Raw lidar data consist of positions (x, y) and intensity values. They must undergo a classification process before individual points can be identified as belonging to ground, building, vegetation, etc., features. By completing this tutorial, you will become comfortable with the following skills:Converting .zlas files to .las for editing,Reassigning LAS class codes,Using automated lidar classification tools, andUsing 2D and 3D features to classify lidar data.Software Used: ArcGIS Pro 3.3Time to Complete: 60 - 90 minutesFile Size: 57mbDate Created: September 25, 2020Last Updated: September 27, 2024

LiDAR_Point_Clouds, Classified. AHD have been preocessed to conform to the Australian Height Datum and converted from files collected as swaths in to tiles of data. The file formats is LAS.

LAS is an industry format created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water

Lineage: Fugro Spatial Solutions (FSS) were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu National Park. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

This data represents LiDAR-derived classified LAS points for Columbia County, Wisconsin in 2011. Point classification uses semi-automated techniques on the point cloud to assign the feature type associated with each point. LiDAR points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. This data is also available as a series of tiles to enable downloads of smaller, more specific areas within the county. To access the tiled data, please visit: https://www.sco.wisc.edu/scoapps/lidar/tile-search/?layer=columbia

LiDAR_Point_Clouds, UNClassified. ELL Files swaths of flight collected data. Points are located by Elevation, Latitude and Longitude. The file formats is LAS.

LAS is an industry format created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water

Lineage: LIDAR Survey of the floodplains within Kakadu National Park conducted by Fugro Spatial Solutions for Geoscience Australia Fugro Spatial Solutions were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

In January 2020, the North Carolina Department of Transportation (NCDOT) began work on the Interstate 26 (I 26) highway widening project that involves a bridge crossing over the French Broad River (FBR) near Asheville, North Carolina. The U.S Geological Survey (USGS) in cooperation with the NCDOT conducted a pre-construction light detection and ranging (lidar) survey of the streambanks within a one-kilometer reach of the FBR at the bridge construction site in November 2019 (Whaling and others, 2023). In December 2021, a canoe-based repeat streambank lidar survey was collected approximately 23 months after construction began, with the purpose to monitor geomorphological changes to the streambank and inform the NCDOT of potential impacts from construction activities. The survey extended from 300 meters (m) upstream to 700 m downstream from the bridge. Two georeferenced lidar scans were collected; one of the right-descending bank and one of the left-descending bank. Three-dimensional points of the streambanks were collected with a canoe-mounted Velodyne VLP-16 laser scanner integrated with an SBG Systems Ellipse2-D inertial navigation systems (INS), which consists of dual Global Navigation Satellite Systems (GNSS) receivers and an inertial motion unit. The lidar scanner creates a “point cloud” of lidar returns and the INS computes the position and orientation of the points in three-dimensional space. The navigation solution from the INS was further improved in post processing. Ground points were identified in each point cloud with a Cloth Simulation Filter (Zhang and others, 2016) implemented in CloudCompare software (CloudCompare, 2018) and classified with code 2 (ground) according to the American Society for Photogrammetry and Remote Sensing (ASPRS) standard lidar point classes (ASPRS, 2011). Water-surface reflections were identified and classified as code 7 (low noise; ASPRS, 2011). All other points in each point cloud were classified as code 1 (unclassified; ASPRS, 2011). The left and right streambank point clouds are provided as separate LAS files, an industry-standard binary format for storing large point cloud datasets. Each LAS file is provided with position and elevation data in three dimensions in units of meters, 8-bit scaled intensity, and the classification code. The data are projected in Universal Transverse Mercator (UTM) coordinate system, zone 17 north, horizontally referenced to the North American Datum of 1983 (NGS, 2018a), 2011 realization (NAD83 2011), and vertically referenced to the North American Vertical Datum of 1988 (NAVD88; NGS, 2018b).

Ce MNT a été créé à partir du jeu de données de terrain principal (MTD) de Hakai à l'aide de l'outil « MNT to raster » dans ArcGIS for Desktop d'ESRI à l'aide d'une méthode d'échantillonnage Natural Neighbour. Le DEM a été créé nativement à une résolution de 20 m. Ce MNE a été coupé sur le littoral de l'île. Une combinaison de différentes altitudes autour de l'île a été utilisée pour créer le rivage.

