The GA CCC Impact Analysis Map products are a series of ESRI map templates used to map natural and man-made hazard events. They have been designed specifically to support GA's collaboration with EMA to provide situational awareness and exposure information for CCC Operations and Recovery.

This is Planning Dept. data that concerns the coast, but no description was provided.

The cladding elements are entries in relation to a regulatory provision (way width, odds, names of neighbouring municipalities.) or geometrical surface, linear or point indicative elements, dressing the graphic documents of the PLU or the POS. They are necessary for the paper edition of the applicable graphic documents. This may be, for example, a hold of a detail plan, a frame, a cartridge, a reminder for a writing, a draw to draw a rating, an equipment identification label

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This COVADIS data standard concerns communal map documents (CCs). This data standard provides a technical framework describing in detail how to dematerialise these town planning documents in a spatial database that can be used by a GIS tool and interoperable. This standard of data covers both the graphical plans of the sectors and the information overlaying them.This standard of COVADIS data has been developed on the basis of the specifications for the dematerialisation of planning documents created in 2012 by the CNIG, itself based on the consolidated version of the urban planning code dated 16 March 2012. The recommendations of these two documents are consistent even if their purpose is not the same. The COVADIS data standard provides definitions and a structure for organising and storing spatial data from communal maps in an infrastructure, while the CNIG specification serves to frame the digitisation of these data.Part C ‘Data Structure’ presented in this COVADIS standard provides additional recommendations for the storage of data files. These are specific choices for the common data infrastructure of the ministries responsible for agriculture and sustainable development, which do not apply outside their context.

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In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.

This specific data set refers to the 1197 cc 66 kW Euro 6 petrol engine that has been applied in the

The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:

• the engine taxonomy code,
• total driven kilometers over which the data was gathered,
• total time in hours over which the data was gathered,
• the number of vehicles which were tested to create the emission map,
• the DOI (Digital Object Identifier) reference,
• Which emission maps are available in the file.

The DOI http://doi.org/10.5281/zenodo.4268034 refers to a updated meta-data document that provides the full description of the standardized emission map.

Maps

## Overview

Maps is a dataset for object detection tasks - it contains Pools annotations for 4,613 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Cadastral service for Clear Creek County.NOTE: Parcels and Account Owner tables are updated MWF. Due to the view layer created from this service, no other data in this service is currently being updated as of 1/6/2025.

Sentinel2GlobalLULC is a deep learning-ready dataset of RGB images from the Sentinel-2 satellites designed for global land use and land cover (LULC) mapping. Sentinel2GlobalLULC v2.1 contains 194,877 images in GeoTiff and JPEG format corresponding to 29 broad LULC classes. Each image has 224 x 224 pixels at 10 m spatial resolution and was produced by assigning the 25th percentile of all available observations in the Sentinel-2 collection between June 2015 and October 2020 in order to remove atmospheric effects (i.e., clouds, aerosols, shadows, snow, etc.). A spatial purity value was assigned to each image based on the consensus across 15 different global LULC products available in Google Earth Engine (GEE). Our dataset is structured into 3 main zip-compressed folders, an Excel file with a dictionary for class names and descriptive statistics per LULC class, and a python script to convert RGB GeoTiff images into JPEG format. The first folder called "Sentinel2LULC_GeoTiff.zip" contains 29 zip-compressed subfolders where each one corresponds to a specific LULC class with hundreds to thousands of GeoTiff Sentinel-2 RGB images. The second folder called "Sentinel2LULC_JPEG.zip" contains 29 zip-compressed subfolders with a JPEG formatted version of the same images provided in the first main folder. The third folder called "Sentinel2LULC_CSV.zip" includes 29 zip-compressed CSV files with as many rows as provided images and with 12 columns containing the following metadata (this same metadata is provided in the image filenames): Land Cover Class ID: is the identification number of each LULC class Land Cover Class Short Name: is the short name of each LULC class Image ID: is the identification number of each image within its corresponding LULC class Pixel purity Value: is the spatial purity of each pixel for its corresponding LULC class calculated as the spatial consensus across up to 15 land-cover products GHM Value: is the spatial average of the Global Human Modification index (gHM) for each image Latitude: is the latitude of the center point of each image Longitude: is the longitude of the center point of each image Country Code: is the Alpha-2 country code of each image as described in the ISO 3166 international standard. To understand the country codes, we recommend the user to visit the following website where they present the Alpha-2 code for each country as described in the ISO 3166 international standard:https: //www.iban.com/country-codes Administrative Department Level1: is the administrative level 1 name to which each image belongs Administrative Department Level2: is the administrative level 2 name to which each image belongs Locality: is the name of the locality to which each image belongs Number of S2 images : is the number of found instances in the corresponding Sentinel-2 image collection between June 2015 and October 2020, when compositing and exporting its corresponding image tile For seven LULC classes, we could not export from GEE all images that fulfilled a spatial purity of 100% since there were millions of them. In this case, we exported a stratified random sample of 14,000 images and provided an additional CSV file with the images actually contained in our dataset. That is, for these seven LULC classes, we provide these 2 CSV files: A CSV file that contains all exported images for this class A CSV file that contains all images available for this class at spatial purity of 100%, both the ones exported and the ones not exported, in case the user wants to export them. These CSV filenames end with "including_non_downloaded_images". To clearly state the geographical coverage of images available in this dataset, we included in the version v2.1, a compressed folder called "Geographic_Representativeness.zip". This zip-compressed folder contains a csv file for each LULC class that provides the complete list of countries represented in that class. Each csv file has two columns, the first one gives the country code and the second one gives the number of images provided in that country for that LULC class. In addition to these 29 csv files, we provided another csv file that maps each ISO Alpha-2 country code to its original full country name. © Sentinel2GlobalLULC Dataset by Yassir Benhammou, Domingo Alcaraz-Segura, Emilio Guirado, Rohaifa Khaldi, Boujemâa Achchab, Francisco Herrera & Siham Tabik is marked with Attribution 4.0 International (CC-BY 4.0)

