Remote sensing-based determination of understory grass greening stage over boreal forest

Hassan, Quazi K.; Rahman, K. Mahmud

doi:10.1117/1.jrs.7.073578

Cited by 8 publications

(4 citation statements)

References 23 publications

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“…At the end of the peak of the growing season, all six natural subregions experienced much less lightning-caused fires, which could be related to both the understory and overstory being fully developed by the peak of the growing season, thereby reducing fuel flammability [44]. In addition, the weather-in particular temperature regimes-plays an important role in influencing the vegetation phenology [22][23][24]. For example, we observed that temperatures start to increase in the spring, and this trend continues until it reaches a peak during the growing season (see Figure 6 as an example).…”

Section: Discussionmentioning

confidence: 99%

“…Between these two indices, the NDWI has been widely used in fire-related studies, such as forest fire vulnerability mapping [14], fire danger condition [10], fire risk prediction [15,16], fire behavior prediction [17], post-fire evaluation and vegetation response [18,19], and the beginning of the fire season [20,21]. In addition, it has been applied to the study of vegetation growth stages, such as coniferous needle flushing [22], understory grass green stage [23], and deciduous leaf out [24], which might be associated with fire occurrences. Other studies have employed NDVI to study/model fire occurrences [25,26].…”

Section: Introductionmentioning

confidence: 99%

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Applicability of Remote Sensing-Based Vegetation Water Content in Modeling Lightning-Caused Forest Fire Occurrences

Abdollahi

Dewan

Hassan

2019

IJGI

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In this study, our aim was to model forest fire occurrences caused by lightning using the variable of vegetation water content over six fire-dominant forested natural subregions in Northern Alberta, Canada. We used eight-day composites of surface reflectance data at 500-m spatial resolution, along with historical lightning-caused fire occurrences during the 2005–2016 period, derived from a Moderate Resolution Imaging Spectroradiometer. First, we calculated the normalized difference water index (NDWI) as an indicator of vegetation/fuel water content over the six natural subregions of interest. Then, we generated the subregion-specific annual dynamic median NDWI during the 2005–2012 period, which was assembled into a distinct pattern every year. We plotted the historical lightning-caused fires onto the generated patterns, and used the concept of cumulative frequency to model lightning-caused fire occurrences. Then, we applied this concept to model the cumulative frequencies of lightning-caused fires using the median NDWI values in each natural subregion. By finding the best subregion-specific function (i.e., R2 values over 0.98 for each subregion), we evaluated their performance using an independent subregion-specific lightning-caused fire dataset acquired during the 2013–2016 period. Our analyses revealed strong relationships (i.e., R2 values in the range of 0.92 to 0.98) between the observed and modeled cumulative frequencies of lightning-caused fires at the natural subregion level throughout the validation years. Finally, our results demonstrate the applicability of the proposed method in modeling lightning-caused fire occurrences over forested regions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applicability of Remote Sensing-Based Vegetation Water Content in Modeling Lightning-Caused Forest Fire Occurrences

Abdollahi

Dewan

Hassan

2019

IJGI

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“…To define cold days/spells, one of the simplified methods is to use a single threshold of a specific air temperature corresponding to the daily maximum (T max ), minimum (T min ), or average (T avg ) temperature [6,18,19]. Using such a single threshold of temperature for a country creates some issues, which are not appropriate for the following instances: (i) large waterbodies being present in some parts of a country [20], as areas adjacent to waterbodies usually have mild temperature; (ii) countries spanning over a larger range of latitudes [21,22], as higher latitudes predominate relatively cooler temperatures [23,24]; and (iii) diverse topography, which produces temperature variations, even in cases of narrow latitude [25]. In Bangladesh, a single T min threshold of ≤10 • C is used for the whole country to define a cold day, and a cold spell is declared when at least two nearby weather stations show three and more consecutive cold days [26,27].…”

