Spatio-Temporal Analysis of Land and Forest Fires in Indonesia Using MODIS Active Fire Dataset

2018 ◽  
pp. 105-127 ◽  
Author(s):  
Israr Albar ◽  
I. Nengah Surati Jaya ◽  
Bambang Hero Saharjo ◽  
Budi Kuncahyo ◽  
Krishna Prasad Vadrevu
Keyword(s):  
Forest Fires ◽  
Temporal Analysis ◽  
Active Fire ◽  
Spatio Temporal

Spatio-Temporal Typology of Land and Forest Fire in Sumatra

2016 ◽  
Vol 4 (1) ◽  
pp. 83 ◽  
Author(s):  
Israr Albar ◽  
I. Nengah Surati Jaya ◽  
Bambang Hero Saharjo ◽  
Budi Kuncahyo
Keyword(s):  
Forest Fires ◽  
Geographic Location ◽  
Temporal Analysis ◽  
Forest Area ◽  
Single Linkage ◽  
Active Fire ◽  
Linkage Method ◽  
Spatio Temporal ◽  
Key Indicators ◽  
Typology Analysis

<p>The characteristic of land and forest fires occurred in Indonesia are varied widely, following the variation of time within a year and geographic location. This paper describes how the spatio-temporal of forest and land fire typology was developed. The main objective of this study was to develop a spatio-temporal typology of forest and land fire by considering several key indicators that directly related to the density of active fire occurrence, such as percentage of forest area (x<sub>1</sub>), population density (x<sub>2</sub>), ratio of forest area to population (x<sub>3</sub>), ratio of plantation area to population (x<sub>4</sub>), ratio of agriculture area to population (x<sub>5</sub>), GRDP (x<sub>6</sub>), population growth (x<sub>7</sub>), deforestation growth (x<sub>8</sub>), plantation growth (x<sub>9</sub>) and dry agriculture growth (x<sub>10</sub>) as well as  MODIS-based fire hotspot. The typology analysis was performed using clustering techniques with Euclidean distance dissimilarity measure, where the grouping process was drawn with single linkage method. The temporal analysis showed that the highest occurrence of the fire hotspot was mainly found in the third quarter. It was found that the forest and land fire typology could be developed into three classes using variables x<sub>6</sub> and x<sub>7</sub> with overall accuracy of 78.15% or x<sub>1</sub>-x<sub>6</sub>-x<sub>7</sub> with overall accuracy of 78.8%.  No accuracy improvement was obtained when the typology was developed using five variables x<sub>1</sub>-x<sub>3</sub>-x<sub>4</sub>-x<sub>6</sub>-x<sub>7.</sub><em></em></p>

scholarly journals Automated location of active fire perimeters in aerial infrared imaging using unsupervised edge detectors

2018 ◽  
Vol 27 (4) ◽  
pp. 241 ◽  
Author(s):  
M. M. Valero ◽  
O. Rios ◽  
E. Pastor ◽  
E. Planas
Keyword(s):  
Forest Fires ◽  
Large Scale ◽  
Infrared Imaging ◽  
Weather Conditions ◽  
Automated System ◽  
Rate Of Spread ◽  
Active Fire ◽  
Edge Detectors ◽  
Spatio Temporal ◽  
Manual Tasks

A variety of remote sensing techniques have been applied to forest fires. However, there is at present no system capable of monitoring an active fire precisely in a totally automated manner. Spaceborne sensors show too coarse spatio-temporal resolutions and all previous studies that extracted fire properties from infrared aerial imagery incorporated manual tasks within the image processing workflow. As a contribution to this topic, this paper presents an algorithm to automatically locate the fuel burning interface of an active wildfire in georeferenced aerial thermal infrared (TIR) imagery. An unsupervised edge detector, built upon the Canny method, was accompanied by the necessary modules for the extraction of line coordinates and the location of the total burned perimeter. The system was validated in different scenarios ranging from laboratory tests to large-scale experimental burns performed under extreme weather conditions. Output accuracy was computed through three common similarity indices and proved acceptable. Computing times were below 1 s per image on average. The produced information was used to measure the temporal evolution of the fire perimeter and automatically generate rate of spread (ROS) fields. Information products were easily exported to standard Geographic Information Systems (GIS), such as GoogleEarth and QGIS. Therefore, this work contributes towards the development of an affordable and totally automated system for operational wildfire surveillance.

