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 Italy

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_italy

93.75 KB
3588 rows
15 columns


CREATE TABLE modis_2018_italy (
  "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 Jamaica

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_jamaica

18.27 KB
201 rows
15 columns


CREATE TABLE modis_2018_jamaica (
  "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 Japan

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_japan

101.33 KB
3567 rows
15 columns


CREATE TABLE modis_2018_japan (
  "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 Jordan

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_jordan

12.06 KB
42 rows
15 columns


CREATE TABLE modis_2018_jordan (
  "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 Kazakhstan

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_kazakhstan

657.11 KB
30807 rows
15 columns


CREATE TABLE modis_2018_kazakhstan (
  "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 Kenya

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_kenya

57.37 KB
1736 rows
15 columns


CREATE TABLE modis_2018_kenya (
  "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 Kosovo

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_kosovo

16.58 KB
161 rows
15 columns


CREATE TABLE modis_2018_kosovo (
  "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 Kuwait

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_kuwait

30.74 KB
609 rows
15 columns


CREATE TABLE modis_2018_kuwait (
  "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 Kyrgyzstan

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_kyrgyzstan

25.86 KB
458 rows
15 columns


CREATE TABLE modis_2018_kyrgyzstan (
  "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 Lao Pdr

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_lao_pdr

542.43 KB
28094 rows
15 columns


CREATE TABLE modis_2018_lao_pdr (
  "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 Latvia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_latvia

16.24 KB
146 rows
15 columns


CREATE TABLE modis_2018_latvia (
  "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 Lebanon

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_lebanon

12.01 KB
38 rows
15 columns


CREATE TABLE modis_2018_lebanon (
  "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 Lesotho

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_lesotho

18.07 KB
192 rows
15 columns


CREATE TABLE modis_2018_lesotho (
  "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 Liberia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_liberia

129.66 KB
5558 rows
15 columns


CREATE TABLE modis_2018_liberia (
  "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 Libya

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_libya

81 KB
3984 rows
15 columns


CREATE TABLE modis_2018_libya (
  "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 Lithuania

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_lithuania

13.29 KB
67 rows
15 columns


CREATE TABLE modis_2018_lithuania (
  "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 Luxembourg

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_luxembourg

13.84 KB
81 rows
15 columns


CREATE TABLE modis_2018_luxembourg (
  "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 Macedonia Former Yugoslav Republic Of

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_macedonia_former_yugoslav_republic_of

27.01 KB
546 rows
15 columns


CREATE TABLE modis_2018_macedonia_former_yugoslav_republic_of (
  "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 Madagascar

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_madagascar

1.08 MB
63161 rows
15 columns


CREATE TABLE modis_2018_madagascar (
  "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 Malawi

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_malawi

178.12 KB
8220 rows
15 columns


CREATE TABLE modis_2018_malawi (
  "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 Malaysia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_malaysia

89.97 KB
3376 rows
15 columns


CREATE TABLE modis_2018_malaysia (
  "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 Maldives

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_maldives

11.49 KB
30 rows
15 columns


CREATE TABLE modis_2018_maldives (
  "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 Mali

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_mali

494.8 KB
25430 rows
15 columns


CREATE TABLE modis_2018_mali (
  "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 Malta

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_malta

10.29 KB
2 rows
15 columns


CREATE TABLE modis_2018_malta (
  "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 Martinique

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_martinique

10.33 KB
3 rows
15 columns


CREATE TABLE modis_2018_martinique (
  "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
);