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32 results for “Mapping damage”
Damage Absolute Probability map
<p>Damage Absolute Probability map is a layer in support to Area of Interest (AOI) definition for an earthquake event. It provides the spatial distribution, in the examined area, of the absolute values of probability of damage derived considering the most severe damage classes provided by loss assessment data</p>
Relative Potential Damage map
<p>Relative Potential Damage map is a layer in support to Area Of Interest (AOI) definition for an earthquake event. This index provides the indication of expected most affected areas</p>
Quantitative monitoring and mapping of the damage in Syria archeological site Afamia (Apamea).
<p>This data is associated with the paper</p> <p><strong>Remote sensing and map quantitative data in an armed conflict zone.</strong></p> <p><strong>Case study: Quantitative monitoring and mapping of the damage in Syria archeological site Afamia (Apamea).</strong></p> <p>This data is arranged in CSV file.</p> <p>TheCSV file (Data-Afamia-Syria-MOBAIED 2023) contains 143,426 rows and 9 columns that represent the 143,426 entities (points) which can be projected under an adapted GIS.</p> <p>The ID for each entity is specified at the column (A), the spatial coordinates are determined under WGS 84 / UTM zone 37N at the columns (B, C, D, E). </p> <p>The category of each entity is described for each of the years of observation at the columns (F, G, H, I) using the following code:</p> <p>(0) Outside of the archeological site Apamea</p> <p>(1) inside of the archeological site Apamea </p> <p>(2) Fields</p> <p>(3) Other</p> <p>(4) Intact Site</p> <p>(5) Intact Fields</p> <p>(7) Previous Clandestine Excavations</p> <p>(8) Recent Clandestine Excavations</p> <p>(9) Traces of former excavations</p>
Fig. 1. Early Jurassic map illustrating the previously studied areas for ventrally damaged ammonoids. 1 in Low durophagous predation on Toarcian (Early Jurassic) ammonoids in the northwestern Panthalassa shelf basin
Fig. 1. Early Jurassic map illustrating the previously studied areas for ventrally damaged ammonoids. 1, Dotternhausen, Germany (Taverne 2000; Klompmaker et al. 2009); 2, Lyme Regis, England (Andrew et al. 2010). The Toyora area was located in the northwestern part of the Panthalassa. Palaeogeographical map after Scotese (2001).
Offshore wind turbine damage probability maps and hub height TC wind speeds for U.S. Atlantic and Gulf Coasts exposed to historical and future tropical cyclones
<p>Damage probability maps for offshore wind turbines exposed to tropical cyclones (TCs) under both historical and future climate scenarios along the U.S. Atlantic and Gulf Coasts are presented in this dataset. TCs are generated using <a href="../records/10392725" target="_blank" rel="noopener">The Risk Analysis Framework for Tropical Cyclones (RAFT)</a>, forced by <a href="https://pcmdi.llnl.gov/CMIP6/" target="_blank" rel="noopener">CMIP6</a> historical and future global climate simulations. Maximum wind speeds for 20- and 50-year TCs are processed through a <a href="https://www.sciencedirect.com/science/article/pii/S0960148120311423">fragility function</a> specific to offshore wind (OSW) turbines in order to estimate the probability of damage – specifically yielding and buckling – based on wind speed intensity. </p> <p><strong>Included data:</strong></p> <ul> <li><strong>TC wind speeds:</strong> Peak 10-min mean hub height (90m) TC wind speed maps</li> <li><strong>Damage states:</strong> Yielding and Buckling probability maps for OSW turbines</li> <li><strong>Geographic coverage:</strong> U.S. Atlantic and Gulf Coasts (up to 200km from the shoreline)</li> <li><strong>Time periods:</strong> Historic (1980-2014) and Future (2066-2100)</li> </ul> <p><strong>Methodology:</strong></p> <ul> <li><strong>Tropical cyclone simulation:</strong> The RAFT TC model is used to simulate storms for historical and future climates using CMIP6 environmental conditions.</li> <li><strong>TC impact metric:</strong> Wind speeds associated with 20- and 50-year return period TCs are used to estimate the aerodynamic and sea wave loading on OSW turbines.</li> <li><strong>Fragility functions:</strong> Wind speeds are input into a fragility function developed for OSW turbines, estimating the probability of yielding and buckling damage.</li> <li><strong>Damage probability maps:</strong> The results consist of eight (8) gridded damage probability maps representing the likelihoods of yielding and buckling to OSW turbines from 20- and 50-year TCs under historical and future climatic conditions.</li> </ul> <p><strong>Potential Uses:</strong></p> <ul> <li>Assessing the spatial vulnerability of OSW infrastructure to TCs</li> <li>Supporting decision-making for the design and siting of turbines</li> <li>Evaluating the impact of climate change on the risk of damage to OSW infrastructure</li> </ul> <p>For further insights into this dataset, users are encouraged to refer to the associated paper: <a href="https://www.nature.com/articles/s43247-024-01887-6">https://www.nature.com/articles/s43247-024-01887-6</a></p> <p>This dataset offers valuable insights into the potential impact of TCs on offshore wind infrastructure, aiding in risk assessment and resilience planning for the renewable energy sector.</p> <p> </p>