La grille de ce MNT est alignée ou « accrochée » à la grille raster des mesures de la canopée de végétation et des rasters associés.

Le MNT qui en résulte est un modèle d'élévation hydro-aplati à terre nue et donc considéré comme « topographiquement complet ». Chaque pixel représente l'altitude en mètres au-dessus du niveau moyen de la mer de la terre nue à cet endroit. Le système de référence vertical est « Canadian Geodetic Vertical Datum 1928 » (CGVD28).

Hakai a produit des DEM à différentes résolutions nativement à partir du MTD de données LiDAR. Veuillez utiliser le produit de résolution approprié de ceux produits par Hakai à des fins de recherche. Afin de maintenir l'homogénéité, il n'est pas recommandé d'échantillonnager/augmenter à partir de produits à haute résolution, car il peut introduire et propager des erreurs de grandeur variable dans les analyses en cours ; veuillez utiliser des produits déjà disponibles, et si vous avez besoin d'une résolution non disponible, contactez data@hakai.org afin d'obtenir un MNT produit directement à partir du MTD.

Les DEM topographiquement complets suivants ont été produits nativement à partir du DTM par Hakai :

MNT topographiquement complet de 3 m. Ce produit a été utilisé pour produire les jeux de données hydrologiques de Hakai (Streams and Watersheds) MNE topographiquement complet de 20 m. Compatible avec les mesures de la canopée de végétation de Hakai et les rasters associés. MNT topographiquement complet de 25 m Compatible avec les produits de données BCGov TRIM. MNE topographiquement complet de 30 m. Compatible avec les produits STRM.

Création d'un jeu de données de MNT principal :

Clouds de points LiDAR provenant de missions effectuées en 2012 et 2014 au-dessus de Calvert Island où ils sont chargés (XYZ uniquement) dans une classe d'entités ponctuelles dans une géodatabase ESRI.

Seul ground (classe 2) renvoie lorsqu'il est chargé sur la géodatabase.

Le « jeu de données de MNT » ESRI a été créé dans la même géodatabase à l'aide des points LiDAR comme points de masse intégrés.

Les lacs et étangs TEM Plus ayant des valeurs d'altitude moyennes au-dessus des miroirs des plans d'eau ont été utilisés comme lignes de fracture de remplacement dur pour obtenir un aplatissement hydro-aplati.

La géométrie limite minimale de tous les blocs de fichiers LAS contigus a été utilisée comme masque de clip souple lors de la création du jeu de données de MNT en tant que limite de projet.

Le système de coordonnées horizontales et la référence utilisés pour le jeu de données de MNT sont : UTM Zone 9 NAD1983 ; le système de référence vertical a été défini sur CGVD28. Les deux systèmes de référence correspondent au système de référence natif des nuages de points LiDAR.

L'espacement minimal des points défini lors de la création du jeu de données de MNT a été défini sur 1.

Face Recognition (Los 5)

## Overview

Face Recognition (Los 5) is a dataset for classification tasks - it contains Modelo Con Los 5 Integrantes annotations for 1,729 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 [MIT license](https://creativecommons.org/licenses/MIT).

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

NOAA Southeast AK Topobathymetric Lidar data were collected by NV5 Geospatial (NV5) using Leica Hawkeye 4X and Riegl 1560i systems and delivered to NOAA in four blocks. The NOAA Southeast AK Topobathymetric Lidar Block01 was acquired between 20210608 and 20210730 in 13 missions, Block02 was acquired between 20210611 and 20210730 in 14 missions, Block03 was acquired between 20210730 and 20210823 in 6 mission and Block 04 was acquired between 20210625 and 20210823 in 7 missions. The four block dataset includes topobathymetric data in a LAS format 1.4, point data record format 6, with the following classifications in accordance with project specifications and the American Society for Photogrammetry and Remote Sensing (ASPRS) classification standards: 1 - unclassified 2 - ground 7 Withheld -low noise 18 Withheld - high noise 40 - bathymetric bottom or submerged topography 41 - water surface 42 Synthetic- Chiroptera synthetic water surface 43 - submerged feature 45 - water column 64 - Submerged Aquatic Vegetation (SAV) 65 - overlap bathy bottom - temporally different from a separate lift 71 - unclassified associated with areas of overlap bathy bottom/temporal bathymetric differences 72 - ground associated with areas of overlap bathy bottom/temporal bathymetric differences 81 - water surface associated with areas of overlap bathy bottom/temporal bathymetric differences 82 Synthetic - Chiroptera synthetic water surface associated with areas of overlap bathy bottom/temporal bathymetric differences 85 - water column associated with areas of overlap bathy bottom/temporal bathymetric differences 1 Withheld - edge clip 1 Overlap Withheld - unrefracted green data from Chiroptera sensor

