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12 results for “Karlsruhe”
Thermal Bridges on Building Rooftops - Hyperspectral (RGB + Thermal + Height) drone images of Karlsruhe, Germany, with thermal bridge annotations
<p><strong>Overview:</strong></p> <p>The dataset of <strong>Thermal Bridges on Building Rooftops (TBBR dataset)</strong> consists of annotated combined RGB and thermal drone images with a height map. All images were converted to a uniform format of 3000x4000 pixels, aligned, and cropped to <strong>2680x3370</strong> to remove empty borders. See the "Usage" section below for details about the stored formats made available here.</p> <p>The raw images for our dataset were recorded with a normal (RGB) and a FLIR-XT2 (thermal) camera on a DJI M600 drone. They show six large building blocks of around 20 buildings per block recorded in the city centre of the German city Karlsruhe east of the market square. Because of a high overlap rate of the images, the same buildings are on average recorded from different angles in different images about 20 times.</p> <p>All images were recorded during a drone flight on March 19, 2019 from 7 a.m. to 8 a.m. At this time, temperatures were between 3.78 ° C and 4.97 ° C, humidity between 80% and 98%. There was no rain on the day of the flight, but there was 2.3mm/m² 48 hours beforehand. For recording the thermographic images an emissivity of 1.0 was set. The global radiation during this period was between 38.59 W / m² and 120.86 W / m². No direct sunlight can be seen visually on any of the recordings.</p> <p>The dataset contains <strong>926 images</strong> with a total of <strong>6,927 annotations</strong> of thermal bridges on rooftops, split into train and test subsets with 723 (5,614) and 203 (1,313) images (annotations), respectively. The annotations only include thermal bridges that are visually identifiable with the human eye. Because of the aforementioned image overlap, each thermal bridge is annotated multiple times from different angles.</p> <p>For the annotation of the thermal images the image processing program <em>VGG Image Annotator </em>from the Visual Geometry Group, version 2.0.10, was used. The thermal bridge annotations are outlined with polygon shapes. These polygon lines were placed as close as possible but outside the area of significant temperature increase. If a detected thermal bridge was partially covered by another building component located in the foreground, the thermal bridge was also marked across the covering in case of minor coverings. Adjacent thermal bridges, which affect different rooftop components, were annotated separately. For example, a window with poor insulation of the window reveal located in the area of a poorly insulated roof is annotated individually. There is no overlap between annotated areas. While each image contains annotations, they also include thermal bridges present that are not annotated.</p> <p><strong>Usage:</strong></p> <p>Each compressed archive file represents one of the six flight paths. For the related publication the final path (Flug1_105Media) was used as a hold-out test sample. The archives contain Numpy files (one per image) of shape (2680, 3370, 5), where the final dimension is the colour channel in the format [B, G, R, Thermal, Height].</p> <p>Archives were compressed using <a href="https://facebook.github.io/zstd/">ZStandard</a> compression. They can be decompressed in a terminal by running e.g.</p> <pre><code class="language-bash">tar -I zstd -xvf Flug1_105Media.tar.zst</code></pre> <p>these will be decompressed into the file structure:</p> <pre><code>images/ └── Flug1_105Media/ └── DJI_0004_R.npy └── DJI_0006_R.npy └── ...</code></pre> <p>Corresponding annotations are provided in the COCO JSON format. There is one file for training (Flug1_100Media - Flug1_104Media blocks) and one for test (Flug1_105Media block). They contain a single class (thermal bridge) and expect the folder structure shown below.