scholarly journals Spatialtemporal Patterns of MODIS Active Fire/Hotspots in Chiang Rai, Upper Northern Thailand and the Greater Mekong Subregion Countries During 2003-2015

2021 ◽  
pp. 121-131
Author(s):  
Chidsanuphong Chart-asa
Keyword(s):  
Forest Fires ◽  
Temporal Analysis ◽  
Northern Thailand ◽  
Open Burning ◽  
Active Fire ◽  
Haze Pollution ◽  
Administrative Unit ◽  
Radiative Power ◽  
In Fire ◽  
Current Monitoring

For the past decade, smoke-haze pollution from forest fires and open burning has been a yearly recurring problem over Chiang Rai and other provinces in Upper Northern Thailand, along with other countries in the Greater Mekong Sub-region. Remote-sensing active fire/ hotspot data are currently used for monitoring the forest fires and open burning in the sub-region. This study aimed to extend the current monitoring work by performing spatial and temporal analysis to examine the patterns, either globally or locally, of MODIS active fires/hotspots during the critical smoke-haze pollution periods from January to April in 2003-2015. Fire radiative power was used as a weight attribute for each active fire/hotspot. Administrative unit maps were used for aggregating data and creating spatial weight matrices. Results indicated that for all the years over the investigated period and based on detected locations, active fires/hotspots were overall clustered spatially across provincial, interprovincial, and international scales. Their density patterns were locally variable for each year, but the high concentrated zones, in terms of both fire counts and fire radiative powers, were consistently bounded in the hilly and mountainous areas, confirming that the forest fires and open burning problem keeps recurring in certain areas. When aggregated by administrative unit, the administrative boundaries with high active fires/hotspots, in terms of both fire counts and fire radiative powers, were spatially clustered, either globally or locally, but there was only an increasing trend of the clustering intensity in fire radiative powers, implying that the forest fires and open burning problem have become more severe in particular areas. These findings could be useful for further reviewing and strengthening current measures and plans of fire and smoke haze pollution management.

Spatio-Temporal Analysis of Frontal Midline Theta Rhythm in EEG during 3-D Maze Task

2009 ◽  
Vol 129 (10) ◽  
pp. 1778-1784
Author(s):  
Yasuaki Uehara ◽  
Keita Tanaka ◽  
Yoshinori Uchikawa ◽  
Bong-Soo Kim
Keyword(s):  
Theta Rhythm ◽  
Temporal Analysis ◽  
Maze Task ◽  
Frontal Midline Theta ◽  
Spatio Temporal

Spatio-temporal analysis and prediction of grain security in Shaanxi Province

2010 ◽  
Vol 17 (4) ◽  
pp. 770-775
Author(s):  
Ren YANG ◽  
Zhi-Yuan REN ◽  
Qian XU ◽  
Mei-Xia WANG
Keyword(s):  
Temporal Analysis ◽  
Shaanxi Province ◽  
Spatio Temporal ◽  
Grain Security

scholarly journals Spatio-Temporal Analysis of Water Quality Parameters in Machángara River with Nonuniform Interpolation Methods

Water ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 507 ◽  
Author(s):  
Iván Vizcaíno ◽  
Enrique Carrera ◽  
Margarita Sanromán-Junquera ◽  
Sergio Muñoz-Romero ◽  
José Luis Rojo-Álvarez ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Analysis ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Interpolation Methods ◽  
Spatio Temporal

scholarly journals Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran

GeoJournal ◽  
2021 ◽  
Author(s):  
R. Nasiri ◽  
S. Akbarpour ◽  
AR. Zali ◽  
N. Khodakarami ◽  
MH. Boochani ◽  
...  
Keyword(s):  
Incidence Rate ◽  
Temporal Analysis ◽  
Spatio Temporal
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