BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ESGRS - ECPv6.16.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:ESGRS
X-ORIGINAL-URL:https://www.esgrs.ae
X-WR-CALDESC:Events for ESGRS
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Dubai
BEGIN:STANDARD
TZOFFSETFROM:+0400
TZOFFSETTO:+0400
TZNAME:+04
DTSTART:20200101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Dubai:20211130T100000
DTEND;TZID=Asia/Dubai:20211130T110000
DTSTAMP:20260611T165802
CREATED:20211130T095259Z
LAST-MODIFIED:20240514T034146Z
UID:3698-1638266400-1638270000@www.esgrs.ae
SUMMARY:Spatio-temporal Forest fire monitoring using spatial-statistical and Geo-spatial analysis of factors determining forest fire in Margalla Hills\, Islamabad\, Pakistan
DESCRIPTION:The spatio-temporal changes in burnt area were identified using Landsat satellite data and modeling was used to predict the fire ignition and size distribution daily and yearly. Forest fire ignition models are effective ways to predict and classify drivers for ignition probability across broad areas. The aim was therefore to compare the predictive output and significance of predictable ignition and spatial patterns of three inflammation-distribution model types; one parametric\, a statistical model and two machine-learning algorithms: Maximum entropy (Maxent) and Random Forests (RF). We parameterized the models for Margalla Hills\, the National Park\, Islamabad\, Pakistan using 30 years of ignition\, socio-economic\, and environmental data. The best predictors of forest fire sites in all models were human population and development variables (although variable rankings were slightly differentiated)\, as well as elevation. However\, despite similar model performance and variables\, the map of ignition probabilities generated by Maxent was markedly different from those of the two other models.\nRelated Published papers: \n\nTariq\, A.; Shu\, H.; Siddiqui\, S.; Munir\, I.; Sharifi\, A.; Li\, Q.; Lu\, L. Spatio-temporal analysis of forest fire events in the Margalla Hills\, Islamabad\, Pakistan using socio-economic and environmental variable data with machine learning methods. For. Res. 2021\, 13\, 12\, doi: https://doi.org/10.1007/s11676-021-01354-4 (Journal of Forestry Research)\nTariq\, A*.; Shu\, H.; Saddiqui\, S.; Mousa\, B.G.; Munir\, I.; Nasri\, A.; Waqas\, H.; Baqa\, M.F.; Lu\, L. Forest fire Monitoring using spatial-statistical and Geo-spatial analysis of factors determining Forest fire in Margalla Hills\, Islamabad\, Pakistan. Geomatics\, Nat. Hazards Risk 2021\, 12\, 1212–1233\, doi: https://doi.org/10.1080/19475705.2021.1920477  (Geomatics\, Natural Hazards and Risks).\n\n\n\n\n    \n    \n    \n\n                \n        \n            \n\n                \n                                \n                    \n                        \n                            \n                                \n                                DR. AQIL TARIQKEY POSTDOCTORAL FELLOW STATE KEY LABORATORY OF INFORMATION ENGINEERING IN SURVEYING\, MAPPING AND REMOTE SENSING (LIESMARS)\, WUHAN UNIVERSITY\, WUHAN CHINA. (PHOTOGRAMMETRY\, REMOTE SENSING\, GIS\, GEOMATICS\, SPATIAL ANALYSIS AND GEOINFORMATION)Dr. Aqil Tariq was born in Rawalpindi\, Punjab\, Pakistan. Currently\, he is working as postdoctoral fellow in the State key Laboratory of Information Engineering in Surveying\, Mapping and Remote Sensing (LIESMARS)\, Wuhan University\, Wuhan China. He did one Master of Science in Geography and second Master of Science in Remote Sensing and GIS. Dr. Aqil Tariq has completed his Ph.D. (Photogrammetry and Remote sensing) within a span of three years i.e. from.2018-2021. He published 17 papers during Ph.D. tenure. He has very good scientific research writing abilities. Now\, he is author of more than twenty four (24) SCI/SSCI peer reviewed journal papers. He has abilities to conduct research individually. His research interest areas are 3D Geoinformation\, Urban analytics\, spatial analysis to examine land use/land cover\, Geospatial data science\, Agriculture monitoring\, Forest Fire\, Forest monitoring\, forest cover dynamics\, spatial statistics\, multi-criteria algorithms\, ecosystem sustainability\, hazards risk reduction\, statistical analysis and modelling using Python\, R and MATLAB. He is also working as reviewers in high SCI/SSCI impact factor Journals. He is also member of different international science communities’ i.e. ISPRS\, International Water Resources Association\, International Association of Geodesy\, Surveying & Spatial Sciences Institute (SSSI) and Emirati Society of GIS and Remote Sensing. \n\n                            \n                        \n                    \n\n                    \n                        \n            \n\n        \n                \n        \n            No Results Found
URL:https://www.esgrs.ae/event/spatio-temporal-forest-fire-monitoring-using-spatial-statistical-and-geo-spatial-analysis-of-factors-determining-forest-fire-in-margalla-hills-islamabad-pakistan/
CATEGORIES:2021,Webinars
ATTACH;FMTTYPE=image/png:https://www.esgrs.ae/wp-content/uploads/2023/07/islamabad-fire-1.png
END:VEVENT
END:VCALENDAR