scholarly journals Methods to Detect Edge Effected Reductions in Fire Frequency in Simulated Forest Landscapes

2019 ◽  
Vol 8 (6) ◽  
pp. 277 ◽  
Author(s):  
Xinyuan Wei ◽  
Chris P. S. Larsen
Keyword(s):  
Edge Detection ◽  
Fire Frequency ◽  
Detection Methods ◽  
Simulation Studies ◽  
Rigid Boundary ◽  
Maximum Width ◽  
Mean Width ◽  
Buffer Width ◽  
In Fire ◽  
Future Landscape

Reductions in fire frequency (RFF) are known to occur in the area adjacent to the rigid-boundary of simulated forest landscapes. Few studies, however, have removed those edge effected regions (EERs), and many others may, thus, have misinterpreted their simulated forest conditions within those unidentified edges. We developed three methods to detect and remove EERs with RFF and applied them to fire frequency maps of 2900 × 2900 grids developed using between 1000 and 1200 fire-year maps. The three methods employed different approaches: scanning, agglomeration, and division, along with the consensus of two and three of those methods. The detected EERs with RFF ranged in mean width from 5.9 to 17.3 km, and occupied 4.9 to 21.3% of the simulated landscapes. Those values are lower than the 40 km buffer width, which occupied 47.5% of the simulated landscape, used in a previous study in this area that based buffer width on length of the largest fire. The maximum width of the EER covaried with wind predominance, indicating it is not possible to prescribe a standard buffer width for all simulation studies. The three edge detection methods differ in their optimality, with the best results provided by a consensus of the three methods. We suggest that future landscape forest simulation studies should, to ensure their results near the rigid boundary are not misrepresentative, simulate an appropriately enlarged study area and then employ edge detection methods to remove the EERs with RFF.

Comparative Analysis of Edge Detection Methods and its Implementation using UTLP Kit

2016 ◽  
Vol 3 (2) ◽  
pp. 26
Author(s):  
HEMALATHA R. ◽  
SANTHIYAKUMARI N. ◽  
MADHESWARAN M. ◽  
SURESH S. ◽  
◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Edge Detection ◽  
Detection Methods

scholarly journals Low Complexity Lane Detection Methods for Light Photometry System

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1665
Author(s):  
Jakub Suder ◽  
Kacper Podbucki ◽  
Tomasz Marciniak ◽  
Adam Dąbrowski
Keyword(s):  
Edge Detection ◽  
Optimal Path ◽  
Color Space ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Detection Methods ◽  
Raspberry Pi ◽  
Line Detection ◽  
Hsv Color Space

The aim of the paper was to analyze effective solutions for accurate lane detection on the roads. We focused on effective detection of airport runways and taxiways in order to drive a light-measurement trailer correctly. Three techniques for video-based line extracting were used for specific detection of environment conditions: (i) line detection using edge detection, Scharr mask and Hough transform, (ii) finding the optimal path using the hyperbola fitting line detection algorithm based on edge detection and (iii) detection of horizontal markings using image segmentation in the HSV color space. The developed solutions were tuned and tested with the use of embedded devices such as Raspberry Pi 4B or NVIDIA Jetson Nano.

Fire regime shift linked to increased forest density in a piñon–juniper savanna landscape

2014 ◽  
Vol 23 (2) ◽  
pp. 234 ◽  
Author(s):  
Ellis Q. Margolis
Keyword(s):  
Regime Shift ◽  
Fire History ◽  
Fire Regime ◽  
Fire Regimes ◽  
Fire Frequency ◽  
Climatic Conditions ◽  
Tree Density ◽  
High Severity ◽  
Wide Range ◽  
In Fire

