fertile < 2.9 Ga successions.}, language = {en} } @article{FaethKunzKneisel2022, author = {F{\"a}th, Julian and Kunz, Julius and Kneisel, Christof}, title = {Monitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT)}, series = {Journal of Forestry Research}, volume = {33}, journal = {Journal of Forestry Research}, number = {5}, issn = {1007-662X}, doi = {10.1007/s11676-022-01498-x}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324073}, pages = {1649-1662}, year = {2022}, abstract = {The effects of drought on tree mortality at forest stands are not completely understood. For assessing their water supply, knowledge of the small-scale distribution of soil moisture as well as its temporal changes is a key issue in an era of climate change. However, traditional methods like taking soil samples or installing data loggers solely collect parameters of a single point or of a small soil volume. Electrical resistivity tomography (ERT) is a suitable method for monitoring soil moisture changes and has rarely been used in forests. This method was applied at two forest sites in Bavaria, Germany to obtain high-resolution data of temporal soil moisture variations. Geoelectrical measurements (2D and 3D) were conducted at both sites over several years (2015-2018/2020) and compared with soil moisture data (matric potential or volumetric water content) for the monitoring plots. The greatest variations in resistivity values that highly correlate with soil moisture data were found in the main rooting zone. Using the ERT data, temporal trends could be tracked in several dimensions, such as the interannual increase in the depth of influence from drought events and their duration, as well as rising resistivity values going along with decreasing soil moisture. The results reveal that resistivity changes are a good proxy for seasonal and interannual soil moisture variations. Therefore, 2D- and 3D-ERT are recommended as comparatively non-laborious methods for small-spatial scale monitoring of soil moisture changes in the main rooting zone and the underlying subsurface of forested sites. Higher spatial and temporal resolution allows a better understanding of the water supply for trees, especially in times of drought.}, language = {en} } @article{GeyerLandingMeieretal.2023, author = {Geyer, Gerd and Landing, Ed and Meier, Stefan and H{\"o}hn, Stefan}, title = {Oldest known West Gondwanan graptolite: Ovetograptus? sp. (lower Agdzian/lowest Wuliuan; basal Middle Cambrian) of the Franconian Forest, Germany, and review of pre-Furongian graptolithoids}, series = {Pal{\"a}ontologische Zeitschrift}, volume = {97}, journal = {Pal{\"a}ontologische Zeitschrift}, number = {4}, issn = {0031-0220}, doi = {10.1007/s12542-022-00627-5}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324099}, pages = {677-686}, year = {2023}, abstract = {The occurrence of a likely graptolite in lowest Wuliuan strata of the Franconian Forest almost certainly records the oldest known graptolithoid hemichordate in West Gondwana and possibly the oldest graptolite presently known. The fossil is a delicate, erect, apparently unbranched rhabdosome with narrow thecae tentatively assigned to the poorly known genus Ovetograptus of the Dithecodendridae. This report includes an overview of pre-Furongian graptolithoids with slight corrections on the stratigraphic position of earlier reported species.}, language = {en} }