Name: INVESTIGATIVE WILDFIRE DATA FOR TURKEY/ NASA
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

INVESTIGATIVE WILDFIRE DATA FOR TURKEY/ NASA

BE CAREFUL OF THE FILE NAMES.

IT CONTAINS THE DATA NEEDED TO RESEARCH LATEST FOREST FIRES IN TURKEY.

PAY ATTENTION TO THE DATE INTERVALS. THESE ARE 7-11 DAILY DATA OF LAST TIMES.

fire _ nrt _ M _ C61 _ 212465 _ all _ countries.csv

This file is important for all countries becuase it contains fire data of last 11 days for all around the world

Content

Data on recent forest fires in Turkey, published with permission from NASA Portal.
The data was created based on the hotspots and obtained from the satellite.

3 SEPARATE SATELLITE DATA:

MODIS C6.1
SUOMI VIIRS C2
J1 VIIRS C1

GENERAL ATTRIBUTES

Latitude
Center of nominal 375 m fire pixel
Longitude
Center of nominal 375 m fire pixel
Bright_ti4
(Brightness temperature I-4)
VIIRS I-4: channel brightness temperature of the fire pixel measured in Kelvin.
Scan
(Along Scan pixel size)
The algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size.
Track
(Along Track pixel size)
The algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size.
Acq_Date
(Acquisition Date)
Date of VIIRS acquisition.
Acq_Time
(Acquisition Time)
Time of acquisition/overpass of the satellite (in UTC).
Satellite
N Suomi National Polar-orbiting Partnership (Suomi NPP)
Confidence
This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence values are set to low, nominal and high. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.

Please note:

Low confidence nighttime pixels occur only over the geographic area extending from 11° E to 110° W and 7° N to 55° S. This area describes the region of influence of the South Atlantic Magnetic Anomaly which can cause spurious brightness temperatures in the mid-infrared channel I4 leading to potential false positive alarms. These have been removed from the NRT data distributed by FIRMS.
Version
Version identifies the collection (e.g. VIIRS Collection 1) and source of data processing: Near Real-Time (NRT suffix added to collection) or Standard Processing (collection only).

"1.0NRT" - Collection 1 NRT processing.

"1.0" - Collection 1 Standard processing.

Bright_ti5
(Brightness temperature I-5)
I-5 Channel brightness temperature of the fire pixel measured in Kelvin.
FRP
(Fire Radiative Power)
FRP depicts the pixel-integrated fire radiative power in MW (megawatts). Given the unique spatial and spectral resolution of the data, the VIIRS 375 m fire detection algorithm was customized and tuned in order to optimize its response over small fires while balancing the occurrence of false alarms. Frequent saturation of the mid-infrared I4 channel (3.55-3.93 µm) driving the detection of active fires requires additional tests and procedures to avoid pixel classification errors. As a result, sub-pixel fire characterization (e.g., fire radiative power [FRP] retrieval) is only viable across small and/or low-intensity fires. Systematic FRP retrievals are based on a hybrid approach combining 375 and 750 m data. In fact, starting in 2015 the algorithm incorporated additional VIIRS channel M13 (3.973-4.128 µm) 750 m data in both aggregated and unaggregated format.

Satellite measurements of fire radiative power (FRP) are increasingly used to estimate the contribution of biomass burning to local and global carbon budgets. Without an associated uncertainty, however, FRP-based biomass burning estimates cannot be confidently compared across space and time, or against estimates derived from alternative methodologies. Differences in the per-pixel FRP measured near-simultaneously in consecutive MODIS scans are approximately normally distributed with a standard deviation (ση) of 26.6%. Simulations demonstrate that this uncertainty decreases to less than ~5% (at ±1 ση) for aggregations larger than ~50 MODIS active fire pixels. Although FRP uncertainties limit the confidence in flux estimates on a per-pixel basis, the sensitivity of biomass burning estimates to FRP uncertainties can be mitigated by conducting inventories at coarser spatiotemporal resolutions.