Piñon–juniper (PJ) fire regimes are generally characterised as infrequent high-severity. However, PJ ecosystems vary across a large geographic and bio-climatic range and little is known about one of the principal PJ functional types, PJ savannas. It is logical that (1) grass in PJ savannas could support frequent, low-severity fire and (2) exclusion of frequent fire could explain increased tree density in PJ savannas. To assess these hypotheses I used dendroecological methods to reconstruct fire history and forest structure in a PJ-dominated savanna. Evidence of high-severity fire was not observed. From 112 fire-scarred trees I reconstructed 87 fire years (1547–1899). Mean fire interval was 7.8 years for fires recorded at ≥2 sites. Tree establishment was negatively correlated with fire frequency (r=–0.74) and peak PJ establishment was synchronous with dry (unfavourable) conditions and a regime shift (decline) in fire frequency in the late 1800s. The collapse of the grass-fuelled, frequent, surface fire regime in this PJ savanna was likely the primary driver of current high tree density (mean=881treesha–1) that is >600% of the historical estimate. Variability in bio-climatic conditions likely drive variability in fire regimes across the wide range of PJ ecosystems.

scholarly journals Effect of morphological algorithms on medical imaging

2021 ◽  
Vol 8 (3) ◽  
pp. 1-8
Author(s):  
Cuong Phan Viet ◽  
Thao Ho Thi ◽  
Anh Le Tuan ◽  
Ha Nguyen Hong ◽  
Thanh Ha Quang
Keyword(s):  
Medical Imaging ◽  
Edge Detection ◽  
Medical Images ◽  
Computer Software ◽  
Diagnosis And Treatment ◽  
Detection Methods ◽  
Morphological Operators

Handling and improving the quality of medical images with the help of computer software is one of the important stages in the diagnosis and treatment. In this article, we focus on describing the new morphological algorithms by ITK (Insight Segmentation and Registration Toolkit). These morphological operators eliminate noise, detect good edges, and overcome the drawback of traditional edge detection methods.

scholarly journals Tropical Dry Forest Resilience to Fire Depends on Fire Frequency and Climate

2021 ◽  
Vol 4 ◽  
Author(s):  
Maximilian Hartung ◽  
Geovana Carreño-Rocabado ◽  
Marielos Peña-Claros ◽  
Masha T. van der Sande
Keyword(s):  
Tropical Forests ◽  
Tropical Dry Forest ◽  
Remote Sensing Data ◽  
Fire Frequency ◽  
Dry Forest ◽  
Fire Disturbance ◽  
Fire Intensity ◽  
Forest Resilience ◽  
Landsat Satellite ◽  
In Fire

Wildfires are becoming increasingly frequent and devastating in many tropical forests. Although seasonally dry tropical forests (SDTF) are among the most fire-threatened ecosystems, their long-term response to frequent wildfires remains largely unknown. This study is among the first to investigate the resilience in response to fire of the Chiquitano SDTF in Bolivia, a large ecoregion that has seen an unprecedented increase in fire intensity and frequency in recent years. We used remote sensing data to assess at a large regional and temporal scale (two decades) how fire frequency and environmental factors determine the resilience of the vegetation to fire disturbance. Resilience was measured as the resistance to fire damage and post-fire recovery. Both parameters were monitored for forested areas that burned once (F1), twice (F2), and three times (F3) between 2000 and 2010 and compared to unburned forests. Resistance and recovery were analyzed using time series of the Normalized Burn Ratio (NBR) index derived from Landsat satellite imagery, and climatic, topographic, and a human development-related variable used to evaluate their influence on resilience. The overall resilience was lowest in forests that burned twice and was higher in forests that burned three times, indicating a possible transition state in fire resilience, probably because forests become increasingly adapted during recurrent fires. Climatic variables, particularly rainfall, were most influential in determining resilience. Our results indicate that the Chiquitano dry forest is relatively resilient to recurring fires, has the capacity to recover and adapt, and that climatic differences are the main determinants of the spatial variation observed in resilience. Nevertheless, further research is needed to understand the effect of the higher frequency and intensity of fires expected in the future due to climate change and land use change, which may pose a greater threat to forest resilience.

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