ANALYSIS OF FILTERING TECHNIQUES FOR INVESTIGATING LANDSLIDE-INDUCED TOPOGRAPHIC CHANGES IN THE OETZ VALLEY (TYROL, AUSTRIA)

Abstract. Landslides endanger settlements and infrastructure in mountain areas across the world. Monitoring of landslides is therefore essential in order to understand and possibly predict their behavior and potential danger. Terrestrial laser scanning has proven to be a successful tool in the assessment of changes on landslide surfaces due to its high resolution and accuracy. However, it is necessary to classify the 3D point clouds into vegetation and bare-earth points using filtering algorithms so that changes caused by landslide activity can be quantified. For this study, three classification algorithms are compared on an exemplary landslide study site in the Oetz valley in Tyrol, Austria. An optimal set of parameters is derived for each algorithm and their performances are evaluated using different metrics. The volume changes on the study site between the years 2017 and 2019 are compared after the application of each algorithm. The results show that (i) the tested filter techniques perform differently, (ii) their performance depends on their parameterization and (iii) the best-performing parameterization found over the vegetated test area will yield misclassifications on non-vegetated rough terrain. In particular, if only small changes have occurred the choice of the filtering technique and its parameterization play an important role in estimating volume changes

Unraveling the structure-activity-selectivity relationships in furfuryl alcohol photoreforming to H2 and hydrofuroin over ZnxIn2S3+x photocatalysts

ZnxIn2S3+x has emerged as a promising candidate for alcohol photoreforming based on C-H activation and C-C coupling. However, the underlying structure-activity-selectivity relationships remain unclear. Here we report on ZnxIn2S3+x with varying Zn:In:S ratios for visible-light-driven furfuryl alcohol reforming into H2 and hydrofuroin, a jet fuel precursor, via C-H activation and C-C coupling. S-• radicals are directly identified as the catalytically active sites responsible for C-H activation in furfuryl alcohol, promoting selectivity toward H2 and hydrofuroin. The optimum ZnxIn2S3+x activity derives from a trade-off between enhanced carrier dynamics and diminished visible light absorption as the x value in ZnxIn2S3+x increases. Further, a higher Zn-S:In-S layer ratio prolongs the S-• lifetime in the Zn-S layer, promoting C-H activation and delivering a higher C-C coupling product selectivity. The findings represent a step toward further establishing sulfide-based photocatalysts for sustainable H2 production via organic photoreforming.Denny Gunawan, Jodie A. Yuwono, Priyank V. Kumar, Akasha Kaleem, Michael P. Nielsen, Murad J.Y. Tayebjee, Louis Oppong-Antwi, Haotian Wen, Inga Kuschnerus, Shery L.Y. Chang, Yu Wang, Rosalie K. Hocking, Ting-Shan Chan, Cui Ying Toe, Jason Scott, Rose Ama

Development and characterization of superparamagnetic coatings

Since 2005, Magnetic Particle Imaging (MPI) is handled as a key technology with great potential in medical applications as an imaging method [1]. The superparamagnetic iron oxide nanoparticles (SPIONs) which are already used as a tracer in MPI, combined with various polymers, are being investigated in order to enhance this potential. A combination of polymers such as polyethylene (PE) and polyurethane (PU) and SPIONs could be used as a coating for medical devices, or added to semi-rigid polyurethane for the production of surgical instruments [2]. This would be of great interest, since the method provides high sensitivity with simultaneous high spatial resolution and three-dimensional imaging in real time. Therefore various superparamagnetic coatings were developed, tested and characterized. Finally SPIONs and various polymers were combined directly and used for MPI-compatible models

Automatic detection of bulldozer-induced changes on a sandy beach from video using YOLO algorithm