</p> <p>Note: The annotation files contain <em>relative</em> paths to numpy files, in case of problems please convert to <em>absolute</em> paths (i.e. insert the containing directory before each file path in the JSON annotation files).</p> <p>We provide the <a href="https://github.com/Helmholtz-AI-Energy/TBBRDet"><strong>TBBRDet software</strong></a> which includes a dataloader and dataset inspection tools which make use of the <a href="https://github.com/facebookresearch/detectron2">Detectron2</a> and <a href="https://github.com/open-mmlab/mmdetection">MMDetection</a> libraries.</p> <p>We recommend the following folder structure for use:</p> <pre><code>├── train/ │ ├── Flug1_100-104Media_coco.json │ └── images/ │ ├── Flug1_100Media/ │ │ ├── DJI_XXXX_R.npy │ │ └── ... │ ├── ... │ └── Flug1_104Media/ │ ├── DJI_XXXX_R.npy │ └── ... └── test/ ├── Flug1_105Media_coco.json └── images/ └── Flug1_105Media/ ├── DJI_XXXX_R.npy └── ...</code></pre> <p><strong>Metadata:</strong></p> <p>The experimental metadata was structured with the <strong>Spatio Temporal Asset Catalog (STAC)</strong> specification family. This specification provides a standardized way for describing geospatial assets. It defines related JSON object types of Item, Catalog, and Catalog, extending on Collection as the basis.</p> <p>One STAC Collection JSON object provides information about the recorded images and the environmental conditions during recordings. It also contains information about the overall bounding box of the entire area in which images were recorded.</p> <p>This object links to related STAC Item JSON objects containing information about the recorded city blocks and the cameras. The objects for the city blocks contain the GeoJSON geometry of the respective block and the<br> corresponding bounding box. The objects containing the camera information are based on an existing STAC extension for camera related metadata.</p> <p>Metadata of the archived NumPy files for each image was structured using the <strong>Data Package</strong> schema from the <strong>Frictionless Standards</strong>. This standard describes a collection of data files. Therefore, metadata about all containerized NumPy files of the six flight paths (Flug1_100Media - Flug1_104Media blocks and Flug1_105Media block) is provided within a JSON-based file.</p> <p>Note that <strong>camera1</strong> corresponds to the <strong>RGB camera</strong> and <strong>camera2</strong> the <strong>thermal</strong>.</p> <p><strong>FAIR Digital Objects:</strong></p> <p>All files are represented in a standardized way as <strong>FAIR Digital Objects<br> (FAIR DOs)</strong> to enable machine actionable decisions on the data in spirit of<br> the FAIR principles.</p> <p><strong>Persistent Identifier (PID):</strong></p> <p>Persistent Identifiers (PIDs) are resolvable with the <a href="https://hdl.handle.net/">Handle.Net Registry (HNR)</a>.</p> <table> <thead> <tr> <th scope="col">File</th> <th scope="col">Persistent Identifier (PID)</th> </tr> </thead> <tbody> <tr> <td>Flug1_100-104Media_coco.json</td> <td>21.11152/6ea60288-d895-414e-80c0-26c9fdd662b2</td> </tr> <tr> <td>Flug1_105Media_coco.json</td> <td>21.11152/58d43ddc-5e29-4980-8675-ae579b50a1e2</td> </tr> <tr> <td>Flug1_100.tar.zst</td> <td>21.11152/6858a0b5-cc60-40e9-afef-8c2dd8b35e8e</td> </tr> <tr> <td>Flug1_101.tar.zst</td> <td>21.11152/e670f510-7e00-4d3a-9b90-3bac7a7c069e</td> </tr> <tr> <td>Flug1_102.tar.zst</td> <td>21.11152/3ab9f444-05f6-445e-a691-62fae4021bea</td> </tr> <tr> <td>Flug1_103.tar.zst</td> <td>21.11152/365fd8cf-8e86-41b8-9d0e-b816fdd01d29</td> </tr> <tr> <td>Flug1_104.tar.zst</td> <td>21.11152/041a6111-644a-4617-afb3-3c421a88e8e3</td> </tr> <tr> <td>Flug1_105.tar.zst</td> <td>21.11152/f48bf4e7-3879-4216-8f64-45a060b8f658</td> </tr> <tr> <td>Flug1_100-105_frictionless_standards.json</td> <td>21.11152/7b58b3b5-75eb-4417-ac4d-abe025e159f6</td> </tr> <tr> <td>Flug1_collection_stac_spec.json</td> <td>21.11152/ba370aa3-6422-428c-9ff7-c2ef429df603</td> </tr> <tr> <td>Flug1_100_stac_spec.json</td> <td>21.11152/09cb76fc-b8cb-4116-a22a-68c5bdfa77b0</td> </tr> <tr> <td>Flug1_101_stac_spec.json</td> <td>21.11152/24a55398-b96b-43dd-b0fb-cd8ce302c7ce</td> </tr> <tr> <td>Flug1_102_stac_spec.json</td> <td>21.11152/721234ac-4b5a-4d02-9944-82a08ef2db35</td> </tr> <tr> <td>Flug1_103_stac_spec.json</td> <td>21.11152/ebaeb5bc-0514-47c9-bcd2-98f0253843d8</td> </tr> <tr> <td>Flug1_104_stac_spec.json</td> <td>21.11152/9854677c-77c5-4a0b-916b-57dd9ec20198</td> </tr> <tr> <td>Flug1_105_stac_spec.json</td> <td>21.11152/cfd0fc0e-f5ea-464e-a57f-28e882924860</td> </tr> <tr> <td>Flug1_camera1_stac-spec.json</td> <td>21.11152/976fcf28-f924-4a21-b53d-5d054ad8198d</td> </tr> <tr> <td>Flug1_camera2_stac-spec.json</td> <td>21.11152/37833c54-1d36-42e4-858d-831447122863</td> </tr> </tbody> </table>
Hyperspectral (RGB + Thermal) drone images of Karlsruhe, Germany - Raw images for the Thermal Bridges on Building Rooftops (TBBR) dataset
<p><strong>Overview:</strong></p> <p>This repository contains the <strong>raw images</strong> for the dataset of <a href="https://doi.org/10.5281/zenodo.4767771"><strong>Thermal Bridges on Building Rooftops (TBBR) dataset</strong></a>.</p> <p>This dataset contains <strong>5696 drone images</strong> (2848 RGB and 2848 thermal) of building rooftops, recorded with a normal (RGB) and a FLIR-XT2 (thermal) camera on a DJI M600 drone. They show six large building blocks of around 20 buildings per block recorded in the city centre of the German city Karlsruhe east of the market square. Because of a high overlap rate of the images, the same buildings are on average recorded from different angles in different images about 20 times.</p> <p>All images were recorded during a drone flight on March 19, 2019 from 7 a.m. to 8 a.m. At this time, temperatures were between 3.78 ° C and 4.97 ° C, humidity between 80% and 98%. There was no rain on the day of the flight, but there was 2.3mm/m² 48 hours beforehand. For recording the thermographic images an emissivity of 1.0 was set. The global radiation during this period was between 38.59 W / m² and 120.86 W / m². No direct sunlight can be seen visually on any of the recordings.</p> <p><strong>Usage:</strong></p> <p>Each zip archive file represents one of the six drone flight paths. The archives contain JPG files of size 4000x3000 pixels (RGB) and 640x512 (Thermal), separated into individual directories for RGB and Thermal:</p> <pre><code>├── Flug_100/ │ ├── RGB/ │ │ ├── DJI_0004.jpg │ │ ├── DJI_0006.jpg │ │ └── ... │ └── Thermal/ │ ├── DJI_0003_R.JPG │ ├── DJI_0005_R.JPG │ └── ... ├── Flug_101/ │ ├── RGB/ │ │ ├── DJI_0001.jpg │ │ ├── DJI_0003.jpg │ │ └── ... │ └── Thermal/ │ ├── DJI_0000_R.JPG │ ├── DJI_0002_R.JPG │ └── ... └── ...</code></pre> <p><strong>File Numbering/Naming Scheme:</strong></p> <p>The pairs of RGB + Thermal images follow the simple numbering scheme of: <strong>RGB = Thermal + 1</strong>.<br> For example, DJI_0003_R.jpg and DJI_0004.JPG are the matching Thermal and RGB images, respectively, that can be merged to form a single hyperspectral drone image.</p> <p>To perform the merging, we recommend using the <strong>merge_image_layers.py</strong> script provided by the associated <strong><a href="https://github.com/Helmholtz-AI-Energy/TBBRDet">TBBRDet software</a></strong> (see the scripts/alignment/ directory).</p> <p>For convenience, we have provided a CSV listing all annotated images in the <a href="https://doi.org/10.5281/zenodo.4767771"><strong>Thermal Bridges on Building Rooftops (TBBR) dataset</strong></a>. The CSV format is as follows:</p> <pre><code>Flight,RGB,Thermal Flug_100,DJI_0048.jpg,DJI_0047_R.JPG Flug_100,DJI_0050.jpg,DJI_0049_R.JPG ...</code></pre> <p> </p>
Linked collectors and determiners for: The Spider Collection at the Staatliches Museum für Naturkunde Karlsruhe.
