scholarly journals An Approach For Identifying The Forest Fire Using Land Surface Imagery By Locating The Abnormal Temperature Distribution

2013 ◽  
Vol 14 (3) ◽  
pp. 06-12 ◽  
Author(s):  
S Anitha ◽  
Keyword(s):  
Temperature Distribution ◽  
Forest Fire ◽  
Land Surface ◽  
Abnormal Temperature

scholarly journals Introducing a New Remote Sensing-Based Model for Forecasting Forest Fire Danger Conditions at a Four-Day Scale

2019 ◽  
Vol 11 (18) ◽  
pp. 2101 ◽  
Author(s):  
M. Ahmed ◽  
Quazi Hassan ◽  
Masoud Abdollahi ◽  
Anil Gupta
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Land Surface ◽  
Vegetation Index ◽  
Significant Risk ◽  
Fire Danger ◽  
Area Of Interest ◽  
Forest Fire Danger ◽  
Very High

Forest fires are natural disasters that create a significant risk to the communities living in the vicinity of forested landscape. To minimize the risk of forest fires for the resilience of such urban communities and forested ecosystems, we proposed a new remote sensing-based medium-term (i.e., four-day) forest fire danger forecasting system (FFDFS) based on an existing framework, and applied the system over the forested regions in the northern Alberta, Canada. Hence, we first employed moderate resolution imaging spectroradiometer (MODIS)-derived daily land surface temperature (Ts) and surface reflectance products along with the annual land cover to generate three four-day composite for Ts, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) at 500 m spatial resolution for the next four days over the forest-dominant regions. Upon generating these four-day composites, we calculated the variable-specific mean values to determine variable-specific fire danger maps with two danger classes (i.e., high and low). Then, by assuming the cloud-contaminated pixels as the low fire danger areas, we combined these three danger maps to generate a four-day fire danger map with four danger classes (i.e., low, moderate, high, and very high) over our study area of interest, which was further enhanced by incorporation of a human-caused static fire danger map. Finally, the four-day scale fire danger maps were evaluated using observed/ground-based forest fire occurrences during the 2015–2017 fire seasons. The results revealed that our proposed system was able to detect about 75% of the fire events in the top two danger classes (i.e., high and very high). The system was also able to predict the 2016 Horse River wildfire, the worst fire event in Albertian and Canadian history, with about 67% agreement. The higher accuracy outputs from our proposed model indicated that it could be implemented in the operational management, which would be very useful for lessening the adverse impact of such fire events.

Observations of the ABL Structures over a Heterogeneous Land Surface during IHOP_2002

2007 ◽  
Vol 8 (2) ◽  
pp. 221-244 ◽  
Author(s):  
Song-Lak Kang ◽  
Kenneth J. Davis ◽  
Margaret LeMone
Keyword(s):  
Temperature Distribution ◽  
Surface Temperature ◽  
Land Surface ◽  
Joint Probability ◽  
Surface Flux ◽  
Weather Conditions ◽  
Surface Heterogeneity ◽  
Small Scale ◽  
Mesoscale Circulations ◽  
Obukhov Length

Abstract This study analyzes data collected by aircraft and surface flux sites over a 60-km north–south-oriented aircraft track for five fair-weather days during the International H2O Project (IHOP_2002) to investigate the atmospheric boundary layer (ABL) structures over a heterogeneous land surface under different background weather conditions. The surface skin temperature distribution over the aircraft track in this case is mostly explained by the soil thermal properties and soil moisture, and corresponds to the observed ABL depths except one day having a weak surface temperature gradient and a weak capping inversion. For the other four days, the blending height of the surface heterogeneity likely exceeds the ABL depth and thus the ABL establishes equilibrium with local surface conditions. Among the four days, two days having relatively small Obukhov lengths are evaluated to show the background weather conditions under which small-scale surface heterogeneity can influence the entire ABL. In fact, on one of these two days, relatively small-scale features of the surface temperature distribution can be seen in the ABL depth distribution. On the two small Obukhov length days multiresolution spectra and joint probability distributions, which are applied to the data collected from repeated low-level aircraft passes, both imply the existence of surface-heterogeneity-generated mesoscale circulations on scales of 10 km or more. Also on these two small Obukhov length days, the vertical profiles of dimensionless variances of velocity, temperature, and moisture show large deviations from the similarity curves, which also imply the existence of mesoscale circulations.

scholarly journals Deteksi Perubahan Suhu Permukaan Menggunakan Data Satelit Landsat Multi-Waktu Studi Kasus Cekungan Bandung

