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  • BB

  • Accuracy Analysis of Photogrammetric UAV Image Blocks: Influence of Onboard RTK-GNSS and Cross Flight Patterns

    • Authors: Gerke, M.;  Advisor: -;  Participants: - (2016)

  • Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. Despite the flexibility gained when using those devices, one has to invest more effort for ground control measurements compared to conventional photogrammetric airborne data acquisition, because positioning devices on UAVs are generally less accurate. Additionally, the limited quality of employed end-user cameras asks for self-calibration, which might cause some problems as well. A good distribution of ground control points (GCPs) is not only needed to solve for the absolute orientation of the image block in the desired coordinate frame, but also to mitigate block deformation effects which are resulting mainly from remaining systematic errors in the camera calibration. In this paper recent developments in ...
  • BB

  • A web-based platform for remote sensing image annotation

    • Authors: Garcia-Pedrero, A.;  Advisor: -;  Participants: - (2016)

  • The generation of labeled data for training automated methods used in the analysis of remote sensing images is a challenging task. Approaches as Active Learning aim to perform accurate classifications in a scenario of a few annotated data. These approaches generally require the interaction between the user and the machine learning method during training phase. However, in the remote sensing area, it is difficult to find a tool that facilitates this interaction. In this work, an interactive web-based platform to perform the training of method for remote sensing image annotation by means of an active learning approach is proposed. The platform integrates open-source GIS technologies and object-based approach in order to facilitate the interaction between the user and the active learni...
  • BB

  • A web-based platform for remote sensing image annotation

    • Authors: Garcia-Pedrero, A.;  Advisor: -;  Participants: - (2016)

  • The generation of labeled data for training automated methods used in the analysis of remote sensing images is a challenging task. Approaches as Active Learning aim to perform accurate classifications in a scenario of a few annotated data. These approaches generally require the interaction between the user and the machine learning method during training phase. However, in the remote sensing area, it is difficult to find a tool that facilitates this interaction. In this work, an interactive web-based platform to perform the training of method for remote sensing image annotation by means of an active learning approach is proposed. The platform integrates open-source GIS technologies and object-based approach in order to facilitate the interaction between the user and the active learni...
  • BB

  • Bi-decadal groundwater level trends in a semi-arid south indian region: Declines, causes and management

    • Authors: Shukla, S.; Sishodia, R.P.;  Advisor: -;  Participants: - (2016)

  • India, world’s largest groundwater user (250 billion m3 yr−1) has been reported to experience declining groundwater levels. However, the statistical significance of the decline has not been analyzed to separate human effects from natural variability. Contrary to common perception of widespread groundwater declines only 22–36% of the wells showed statistically significant declines. The use of well depth during dry well periods may slightly underestimate the number of declining wells (by 1%) and rate of decline. Increase in groundwater irrigated area combined with rainfall and power subsidy policy, were the main causative factors for the decline. Groundwater decline after implementation of free-electricity policy in 2004 confirmed the nexus between power subsidy and groundwater. These...
  • BB

  • Coastal changes and movements in the wider Vlora (Albania) area

    • Authors: Kanjir, U.;  Advisor: -;  Participants: - (2016)

  • This paper explores the environmental change monitoring on the Albanian coastline (Vlora area) by analysing optical remote sensing data. Changes along this coastline are driven by coastal erosion and abusive urban construction of mostly tourist complexes and other man-made processes and pressures (e.g. sandpits, poor wastewater management, etc.). The change detection is based on yearly Landsat data of the period between 1984 and 2015. On the basis of mentioned images, each year's Normalized Difference Water Index (NDWI), Normalized Difference Build-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) are extracted. With the use of change vector analysis technique the combination of these indexes were then compared between each other. The quantitative extent of coastal c...
  • BB

  • Climate variability and irrigation impacts on streamflows in a Karst watershed—A systematic evaluation

    • Authors: Srivastava, P.; Singh, S.;  Advisor: -;  Participants: - (2016)

  • This study focuses on a systematic evaluation and separation of El Niño Southern Oscillation (ENSO) induced droughts and irrigation water withdrawal impacts on flow levels using a novel and powerful statistical technique, called JRFit. JRFit procedure was applied to quantify significant differences in streamflows, baseflows, and low flow statistics during non-irrigation (NI) and irrigation (IR) periods associated with ENSO phases. The results indicate that overall streamflow levels have decreased by approximately 20% after the introduction of irrigation in the study area. This study provides useful information to policymakers to devise irrigation water withdrawal policies during La Niña growing seasons for maintaining flow levels in the study area.
  • BB

  • Dropband:a convolutional neural network with data augmentation for scene classification of VHR satellite images

    • Authors: Yang, Naisen;  Advisor: -;  Participants: - (2016)

  • Data augmentation is a common method that can prevent the overfitting of classification tasks in deep neural networks. This paper presents another kind of data augmentation method called DropBand that is useful for remote sensing image classification. Data augmentation is usually used along two dimensions of the image plane. This method executes this operation in the third dimension formed by all the spectral bands of an input image. With dropping a band of images out, the error rate of deep neural networks can be reduced. This method can also be viewed as a peculiar version of deterministic Dropout. The normal Dropout does not work well when it is applied to input channels of neural networks. To release this issue, dropping a band of input by schedule is employed. Moreover, model s...
  • SH

  • Earth security index 2016 :Business diplomacy for sustainable development

    • Authors: -;  Advisor: -;  Participants: - (2016)

  • The report provides companiesan eye-opening approach to sustainable growth in the countries where they operate. Governments seeking to collaborate with the private sector to address development challenges in the context of the global goals for sustainable development. The report provides policy-makers with a framework to guide their engagement of companies and the opportunities for strategic partnerships around key issues.