    The channel bits are as follows:
    0 - Riegl VQ1560 NIR channel A and Chiroptera green shallow laser
    1 - Riegl VQ1560 NIR channel B and Chiroptera/Hawkeye synthetic water surface
    2 - Hawkeye green deep laser
    3 - Chiroptera NIR

    The user byte is mapped as the following:
    0 - Riegl NIR channel A
    1 - Riegl NIR channel B
    10 - Chiroptera green shallow
    11 - Chiroptera green shallow 4X
    12 - Chiroptera green shallow synthetic
    20 - Hawkeye green deep
    21 - Hawkeye green deep 4X
    22 - Hawkeye green deep synthetic
    30 - Chiroptera NIR

Data in all blocks includes lidar intensity values, number of returns, return number, time, and scan angle. The block01 boundary extent covers 103,002 acres , the Block02 boundary extent covers 76,119 acres, the block03 boundary extent covers 55,929 acres and Block04 boundary extent covers 18,351 acres of the combined topographic and bathymetric project boundaries.

After the initial Southeast AK Topobathymetric Lidar submission, NOAA reviewed the data and provided NV5 Geospatial with a feedback edit review. NV5 Geospatial has corrected these feedback edits and incorporated them into the final block datasets. Additionally, green laser intensity values were normalized for depth for the dataset resulting in a full redelivery of all LAS files. LAS files were compiled in 500 m x 500 m tiles. The final classified lidar data were then transformed from ellipsoid (GRS80) to geoidal height (Geoid12b) and used to create topobathymetric DEMs in GeoTIFF format with 1m pixel resolution.

This dataset contains different collected datasets with crime data of many large cities. Below are the descriptions for each seperate dataset. Note: Dataset properties and column may differ from each other since the information was collected by the local police in different styles and situations.

1. Los Angeles

The Los Angeles dataset has the collected data on different crimes that happened in Los Angeles from 2000 up until May 2024. The columns are as follows:

• DR_NO - Division of Records Number: Official file number made up of a 2 digit year, area ID, and 5 digits

• Date Rptd - The date when the police found out about the crime

• Date OCC - The actual date of the crime

• Time OCC - In military time

• Area - The LAPD has 21 Community Police Stations referred to as Geographic Areas within the department. These Geographic Areas are sequentially numbered from 1-21.

• Area Name - The 21 Geographic Areas or Patrol Divisions are also given a name designation that references a landmark or the surrounding community that it is responsible for. For example 77th Street Division is located at the intersection of South Broadway and 77th Street, serving neighborhoods in South Los Angeles.

• Rpt Dist No - A four-digit code that represents a sub-area within a Geographic Area. All crime records reference the "RD" that it occurred in for statistical comparisons. Find LAPD Reporting Districts on the LA City GeoHub at http://geohub.lacity.org/datasets/c4f83909b81d4786aa8ba8a74a4b4db1_4

• Crm Cd - Indicates the crime committed. (Same as Crime Code 1)

• Crm Cd Desc - Defines the Crime Code provided.

• Mocodes - Modus Operandi: Activities associated with the suspect in commission of the crime.

• Vict Age - The age of the victim

• Vict Sex - The gender of the victim. They are as follows:

  • M - Male
  • F - Female
  • X - Unknown

• Vict Descent - Descent Code:

  • A - Other Asian
  • B - Black
  • C - Chinese
  • D - Cambodian
  • F - Filipino
  • G - Guamanian
  • H - Hispanic/Latin/Mexican
  • I - American Indian/Alaskan Native
  • J - Japanese
  • K - Korean
  • L - Laotian
  • O - Other
  • P - Pacific Islander
  • S - Samoan
  • U - Hawaiian
  • V - Vietnamese
  • W - White
  • X - Unknown
  • Z - Asian Indian

• Premis Cd - The type of structure, vehicle, or location where the crime took place.

• Premis Desc - Defines the Premise Code provided.

• Weapon Used Cd - The type of weapon used in the crime.

