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 Paraguay

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_paraguay

582.94 KB
29829 rows
15 columns


CREATE TABLE modis_2018_paraguay (
  "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 Peru

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_peru

308.43 KB
13522 rows
15 columns


CREATE TABLE modis_2018_peru (
  "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 Philippines

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_philippines

117.22 KB
4718 rows
15 columns


CREATE TABLE modis_2018_philippines (
  "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 Poland

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_poland

32.03 KB
678 rows
15 columns


CREATE TABLE modis_2018_poland (
  "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 Portugal

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_portugal

48.81 KB
1310 rows
15 columns


CREATE TABLE modis_2018_portugal (
  "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 Puerto Rico

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_puerto_rico

12.84 KB
57 rows
15 columns


CREATE TABLE modis_2018_puerto_rico (
  "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 Qatar

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_qatar

22.81 KB
382 rows
15 columns


CREATE TABLE modis_2018_qatar (
  "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 Republic Of Congo

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_republic_of_congo

447.23 KB
23148 rows
15 columns


CREATE TABLE modis_2018_republic_of_congo (
  "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 Republic Of Korea

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_republic_of_korea

40.48 KB
1124 rows
15 columns


CREATE TABLE modis_2018_republic_of_korea (
  "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 Reunion

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_reunion

28.03 KB
624 rows
15 columns


CREATE TABLE modis_2018_reunion (
  "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 Romania

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_romania

90.03 KB
3552 rows
15 columns


CREATE TABLE modis_2018_romania (
  "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 Russian Federation

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_russian_federation

4.91 MB
267093 rows
15 columns


CREATE TABLE modis_2018_russian_federation (
  "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 Rwanda

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_rwanda

15.03 KB
116 rows
15 columns


CREATE TABLE modis_2018_rwanda (
  "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 Saint Helena

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_saint_helena

10.19 KB
1 row
15 columns


CREATE TABLE modis_2018_saint_helena (
  "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 Saint Kitts And Nevis

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_saint_kitts_and_nevis

10.72 KB
9 rows
15 columns


CREATE TABLE modis_2018_saint_kitts_and_nevis (
  "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 Saint Vincent And The Grenadines

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_saint_vincent_and_the_grenadines

10.18 KB
1 row
15 columns


CREATE TABLE modis_2018_saint_vincent_and_the_grenadines (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" BIGINT,
  "track" BIGINT,
  "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 Samoa

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_samoa

11.67 KB
30 rows
15 columns


CREATE TABLE modis_2018_samoa (
  "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 Sao Tome And Principe

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_sao_tome_and_principe

10.5 KB
6 rows
15 columns


CREATE TABLE modis_2018_sao_tome_and_principe (
  "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 Saudi Arabia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_saudi_arabia

71 KB
2491 rows
15 columns


CREATE TABLE modis_2018_saudi_arabia (
  "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 Senegal

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_senegal

293.04 KB
15107 rows
15 columns


CREATE TABLE modis_2018_senegal (
  "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 Serbia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_serbia

98.7 KB
3936 rows
15 columns


CREATE TABLE modis_2018_serbia (
  "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 Sierra Leone

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_sierra_leone

355.25 KB
19931 rows
15 columns


CREATE TABLE modis_2018_sierra_leone (
  "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 Singapore

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_singapore

10.34 KB
3 rows
15 columns


CREATE TABLE modis_2018_singapore (
  "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 Sint Maarten

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_sint_maarten

10.19 KB
1 row
15 columns


CREATE TABLE modis_2018_sint_maarten (
  "latitude" DOUBLE,
  "longitude" DOUBLE,
  "brightness" DOUBLE,
  "scan" BIGINT,
  "track" BIGINT,
  "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 Slovakia

@kaggle.brsdincer_investigative_wildfire_data_for_turkey_nasa.modis_2018_slovakia

21.07 KB
367 rows
15 columns


CREATE TABLE modis_2018_slovakia (
  "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
);