Potential Damage map
<p>Potential Damage map is a layer in support to Area Of Interest definition for a Tsunami event. It provides the indication of areas where a higher level of damage from a tsunami event is expected</p>
7.8 Earthquake Damage Mapping in Turkey and Syria
<p>In the early hours of February 6th, 2023, a devastating earthquake of magnitude 7.8 in Gaziantep and magnitude 7.5 in Ekinözü struck Turkey and Syria, causing widespread loss of life and property. In the aftermath of the quake, more than 36,000 fatalities and numerous injuries were reported in one week. The unprecedented magnitude of the earthquake highlights the delicate nature of human life, yet it also underscores the resilience of the human spirit.</p> <p>To assist in the aftermath of this disaster, the present study aims to assess the damage caused by the earthquake through the analysis of Sentinel-1 satellite data. We adopt a combination of coherence and displacement parameters to create a damage map of the affected areas. First, we calculate the difference in coherence between pre- and post-earthquake images and retain only pixels with a coherence value higher than 0.25 and a negative change in coherence. The resulting change in coherence is expressed as a percentage (diff_coherence_percent) after converting it to a percentage by multiplying it by 100.</p> <p>Next, we enhance positive displacement values and take the absolute value of all displacement values, expressing the magnitude of displacement as a percentage (disp_percent) by dividing it by a threshold of 0.9 m and multiplying it by 100. Finally, we compute the damage percentage as the weighted average of both “diff_coherence_percent” and “disp_percent”, with equal weighting.</p> <p>The results of our study can provide valuable insights into the impact of the earthquake and help guide recovery efforts by providing a map of the damage caused by the quake. Advanced radar technology and satellite imagery highlight the importance of utilizing cutting-edge tools in studying natural disasters and their impacts on communities.</p>
CPD-seq mapping of UV damage formation and repair in yeast
GEO Series GSE79977. Saccharomyces cerevisiae. 8 samples. Type: Other.
CPD-seq map of UV damage formation in human fibroblasts
GEO Series GSE103487. Homo sapiens. 10 samples. Type: Other.
Nick-seq for singlenucleotide resolution genomic maps of DNA modifications and damage:DNA damage mapping
GEO Series GSE138070. Escherichia coli str. K-12 substr. DH10B. 8 samples. Type: Other.
Nick-seq for singlenucleotide resolution genomic maps of DNA modifications and damage:DNA PT modification mapping
GEO Series GSE138476. Salmonella enterica subsp. enterica serovar Cerro. 4 samples. Type: Other.
CPD-seq mapping of UV damage repair in rad16 mutant yeast
GEO Series GSE131101. Saccharomyces cerevisiae. 5 samples. Type: Other.
Genome-wide Map of R-Loop-Induced Damage Reveals How a Subset of R-Loops Contributes to Genomic Instability
GEO Series GSE110575. Saccharomyces cerevisiae. 14 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Genome wide mapping of DNA lesions by Repair Assisted Damage Detection sequencing – RADD-Seq
GEO Series GSE166843. Homo sapiens. 7 samples. Type: Other.
A damaged genome's transcriptional landscape through multilayered expression profiling around in situ-mapped DNA double-strand breaks
GEO Series GSE97589. Homo sapiens. 25 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Dynamic Maps of UV Damage Formation and Repair for the Human Genome
GEO Series GSE98025. Homo sapiens. 38 samples. Type: Other.
Genome-wide mapping of oxidative DNA damage via engineering of 8-oxoguanine DNA glycosylase
GEO Series GSE136862. Mus musculus. 6 samples. Type: Other.
Single-nucleotide resolution dynamic repair maps of UV damage in Saccharomyces cerevisiae genome
GEO Series GSE110621. Saccharomyces cerevisiae. 10 samples. Type: Other.
Human genome wide repair map of DNA damage caused by the cigarette smoke carcinogen benzo[a]pyrene
GEO Series GSE97675. Homo sapiens. 8 samples. Type: Other.
Global landscape mapping of chromatin accessibility in DNA damage-induced senescent human stromal cells
GEO Series GSE135481. Homo sapiens. 9 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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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.
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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.