Natural history specimen data linked to collectors and determiners held within, "The Spider Collection at the Staatliches Museum für Naturkunde Karlsruhe". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8277b324-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/8277b324-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8277b324-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/8277b324-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
CityCLIM 100m UltraHD LES Example Movies for Karlsruhe Nest
<p>This archive containes examples of georeferenced output movies from Large Eddy Simulations using the UltraHD model by Meteologix AG. These movies cover one model run of the operational UltraHD for the Karlsruhe region. Movies for the following parameters are included: Overview-RGB including land use and clouds, 2m temperature (in two color scales), skin temperature (in two color scales), 2m dewpoint, wind speed and the airflow parameter (describing advection of relative warm or cold air) and the moist airflow parameter (describing advection of relative moist or dry air). Since these movies were used as map overlays within the CityCLIM web frontend color scales are not included in this example movies. During the CityCLIM project such movies were produced from beginning of June 2023 till October 2024 for three different city regions (Luxemburg, Karlsruhe and Valencia).</p>
500 Hourly Synthetic Single-Family Household Heat Pump Load Profiles for Karlsruhe, Germany (2021)
<p>We created a synthetic dataset of 500 hourly single-family household water-to-water heat pump load profiles based on the weather profile of Karlsruhe, Germany in 2021. We have applied the open-source methodology published in [1], which applies a k-means clustering process to match daily weather profiles with randomly drawn empirical observations from the high-quality heat pump load profile dataset published in [2]. We have selected a number of 5 clusters, for a good balance between variance of profiles and accuracy, as discussed in [1]. The dataset can be used for modeling large numbers of heat pumps in grid sections or energy communities. </p> <p>The unit of the measurement is Wh. Through the "SFH" identifier, the underlying, randomly drawn households from [2] can be identified. </p> <p>[1] Semmelmann, L., Jaquart, P., & Weinhardt, C. (2023). Generating synthetic load profiles of residential heat pumps: a k-means clustering approach. <em>Energy Informatics</em>, <em>6</em>(Suppl 1), 37.</p> <p>[2] Schlemminger, M., Ohrdes, T., Schneider, E., & Knoop, M. (2022). Dataset on electrical single-family house and heat pump load profiles in Germany. <em>Scientific data</em>, <em>9</em>(1), 56.</p>
Linked collectors and determiners for: Fungus Collections at Staatliches Museum für Naturkunde Karlsruhe (Herbarium KR).
Natural history specimen data linked to collectors and determiners held within, "Fungus Collections at Staatliches Museum für Naturkunde Karlsruhe (Herbarium KR)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/61a9ca38-b62f-11e2-afcb-00145eb45e9a">https://bionomia.net/dataset/61a9ca38-b62f-11e2-afcb-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/61a9ca38-b62f-11e2-afcb-00145eb45e9a">https://gbif.org/dataset/61a9ca38-b62f-11e2-afcb-00145eb45e9a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Staatliches Museum für Naturkunde Karlsruhe_Abteilung Biowissenschaften - Referat Zoologie_Oribatida_SMNK-Taxonomische Belegsammlung ORIB.
