Geographic data Visualisation and Map Generation
| Main Author: | Pandya, Pranav |
|---|---|
| Other Authors: | Hadiya, Kartikey |
| Format: | Dataset |
| Terbitan: |
Mendeley
, 2019
|
| Subjects: | |
| Online Access: |
https:/data.mendeley.com/datasets/t98c6t6ccr |
| ctrlnum |
0.17632-t98c6t6ccr.1 |
|---|---|
| fullrecord |
<?xml version="1.0"?>
<dc><creator>Pandya, Pranav</creator><title>Geographic data Visualisation and Map Generation</title><publisher>Mendeley</publisher><description>This project is one of the academic projects given to us in the Geographic Information System (GIS) Course.
Created by: Pranav Pandya (Me) and
Kartikey Hadiya
We sampled information for pollution emission in Delhi, India.
Pollution data was obtained from https://data.gov.in/resources/real-time-air-quality-index-various-locations
Pollution index data can be obtained from https://cpcb.nic.in/RealTimeAirQualityData.php
Pollution data only had address of Indian Meteorological Department, so each station was located in Google Earth and pin points were added at each station.
Then in the sidebar containing those pins on right-click, a new folder was added and all the pins were added in that new folder in google earth. Then that folder was saved as kml file.
This kml file was uploaded to Mygeodata: https://mygeodata.cloud/converter/kml-to-csv and was converted into csv.
Then the csv file was opened and coordinates were copied in the pollution data file. That file was later saved as CSV and imported in ArcGIS and xy data was displayed.
Shapefile was obtained from web search, which is attached as well. That shapefile was imported in ArcGIS and the final view was generated which is shown in the picture.</description><subject>Remote Sensing</subject><subject>Air Pollution</subject><subject>Geographic Information Systems</subject><subject>Data Visualization</subject><subject>Exploratory Spatial Data Analysis</subject><contributor>Hadiya, Kartikey</contributor><type>Other:Dataset</type><identifier>10.17632/t98c6t6ccr.1</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/t98c6t6ccr</relation><date>2019-11-02T16:24:05Z</date><recordID>0.17632-t98c6t6ccr.1</recordID></dc>
|
| format |
Other:Dataset Other |
| author |
Pandya, Pranav |
| author2 |
Hadiya, Kartikey |
| title |
Geographic data Visualisation and Map Generation |
| publisher |
Mendeley |
| publishDate |
2019 |
| topic |
Remote Sensing Air Pollution Geographic Information Systems Data Visualization Exploratory Spatial Data Analysis |
| url |
https:/data.mendeley.com/datasets/t98c6t6ccr |
| contents |
This project is one of the academic projects given to us in the Geographic Information System (GIS) Course.
Created by: Pranav Pandya (Me) and
Kartikey Hadiya
We sampled information for pollution emission in Delhi, India.
Pollution data was obtained from https://data.gov.in/resources/real-time-air-quality-index-various-locations
Pollution index data can be obtained from https://cpcb.nic.in/RealTimeAirQualityData.php
Pollution data only had address of Indian Meteorological Department, so each station was located in Google Earth and pin points were added at each station.
Then in the sidebar containing those pins on right-click, a new folder was added and all the pins were added in that new folder in google earth. Then that folder was saved as kml file.
This kml file was uploaded to Mygeodata: https://mygeodata.cloud/converter/kml-to-csv and was converted into csv.
Then the csv file was opened and coordinates were copied in the pollution data file. That file was later saved as CSV and imported in ArcGIS and xy data was displayed.
Shapefile was obtained from web search, which is attached as well. That shapefile was imported in ArcGIS and the final view was generated which is shown in the picture. |
| id |
IOS7969.0.17632-t98c6t6ccr.1 |
| institution |
Universitas Islam Indragiri |
| affiliation |
onesearch.perpusnas.go.id |
| institution_id |
804 |
| institution_type |
library:university library |
| library |
Teknologi Pangan UNISI |
| library_id |
2816 |
| collection |
Artikel mulono |
| repository_id |
7969 |
| city |
INDRAGIRI HILIR |
| province |
RIAU |
| shared_to_ipusnas_str |
1 |
| repoId |
IOS7969 |
| first_indexed |
2020-04-08T08:12:08Z |
| last_indexed |
2020-04-08T08:12:08Z |
| recordtype |
dc |
| _version_ |
1686587391954911232 |
| score |
17.538404 |