• Status - Status of the case. (IC is the default)

• Status Desc - Defines the Status Code provided.

• Crm Cd 1 - Indicates the crime committed. Crime Code 1 is the primary and most serious one. Crime Code 2, 3, and 4 are respectively less serious offenses. Lower crime class numbers are more serious.

• Crm Cd 2 - May contain a code for an additional crime, less serious than Crime Code 1.

• Crm Cd 3 - May contain a code for an additional crime, less serious than Crime Code 1.

• Crm Cd 4 - May contain a code for an additional crime, less serious than Crime Code 1.

• Location - Street address of crime incident rounded to the nearest hundred block to maintain anonymity.

• Cross Street - Cross Street of rounded Address

• LAT - Latitude

• LON - Longitude

This dataset has 28 columns and 944K rows. I hope you will find it useful. God bless you

1. Chicago

This dataset contains crime data on Chicago, from 2001 to present. The columns are as follows:

• ID - Unique Identifier for the record

• Case Number - The Chicago Police Department RD Number (Records Division Number), which is unique to the incident.

• Date - Date when the incident occurred. this is sometimes a best estimate.

• Block - The partially redacted address where the incident occurred, placing it on the same block as the actual address.

• IUCR - The Illinois Unifrom Crime Reporting code. This is directly linked to the Primary Type and Description. See the list of IUCR codes at https://data.cityofchicago.org/d/c7ck-438e..

• Primary Type - The primary description of the IUCR code.

• Description - The secondary description of the IUCR code, a subcategory of the primary description.

• Location Description - Description of the location where the incident occurred.

• Arrest - Indicates whether an arrest was made.

• Domestic - Indicates whether the incident was domestic-related as defined by the Illinois Domestic Violence Act.

• Beat - Indicates the beat where the incident occurred. A beat is the smallest police geographic area – each beat has a dedicated police beat car. Three to five beats make up a police sector, and three sectors make up a police district. The Chicago Police Department has 22 police districts. See the beats at https://data.cityofchicago.org/d/aerh-rz74.

• Distric...

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Linear Water Features includes single-line drainage water features and artificial path features that run through double-line drainage features such as rivers and streams, and serve as a linear representation of these features. The artificial path features may correspond to those in the USGS National Hydrographic Dataset (NHD). However, in many cases the features do not match NHD equivalent feature and will not carry the NHD metadata codes. These features have a MAF/TIGER Feature Classification Code (MTFCC) beginning with an "H" to indicate the super class of Hydrographic Features.

This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. The dataset contains 2,083,227 rows and 29 columns.

Column name	Description
DR_NO	Division of Records Number: Official file number made up of a 2 digit year, area ID, and 5 digits
Date Rptd	MM/DD/YYYY
DATE OCC	MM/DD/YYYY
TIME OCC	In 24 hour military time.
AREA	The LAPD has 21 Community Police Stations referred to as Geographic Areas within the department. These Geographic Areas are sequentially numbered from 1-21.
AREA NAME	The 21 Geographic Areas or Patrol Divisions are also given a name designation that references a landmark or the surrounding community that it is responsible for.
Crm Cd	Indicates the crime committed. (Same as Crime Code 1)
Crm Cd Desc	Defines the Crime Code provided.
Mocodes	Modus Operandi: Activities associated with the suspect in commission of the crime
Vict Age	Victim age
Vict Sex	F - Female M - Male X - Unknown
Vict Descent	Descent Code: A - Other Asian B - Black C - Chinese D - Cambodian F - Filipino G - Guamanian H - Hispanic/Latin/Mexican I - American Indian/Alaskan Native J - Japanese K - Korean L - Laotian O - Other P - Pacific Islander S - Samoan U - Hawaiian V - Vietnamese W - White X - Unknown Z - Asian Indian
Premis Cd	The type of structure, vehicle, or location where the crime took place.
Premis Desc	Defines the Premise Code provided
Weapon Used Cd	The type of weapon used in the crime.
Weapon Desc	Defines the Weapon Used Code provided.
Status	Status of the case. (IC is the default)
Status Desc	Defines the Status Code provided.
Crm Cd 1	Indicates the crime committed. Crime Code 1 is the primary and most serious one. Crime Code 2, 3, and 4 are respectively less serious offenses. Lower crime class numbers are more serious.
Crm Cd 2	May contain a code for an additional crime, less serious than Crime Code 1.
Crm Cd 3	May contain a code for an additional crime, less serious than Crime Code 1
Crm Cd 4	May contain a code for an additional crime, less serious than Crime Code 1.
LOCATION	Street address of crime incident rounded to the nearest hundred block to maintain anonymity.
Cross Street	Cross Street of rounded Address.
LAT	Latitude
LON	Longtitude