Natural history specimen data linked to collectors and determiners held within, "Staatliches Museum für Naturkunde Karlsruhe_Abteilung Biowissenschaften - Referat Zoologie_Oribatida_SMNK-Taxonomische Belegsammlung ORIB". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a7ab3af6-0f58-4760-9f74-19b4a6e75688">https://bionomia.net/dataset/a7ab3af6-0f58-4760-9f74-19b4a6e75688</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a7ab3af6-0f58-4760-9f74-19b4a6e75688">https://gbif.org/dataset/a7ab3af6-0f58-4760-9f74-19b4a6e75688</a>. Formatted as a Frictionless Data package.
Baden from "Zur Anthropologie der Badener. Bericht über die von der Anthropologischen Kommission des Karlsruher Altertumsvereins an Wehrpflichtigen und Mittelschülern vorgenommenen Untersuchungen, etc".
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249380.5984.jpg">https://4dcity.org/imgupload/1652249380.5984.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm8.staticflickr.com%2F7454%2F11250175254_f65c5467bb_o.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm8.staticflickr.com%2F7454%2F11250175254_f65c5467bb_o.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249380.5984.jpg<br>Image Dimensions: 400x617<br>Megapixels: 0.25 MP<br>Filesize: 65.01 KB<br>
Baden from "Zur Anthropologie der Badener. Bericht über die von der Anthropologischen Kommission des Karlsruher Altertumsvereins an Wehrpflichtigen und Mittelschülern vorgenommenen Untersuchungen, etc".
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249376.4666.jpg">https://4dcity.org/imgupload/1652249376.4666.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2879%2F11249504283_c8bfea6f4d_o.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2879%2F11249504283_c8bfea6f4d_o.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249376.4666.jpg<br>Image Dimensions: 400x634<br>Megapixels: 0.25 MP<br>Filesize: 66.00 KB<br>
Baden from "Zur Anthropologie der Badener. Bericht über die von der Anthropologischen Kommission des Karlsruher Altertumsvereins an Wehrpflichtigen und Mittelschülern vorgenommenen Untersuchungen, etc".
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249376.466.jpg">https://4dcity.org/imgupload/1652249376.466.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2866%2F11252512506_5442ca1304_o.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2866%2F11252512506_5442ca1304_o.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249376.466.jpg<br>Image Dimensions: 400x617<br>Megapixels: 0.25 MP<br>Filesize: 56.28 KB<br>
Baden from "Zur Anthropologie der Badener. Bericht über die von der Anthropologischen Kommission des Karlsruher Altertumsvereins an Wehrpflichtigen und Mittelschülern vorgenommenen Untersuchungen, etc".
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249375.2418.jpg">https://4dcity.org/imgupload/1652249375.2418.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2818%2F11254166235_455a573193_o.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2818%2F11254166235_455a573193_o.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249375.2418.jpg<br>Image Dimensions: 400x607<br>Megapixels: 0.24 MP<br>Filesize: 56.13 KB<br>
Baden from "Zur Anthropologie der Badener. Bericht über die von der Anthropologischen Kommission des Karlsruher Altertumsvereins an Wehrpflichtigen und Mittelschülern vorgenommenen Untersuchungen, etc".
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1652249376.4592.jpg">https://4dcity.org/imgupload/1652249376.4592.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2861%2F11250047434_48f9849ae6_o.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Ffarm3.staticflickr.com%2F2861%2F11250047434_48f9849ae6_o.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1652249376.4592.jpg<br>Image Dimensions: 400x626<br>Megapixels: 0.25 MP<br>Filesize: 65.63 KB<br>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.