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Authors: Rollan, T.A.M.; Advisor: -; Participants: - (2016) - Cabadbaran City is the capital of Agusan del Norte which is located at the north eastern portion of Mindanao, Philippines. Currently, the city government and agriculture office are implementing programs focusing on improving coconut and vegetable productivity, controlling banana disease and infestation, and enhancing abaca production industry. In this study, only discrete LiDAR datasets were utilized. Corresponding orthophotos were used only for training and validation. Land cover classification was done using two workflows using Support Vector Machines (SVM) as the classifier. In the first workflow, land cover classes were classified using rasterized point cloud metrics such as minim...
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Authors: Kamps, M.; Advisor: -; Participants: - (2016) - Land-cover change could considerably lower landslide triggering rainfall thresholds allowing precipitation events with shorter recurrence intervals to initiate shallow landslides. This research focusses on developing an automated, robust and upscalable workflow to quantitatively assess the effect land-cover change has on initiating rainfall induced shallow landslides in the Laternser Valley. Land-cover is classified using four sets of high resolution orthophotos (198x, 2001, 2006, 2009; 0.25 m spatial resolution) by applying an object-based approach with eCognition software. The correlation between land-cover change and landslide occurrence was assessed by analyzing land-cover change ...
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Authors: Campomanes, F.; Advisor: -; Participants: - (2016) - Mangrove forest ecosystems fulfil a number of important functions like supporting the conservation of biological diversity by providing habitats, nurseries, and nutrients for animal species. In the Philippines, mangrove forests are declining due to the growth of aquaculture production. Mangrove forests are slowly being replaced by fishponds. An accurate inventory of what are left of these natural resources is important to know how we can conserve and manage them. This study aims to compare the performance of support vector machines (SVM) with random forest (RF) algorithm in automatically classifying mangrove forests using LiDAR data and orthophotographs in an object based approach. Th...
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Authors: Naorem, V.; Advisor: -; Participants: - (2016) - Robust monitoring approaches for informal settlements using very high-resolution (VHR) satellite imagery can deliver essential information for supporting the formulation of pro-poor policies. Such information can complement census methods or participatory approaches. With the increasing availability of VHR satellite imagery, detection of the informal settlements benefits from the conceptualization of location-specific knowledge in the form of a locally-adapted generic slum ontology (GSO). In this study, we developed the local slum ontology for Mumbai, India, by incorporating local knowledge with image-based proxies. Then, we translated the local ontology into a rule set using Object B...
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Authors: Naorem, V. de; Advisor: -; Participants: - (2016) - Robust monitoring approaches for informal settlements using very high-resolution (VHR) satellite imagery can deliver essential information for supporting the formulation of pro-poor policies. Such information can complement census methods or participatory approaches. With the increasing availability of VHR satellite imagery, detection of the informal settlements benefits from the conceptualization of location-specific knowledge in the form of a locally-adapted generic slum ontology (GSO). In this study, we developed the local slum ontology for Mumbai, India, by incorporating local knowledge with image-based proxies. Then, we translated the local ontology into a rule set using Object B...
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Authors: Bas, T.P. le; Advisor: -; Participants: - (2016) - A need was therefore seen for OBIA to be integrated into GIS. ESRI’s ArcMap is currently used by millions of people daily worldwide and could benefit from access to OBIA. Easy usage and access is essential. A toolbar for push button control was envisaged and RSOBIA (Remote sensing Object Based Image Analysis) was created. The toolbar is easy to use and requires very little training. For the slightly higher level user a toolbox has also been created, so that the RSOBIA functions can be incorporated into other programming models and allows more complex functions to be created.
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Authors: Belgiu, M.; Advisor: -; Participants: - (2017) - Efficient methodologies for mapping croplands are an essential condition for the implementation of sustainable agricultural practices and for monitoring crops periodically. The increasing spatial and temporal resolution of globally available satellite images, such as those provided by Sentinel-2, creates new possibilities for generating accurate datasets on available crop types, in ready-to-use vector data format. Existing solutions dedicated to cropland mapping, based on high resolution remote sensing data, are mainly focused on pixel-based analysis of time series data. This paper evaluates how a time-weighted dynamic time warping (TWDTW) method that uses Sentinel-2 time series perfo...
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Authors: Krafft, P.; Advisor: -; Participants: - (2016) - Accurate and reliable information about the situation in refugee or internally displaced person camps is very important for planning any kind of help like health care, infrastructure or vaccination campaigns. The number and spatial distribution of single dwellings extracted semi-automatically from very high resolution (VHR) satellite imagery as an indicator for population estimations can provide such important information. The accuracy of the extracted dwellings can vary quite a lot depending on various factors. To enhance established single dwelling extraction approaches, we have tested the integration of stratified template matching methods in objectbased image analysis (OBIA) workf...
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Authors: Costa, H.; Advisor: -; Participants: - (2016) - Training of object-based land cover classifications is often performed with objects generated via image segmentation. The objects are commonly assumed to be thematically pure or excluded from training if a mixture of classes is associated with them. However, excluding mixed objects has several consequences such as reducing the size of the training data sets. In this study, it is hypothesized that mixed objects may be used in the training stage of a classification to increase the accuracy with which land cover may be mapped from remotely sensed data, with outputs evaluated in relation to a conventional analysis using only pure objects in training. WorldView-2 data covering the Universi...
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