In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.

This specific data set refers to the 1798 cc 118 kW Euro 5 petrol engine that has been applied in the

The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:

the engine taxonomy code,

total driven kilometers over which the data was gathered,

total time in hours over which the data was gathered,

the number of vehicles which were tested to create the emission map,

the DOI (Digital Object Identifier) reference,

Which emission maps are available in the file.

The DOI http://doi.org/10.5281/zenodo.4268034 refers to a updated meta-data document that provides the full description of the standardized emission map.

In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.

This specific data set refers to the 11124 cc 44 kW Euro 3 petrol engine that has been applied in the Peugeot 106, 206, and Partner. Citroen Saxo, C2, C3, and Berlingo.

The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:

• the engine taxonomy code,
• total driven kilometers over which the data was gathered,
• total time in hours over which the data was gathered,
• the number of vehicles which were tested to create the emission map,
• the DOI (Digital Object Identifier) reference,
• Which emission maps are available in the file.

The DOI http://doi.org/10.5281/zenodo.4268034 refers to a updated meta-data document that provides the full description of the standardized emission map.

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The information contained in graphic documents of a PLU or POS urban planning document shall be added either for regulatory reasons or for information purposes: — the information which is to be annexed to the planning documents in accordance with Articles R123-13 and R123-14 of the Planning Code, — the information reported on the graphic documents for information purposes.

The cladding elements are entries in relation to a regulatory provision (way width, odds, names of neighbouring municipalities.) or geometrical surface, linear or point indicative elements, dressing the graphic documents of the PLU or the POS. They are necessary for the paper edition of the applicable graphic documents. This may be, for example, a hold of a detail plan, a frame, a cartridge, a reminder for a writing, a draw to draw a rating, an equipment identification label

ADMMR map collection: Mystic Mine Samples, CC Section FR 5310E, 4772N + 100 to 5263E, 4908N + 200; 1 in. to 20 feet; 28 x 36 in.

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MAPS – standing for MIDI Aligned Piano Sounds – is a database of MIDI-annotated piano recordings. MAPS has been designed in order to be released in the music information retrieval research community, especially for the development and the evaluation of algorithms for single-pitch or multipitch estimation and automatic transcription of music. It is composed by isolated notes, random-pitch chords, usual musical chords and pieces of music. The database provides a large amount of sounds obtained in various recording conditions.

N_PROCEDURE_URBA_ZSUP_019

These data describe the planning procedures in their latest known state, specifying their situation in terms of progress and effectiveness. On average, a planning procedure lasts three years.

This description is voluntarily limited to achieve a specific objective: show, through summary maps, the geographical distribution and progress of PLU procedures relevant to the management of urban and rural planning policies. These include planning procedures in preparation, revision or repeal. In order to allow an exhaustive summary of the progress of the procedures, the procedures of the past years which have led to urban planning documents which are now enforceable are kept in these data (a planning document is associated with them in the file N_DOCUMENT_URBA_ddd). On the other hand, old urban planning procedures (i.e. those that have resulted in planning documents that are no longer enforceable) and procedures cancelled before their completion are not kept in these data.