2018 ◽  
Vol 19 (2) ◽  
pp. 145 ◽  
Author(s):  
Widya Ningrum ◽  
Ida Narulita
Keyword(s):  
Land Use ◽  
Temperature Distribution ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Surface Temperature Distribution

ABSTRACTThe rapid population growth and development of infrastructure in the Bandung basin has triggered an uncontrolled land use changes. The changes of land use will impact on land surface temperature distribution. Finally, these changes will give influence on climate. Land surface temperature is one of the important climatic elements in the energy balance. Changes in land surface temperature variations will potentially change other elements of the climate. The purpose of this paper is to obtain and to analyze the changes of surface temperature distribution in Bandung basin using multi temporal satellite data processing that is Landsat 5 and Landsat 8 in 2004, 2009 and 2014. Near Infrared Channel (Near Infrared/NIR) and visible wave channels (Visible band) have used to obtain the value Normalized Difference Vegetation Index/NDVI index and Albedo. Land and vegetation emissivity value and thermal band have used to determine land surface temperature. The results showed that the surface temperature distribution of Bandung basin has been changes characterized by the presence of two hotspot characters i.e. hot areas in urban and hot areas in non-urban area. The area is characterized by decreasing vegetation index values, increasing albedo values and increasing on surface temperature.  Land Surface Temperatures average value increased by 1.3°C. Land surface temperature tends to rise supposed as a result of changes in vegetated area into open area and the build area  Keywords: land surface temperature, normalized difference vegetation index, albedoABSTRAKPesatnya pertumbuhan penduduk dan perkembangan infrastruktur di cekungan Bandung telah memicu perubahan tutupan lahan yang tidak terkendali. Perubahan tutupan lahan akan mempengaruhi distribusi suhu permukaan. Hal tersebut pada akhirnya nanti akan mempengaruhi iklim. Suhu permukaan merupakan salah satu unsur iklim yang penting dalam neraca energi. Perubahan variasi suhu permukaan berpotensi mengubah unsur unsur iklim yang lainnya. Tujuan makalah ini adalah untuk mengetahui dan menganalisis perubahan distribusi suhu permukaan di cekungan Bandung melalui pengolahan data satelit multi waktu yaitu Landsat 5 dan Landsat 8 tahun 2004, 2009, 2014 dan 2016. Kanal Inframerah Dekat (Near Infrared/NIR) dan kanal gelombang tampak (Visible band) digunakan untuk memperoleh nilai Indeks Kehijauan Vegetasi (Normalized Difference Vegetation Index/NDVI) dan Albedo. Nilai emisivitas dari tanah dan vegetasi serta Band termal digunakan untuk menentukan nilai Suhu Permukaan Tanah.Hasil penelitian menunjukkan bahwa di cekungan Bandung telah terjadi perubahan distribusi suhu permukaan yang dicirikan oleh adanya dua karakter hotspot yaitu daerah panas di daerah urban dan daerah panas di daerah non-urban. Daerah tersebut dicirikan menurunnya nilai indeks vegetasi, menurunnya nilai albedo dan meningkatnya nilai suhu permukaan tanah. Nilai rataan Suhu Permukaan Tanah tahun 2005 - 2014 meningkat sebesar 1.3°C. Kecenderungan naik ini diduga sebagai akibat adanya perubahan tutupan lahan bervegetasi menjadi daerah yang lebih terbuka dan daerah terbangun.Kata kunci: suhu permukaan, indeks kehijauan vegetasi, albedo 

Application of artificial neural networks and logistic regression to the prediction of forest fire danger in Galicia using MODIS data

2012 ◽  
Vol 21 (8) ◽  
pp. 1025 ◽  
Author(s):  
Mar Bisquert ◽  
Eduardo Caselles ◽  
Juan Manuel Sánchez ◽  
Vicente Caselles
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Logistic Regression ◽  
Artificial Neural Networks ◽  
Surface Temperature ◽  
Forest Fire ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Fire Danger ◽  
Forest Fire Danger

Fire danger models are a very useful tool for the prevention and extinction of forest fires. Some inputs of these models, such as vegetation status and temperature, can be obtained from remote sensing images, which offer higher spatial and temporal resolution than direct ground measures. In this paper, we focus on the Galicia region (north-west of Spain), and MODIS (Moderate Resolution Imaging Spectroradiometer) images are used to monitor vegetation status and to obtain land surface temperature as essential inputs in forest fire danger models. In this work, we tested the potential of artificial neural networks and logistic regression to estimate forest fire danger from remote sensing and fire history data. Remote sensing inputs used were the land surface temperature and the Enhanced Vegetation Index. A classification into three levels of fire danger was established. Fire danger maps based on this classification will facilitate fire prevention and extinction tasks.

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