MakeHealth datathon [Website]

Códigos Presentados en el entrenamiento de Machine Learning

• Regresión
• Clasificación

Descripción del Problema

En los últimos años el dengue en el departamento del Cauca ha presentado una tendencia de aumento, actualmente en situación de alerta con 192 casos reportados en el transcurso del 2022; cabe resaltar que, durante los años 2020 y 2021, este departamento también estuvo en situación de alerta, ya que su comportamiento epidemiológico superó el límite esperado. Este conjunto de datos tiene como fin priorizar los barrios en los municipios de Piamonte, Patía y Miranda donde el riesgo por dengue se ha incrementado en el periodo de tiempo (2015-2021) para ello cuentas con los siguientes dataset 1) casos de dengue georreferenciados por centroide o geocodificados por la dirección de procedencia del caso con variables como la edad, el sexo, ocupación y pertenencia étnica, 2) muestreo entomológico de adultos realizado en el intradomicilio por primera vez en los municipios de estudio y 3) datos meteorológicos de dos tipos: uno proveniente de estaciones meteorológicas in situ y otro con la información a nivel de cada municipio en formato MSWX. Te proponemos el siguiente reto: estratificar haciendo uso de la inteligencia artificial los barrios en cada municipio que son conglomerados de riesgo epidemiológico y entomológico, adicionalmente dispondrás de un dataset con variables meteorológicas que podrás utilizar tanto en la predicción de la distribución potencial de especies de vectores como en la elaboración de modelos de predicción para el dengue a escala de barrio.

Descripción del Dataset

For dataset description in Spanish and English use these files - Para la descripción del dataset use estos archivos

• Spanish: Dataset Dengue (Espanol).pdf
• English: Dengue Dataset.pdf

Esta dataset se compone de 3 partes: 1. Datos Entomológicos (Datos sobre el vector) 2. Casos de Dengue Georeferenciados 3. Datos Meteorológicos

1. Datos Entomológicos (Datos sobre el vector)

Los datos entomológicos se encuentran para 3 municipios en el archivo y contienen las columnas:

entomologico_clean.csv: Contiene las variables: * ‘id’: Identificador del objeto * ‘individualCount’: Conteo de ejemplares * ‘sex’: Cantidad de cada sexo * ‘organismRemarks’: Comentarios sobre los ejemplares * ‘eventID’: Barrio de recolección * ‘eventDate’: Fecha de recolección * ‘locationID’: Código de Municipio * ‘county’: Nombre del Municipio * ‘locality’: Lugar de la recolección * ‘verbatimElevation’: Elevación de la recolección * ‘decimalLatitude’: Latitud * ‘decimalLongitude’: Longitud * ‘scientificName’: Nombre cientifico * ‘higherClassification’: Arbol de clasificación de la especie * ‘genus’: Genero del ejemplar * ‘subgenus’ : Subgénero del ejemplar * ‘specificEpithet’: epíteto específico * ‘vernacularName’: nombre vernáculo

2. Casos de Dengue Georeferenciados

Los casos de dengue georeferenciados se encuentran para 3 municipios y contienen las columnas:

cases_clean.csv: Contiene las variables:

• ‘’OBJECTID’: Identificador del objeto
• ‘Loc_name’: nombre del localizador participante que se utiliza para geocodificar o georreferenciar la dirección
• ‘Longitud’: Longitud. Se utilizó el máximo de decimales disponibles
• ‘Latitud’: Latitud. Se utilizó el máximo de decimales disponibles
• ‘Proceso’: Geocodificación o Georreferenación según corresponda
• ‘Match_addr’: Nombre del barrio, de la vereda o ubicación manual usando la capa de Open Street Maps (OSM)
• ‘Barrio_OSM':Barrio correspondiente con la capa de polígonos de barrio descargada desde el website de OSM
• ‘Sexo’: M masculino, F femenino
• ‘Edad’: 1 - 100
• 'Ocupación ‘: La codificación de la ocupación está a partir de la Clasificación Internacional Uniforme de Ocupaciones (CIUO 88)
• 'Pertenencia etnica’: 1. indigena, 2, rom o gitano, 3. raizal, 4. palenquero, 5. negro, mulato afrocolombiano, 6. Otro
• ‘fec_consulta’: fecha en la que realizó la consulta a la UPGD
• ‘ini_sintomas’: fecha en la que reporta el inicio de síntomas
• ‘locationID’: Código de municipio
• ‘county’: Nombre del municipio