Sandy beaches are subject to changes due to multiple factors, that are both natural (e.g. storms) and anthropogenic. Great efforts are being made to monitor these ecosystems and understand their dynamics in order to assure their conservation. The identification of anthropogenic changes and its differentiation from natural ones is an important task for coastal monitoring. In this study, we present a methodology for the detection of anthropogenic changes in a coastal ecosystem by automatically detecting active bulldozers in continuous beach video data. PCA is used to highlight changes in consecutive images due to moving objects. Next, the YOLO object detection algorithm is used to identify the bulldozers in the change images. YOLO was specifically trained for the task, obtaining a precision of 0.94 and a recall of 0.81. An automatic tool was developed, and the process was carried out on two months of video data, consisting of approximately 19 000 images. The resulting information was compared with changes derived from 3D data obtained from a permanent laser scanner. The correlation among the results of the two methodologies was computed. For a validation area and daily time frame a correlation of 0.88 was obtained between the number of detected bulldozers and the area affected by changes in height larger than 0.3 m.</p

Analysis of Filtering Techniques for Investigating Landslide-Induced Topographic Changes in the Oetz Valley (Tyrol, Austria)

Landslides endanger settlements and infrastructure in mountain areas across the world. Monitoring of landslides is therefore essential in order to understand and possibly predict their behavior and potential danger. Terrestrial laser scanning has proven to be a successful tool in the assessment of changes on landslide surfaces due to its high resolution and accuracy. However, it is necessary to classify the 3D point clouds into vegetation and bare-earth points using filtering algorithms so that changes caused by landslide activity can be quantified. For this study, three classification algorithms are compared on an exemplary landslide study site in the Oetz valley in Tyrol, Austria. An optimal set of parameters is derived for each algorithm and their performances are evaluated using different metrics. The volume changes on the study site between the years 2017 and 2019 are compared after the application of each algorithm. The results show that (i) the tested filter techniques perform differently, (ii) their performance depends on their parameterization and (iii) the best-performing parameterization found over the vegetated test area will yield misclassifications on non-vegetated rough terrain. In particular, if only small changes have occurred the choice of the filtering technique and its parameterization play an important role in estimating volume changes.</p

Die Stadtentwicklung von Karlsruhe Eine Darstellung der raumzeitlichen Entwicklung von Karlsruhe und eine Lowry-Simulation

SIGLETIB: RN 4768 (69) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Automatic detection of bulldozer-induced changes on a sandy beach from video using YOLO algorithm

Sandy beaches are subject to changes due to multiple factors, that are both natural (e.g. storms) and anthropogenic. Great efforts are being made to monitor these ecosystems and understand their dynamics in order to assure their conservation. The identification of anthropogenic changes and its differentiation from natural ones is an important task for coastal monitoring. In this study, we present a methodology for the detection of anthropogenic changes in a coastal ecosystem by automatically detecting active bulldozers in continuous beach video data. PCA is used to highlight changes in consecutive images due to moving objects. Next, the YOLO object detection algorithm is used to identify the bulldozers in the change images. YOLO was specifically trained for the task, obtaining a precision of 0.94 and a recall of 0.81. An automatic tool was developed, and the process was carried out on two months of video data, consisting of approximately 19 000 images. The resulting information was compared with changes derived from 3D data obtained from a permanent laser scanner. The correlation among the results of the two methodologies was computed. For a validation area and daily time frame a correlation of 0.88 was obtained between the number of detected bulldozers and the area affected by changes in height larger than 0.3 m.Optical and Laser Remote SensingCoastal Engineerin

Tissue engineered model of hepatic breast cancer micrometastasis shows host-dependent colonization patterns and drug responses

ABSTRACTEarly stages of colonization of distant organs by metastatic cancer cells (micrometastasis) remain almost inaccessible to study due to lack of relevant experimental approaches. Here, we show the first 3D tissue engineered model of hepatic micrometastasis of triple negative breast cancer (TNBC). It reproduces characteristic histopathological features of the disease and reveals that metastatic TNBC cells colonize liver parenchymal and stromal extracellular matrix with different speed and by different strategies. These engineered tumors induce the angiogenic switch when grafted in vivo, confirming their metastatic-specific behaviour. Furthermore, we proved feasibility and biological relevance of our model for drug and nanoparticle testing and found a down-regulatory effect of the liver microenvironment of the sensitivity of TNBC cells to chemotherapeutic drug doxorubicin in free and nanoformulated forms. The convenient and affordable methodology established here can be translated to other types of metastatic tumors for basic cancer biology research and adapted for high-throughput assays.</jats:p