http://cedadocs.ceda.ac.uk/770/1/SEVIRI_FRP_documentdesc.pdf

Type
(Inferred hot spot type)
0 = presumed vegetation fire

1 = active volcano

2 = other static land source

3 = offshore detection (includes all detections over water)

DayNight
(Day or Night)

D= Daytime fire

N= Nighttime fire

Tables

Modis 2018 Bahrain

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_bahrain

11.06 KB
17 rows
15 columns


CREATE TABLE modis_2018_bahrain (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Bangladesh

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_bangladesh

63.92 KB
2289 rows
15 columns


CREATE TABLE modis_2018_bangladesh (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Barbados

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_barbados

11.24 KB
21 rows
15 columns


CREATE TABLE modis_2018_barbados (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Belarus

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_belarus

47.13 KB
1311 rows
15 columns


CREATE TABLE modis_2018_belarus (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Belgium

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_belgium

28.05 KB
705 rows
15 columns


CREATE TABLE modis_2018_belgium (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Belize

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_belize

37.27 KB
862 rows
15 columns


CREATE TABLE modis_2018_belize (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Benin

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_benin

254.67 KB
12312 rows
15 columns


CREATE TABLE modis_2018_benin (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Bhutan

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_bhutan

17.24 KB
168 rows
15 columns


CREATE TABLE modis_2018_bhutan (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Bolivia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_bolivia

944.58 KB
49924 rows
15 columns


CREATE TABLE modis_2018_bolivia (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Bosnia And Herzegovina

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_bosnia_and_herzegovina

19.31 KB
249 rows
15 columns


CREATE TABLE modis_2018_bosnia_and_herzegovina (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Botswana

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_botswana

232.43 KB
10374 rows
15 columns


CREATE TABLE modis_2018_botswana (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Brazil

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_brazil

4.21 MB
231849 rows
15 columns


CREATE TABLE modis_2018_brazil (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 British Virgin Islands

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_british_virgin_islands

10.32 KB
3 rows
15 columns


CREATE TABLE modis_2018_british_virgin_islands (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Brunei Darussalam

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_brunei_darussalam

10.93 KB
14 rows
15 columns


CREATE TABLE modis_2018_brunei_darussalam (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Bulgaria

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_bulgaria

68.38 KB
2354 rows
15 columns


CREATE TABLE modis_2018_bulgaria (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Burkina Faso

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_burkina_faso

212.76 KB
9981 rows
15 columns


CREATE TABLE modis_2018_burkina_faso (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Burundi

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_burundi

23.03 KB
366 rows
15 columns


CREATE TABLE modis_2018_burundi (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Cambodia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_cambodia

496.38 KB
28815 rows
15 columns


CREATE TABLE modis_2018_cambodia (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Cameroon

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_cameroon

757.22 KB
42718 rows
15 columns


CREATE TABLE modis_2018_cameroon (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Canada

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_canada

1.24 MB
63707 rows
15 columns


CREATE TABLE modis_2018_canada (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Cape Verde

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_cape_verde

10.64 KB
8 rows
15 columns


CREATE TABLE modis_2018_cape_verde (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Central African Republic

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_central_african_republic

2.74 MB
188621 rows
15 columns


CREATE TABLE modis_2018_central_african_republic (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Chad

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_chad

904.79 KB
51229 rows
15 columns


CREATE TABLE modis_2018_chad (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 Chile

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_chile

162.27 KB
7172 rows
15 columns


CREATE TABLE modis_2018_chile (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);

Modis 2018 China

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_china

1.55 MB
78673 rows
15 columns


CREATE TABLE modis_2018_china (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" DOUBLE,
  "track" DOUBLE,
  "acq_date" TIMESTAMP,
  "acq_time" BIGINT,
  "satellite" VARCHAR,
  "instrument" VARCHAR,
  "confidence" BIGINT,
  "version" DOUBLE,
  "bright_t31" DOUBLE,
  "frp" DOUBLE,
  "daynight" VARCHAR,
  "type" BIGINT
);