3. Datos Meteorológicos

Estos datos meteorológicos se encuentran para los 3 municipios en los siguientes archivos:

1. En formato mswx:
2. H_mswx_2015_2022.nc: Humedad Relativa - % HR
3. Pr_mswx_2015_2022.nc: Precipitación total - mm/día
4. Tmax_mswx_2015_2022.nc: Temperatura máxima - °C
5. <b...

Dataset

This dataset was created by Gary Hutson

Released under GPL 2

Contents

The dataset captures instances of criminal activities within the City of Los Angeles, spanning from 2020 onwards. The information originates from handwritten crime reports and, consequently, might contain certain inaccuracies. Instances of missing data in location fields are indicated as (0°, 0°). To uphold privacy, address details are generalized to the closest hundred-block level. It's important to note that the accuracy of this dataset is comparable to the accuracy of the database.

Below are the details of various columns in the dataset:

| Column Name | Data Type | Description | Type | | ----- | ----- | | DR_NO |Text | Division of Records Number: Official file number made up of a 2 digit year, area ID, and 5 digits | Plain Text | | Date Rptd | Floating Timestamp | MM/DD/YYYY | Date & Time | | DATE OCC | Floating Timestamp | MM/DD/YYYY | Date & Time | | TIME OCC | Text | In 24 hour military time. | Plain Text | | AREA | Text | The LAPD has 21 Community Police Stations referred to as Geographic Areas within the department. These Geographic Areas are sequentially numbered from 1-21. | Plain Text | | AREA NAME | Text | The 21 Geographic Areas or Patrol Divisions are also given a name designation that references a landmark or the surrounding community that it is responsible for. For example 77th Street Division is located at the intersection of South Broadway and 77th Street, serving neighborhoods in South Los Angeles. | Plain Text | | Rpt Dist No | Text | A four-digit code that represents a sub-area within a Geographic Area. All crime records reference the "RD" that it occurred in for statistical comparisons. Find LAPD Reporting Districts on the LA City GeoHub at http://geohub.lacity.org/datasets/c4f83909b81d4786aa8ba8a74a4b4db1_4 | Plain Text | | Part 1-2 | Number | Number | | |Crm Cd |Text | Indicates the crime committed. (Same as Crime Code 1) | Plain Text | | Crm Cd Desc | Text | Defines the Crime Code provided. | Plain Text | | Mocodes | Text | Modus Operandi: Activities associated with the suspect in commission of the crime. | Plain Text | | Vict Age |Text | Two character numeric | Plain Text | |Vict Sex | Text | F - Female M - Male X - Unknown | Plain Text | | Vict Descent| Text | Descent Code: A - Other Asian B - Black C - Chinese D - Cambodian F - Filipino G - Guamanian H - Hispanic/Latin/Mexican I - American Indian/Alaskan Native J - Japanese K - Korean L - Laotian O - Other P - Pacific Islander S - Samoan U - Hawaiian V - Vietnamese W - White X - Unknown Z - Asian Indian | Plain Text | | Premis Cd |Number | The type of structure, vehicle, or location where the crime took place. | Number | | Premis | Desc | Text | Defines the Premise Code provided. | Plain Text | | Weapon Used Cd | Text | The type of weapon used in the crime. | Plain Text | | Weapon Desc | Text | Defines the Weapon Used Code provided. | Plain Text | | Status | Text | Status of the case. (IC is the default) | Plain Text | | Status Desc | Text | Defines the Status Code provided. | Plain Text | | Crm Cd 1 | Text | Indicates the crime committed. Crime Code 1 is the primary and most serious one. Crime Code 2, 3, and 4 are respectively less serious offenses. Lower crime class numbers are more serious. | Plain Text | | Crm Cd 2 |Text | May contain a code for an additional crime, less serious than Crime Code 1. | Plain Text | | Crm Cd 3 | Text | May contain a code for an additional crime, less serious than Crime Code 1. | Plain Text | | Crm Cd 4 | Text | May contain a code for an additional crime, less serious than Crime Code 1. | Plain Text | | LOCATION | Text | Street address of crime incident rounded to the nearest hundred block to maintain anonymity. | Plain Text | | Cross Street | Text | Cross Street of rounded Address | Plain Text | | LAT |Number | Latitude | Number | | LON | Number | Longtitude | Number |

This is a pdf file link for Mocode's reference feel free to download

Description

This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data.

Variable Definitions

Variable	Description	Type
DR_NO	Division of Records Number: Official file number made up of a 2 digit year, area ID, and 5 digits	Alphanumeric/String
Date Rptd	Date reported for the crime- MM/DD/YYYY	Date and Time
DATE OCC	Crime occured on the date -MM/DD/YYYY	Date and Time
TIME OCC	The time the crime occured- In 24 hour military time.	Numeric/String
AREA	The LAPD has 21 Community Police Stations referred to as Geographic Areas within the department. These Geographic Areas are sequentially numbered from 1-21.	Numeric/String
AREA NAME	The 21 Geographic Areas or Patrol Divisions are also given a name designation that references a landmark or the surrounding community that it is responsible for. For example 77th Street Division is located at the intersection of South Broadway and 77th Street, serving neighborhoods in South Los Angeles.	String
Rpt Dist No	A four-digit code that represents a sub-area within a Geographic Area. All crime records reference the "RD" that it occurred in for statistical comparisons. Find LAPD Reporting Districts on the LA City GeoHub at http://geohub.lacity.org/datasets/c4f83909b81d4786aa8ba8a74a4b4db1_4	Numeric/String
Part 1-2	Part 1 refers to serious felonies and Part 2 refers to less serious crimes	Numeric
Crm Cd	Indicates the crime committed. (Same as Crime Code 1)	Numeric/String
Crm Cd Desc	Defines the Crime Code provided.	String
Mocodes	Modus Operandi: Activities associated with the suspect in commission of the crime.See attached PDF for list of MO Codes in numerical order. https://data.lacity.org/api/views/y8tr-7khq/files/3a967fbd-f210-4857-bc52-60230efe256c?download=true&filename=MO%20CODES%20(numerical%20order).pdf	Numeric/String
Vict Age	Age of the victim	Numeric/String
Vict Sex	F - Female M - Male X - Unknown	String
Vict Descent	Descent Code: A - Other Asian B - Black C - Chinese D - Cambodian F - Filipino G - Guamanian H - Hispanic/Latin/Mexican I - American Indian/Alaskan Native J - Japanese K - Korean L - Laotian O - Other P - Pacific Islander S - Samoan U - Hawaiian V - Vietnamese W - White X - Unknown Z - Asian Indian	String
Premis Cd	The type of structure, vehicle, or location where the crime took place.	Numeric
Premis Desc	Defines the Premise Code provided.	String
Weapon Used Cd	The type of weapon used in the crime.	Numeric/String
Weapon Desc	Defines the Weapon Used Code provided.	String
Status	Status of the case. (IC is the default)	String
Status Desc	Defines the Status Code provided.	String
Crm Cd 1	Indicates the crime committed. Crime Code 1 is the primary and most serious one. Crime Code 2, 3, and 4 are respectively less serious offenses. Lower crime class numbers are more serious.	Numeric/String
Crm Cd 2	May contain a code for an additional crime, less serious than Crime Code 1.	Numeric/String
Crm Cd 3	May contain a code for an additional crime, less serious than Crime Code 1.	Numeric/String
Crm Cd 4	May contain a code for an additional crime, less serious than Crime Code 1.	Numeric/String
LOCATION	Street address of crime incident rounded to the nearest hundred block to maintain anonymity	String
Cross Street	Cross Street of rounded Address	String
LAT	Latitude	Numeric
LON	Longtitude	Numeric

***NOTE:** For the Data type which we have mentioned as "Numeric/string", the original source desribed them as a plain text but the dataset consists of numerical values for that variable, so for easy understanding we have mentioned "Numeric/string".

Suggested Data Preprocessing

• Remove time from dates
• Convert Time variable values to actual time from numeric
• Create a new column including both latitude and longitude for easy da...