Section: Introductionmentioning

confidence: 99%

A Percentile Method to Determine Cold Days and Spells in Bangladesh

et al. 2023

Self Cite

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The 10th percentiles (10P) of the daily minimum (Tmin) and maximum (Tmax) during 1971–2000 were determined to estimate a threshold for cold days. This 10P (a standard of extreme climatic condition suggested by the World Meteorological Organization) threshold was applied with the daily Tmin and Tmax in the winter months (December, January, and February) of 2000 to 2021 to calculate the number of cold days, and consecutively, cold spells, and their trends. A cold day was declared when the daily Tmax and/or Tmin was lower than that of the 10P threshold, and the average temperature was ≤17 °C in a weather station. In this research, the cold days and spells were categorized into five classes, namely extreme (≤13 °C), severe (>13–14 °C), very (>14–15 °C), moderate (>15–16 °C), and Mild (>16–17 °C). Moreover, a cold spell was considered when such cold days persisted for ≥2 consecutive days in at least two nearby stations. The results revealed a higher number of average cold days during winter in the western and northwestern districts of Bangladesh, and it reduced gradually in the south, southeast, and northeast. Dinajpur and Rajshahi districts showed the highest number of extreme and severe categories of cold days, i.e., 4.81 and 3.24 days/year, respectively. Rajshahi division had the highest number of cold spells on average (3.24/year), and Rangpur division had the highest number of extreme-category (the category that carries the lowest temperature range, ≤13 °C) cold spells (1.29/year). January was the coldest month, with the maximum number of cold days and spells. The highest average number of cold days (25.54%) was observed during the second ten days of January (i.e., 11–20 January). Significant increasing trends were found in the cold days of 11–20 December (5 stations), 21–31 December (3 stations), and the month of December (13 stations). In contrast, significant decreasing trends were noticed for the 1–10 January period in three weather stations. Our proposed 10P method could be used to determine the cold days and spells in Bangladesh that might be useful for the policy makers in formulating appropriate strategies in minimizing the impact of cold regimes during the winter season.

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“…In another study by Hu et al [9] used both 8-day and 16-day composites of MODIS-based Ts over the period of January 2011 to June 2018 for agricultural drought monitoring in the Hetao Plain in Inner Mongolia of Northwest China. Some other studies also used remote sensing based Ts in determining several biophysical parameters of vegetation, such as deciduous phenology [10], understory grass greening stage [11], and surface wetness conditions and growing degree days [12].…”

Section: Introductionmentioning

confidence: 99%

Processing of Near Real Time Land Surface Temperature and Its Application in Forecasting Forest Fire Danger Conditions

Ahmed

Hassan

Abdollahi

et al. 2020

Sensors

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Near real time (NRT) remote sensing derived land surface temperature (Ts) data has an utmost importance in various applications of natural hazards and disasters. Space-based instrument MODIS (moderate resolution imaging spectroradiometer) acquired NRT data products of Ts are made available for the users by LANCE (Land, Atmosphere Near real-time Capability) for Earth Observing System (EOS) of NASA (National Aeronautics and Space Administration) free of cost. Such Ts products are swath data with 5 min temporal increments of satellite acquisition, and the average latency is 60-125 min to be available in public domain. The swath data of Ts requires a specialized tool, i.e., HEG (HDF-EOS to GeoTIFF conversion tool) to process and make the data useful for further analysis. However, the file naming convention of the available swath data files in LANCE is not appropriate to download for an area of interest (AOI) to be processed by HEG. In this study, we developed a method/algorithm to overcome such issues in identifying the appropriate swath data files for an AOI that would be able to further processes supported by the HEG. In this case, we used Terra MODIS acquired NRT swath data of Ts, and further applied it to an existing framework of forecasting forest fires (as a case study) for the performance evaluation of our processed Ts. We were successful in selecting appropriate swath data files of Ts for our study area that was further processed by HEG, and finally were able to generate fire danger map in the existing forecasting model. Our proposed method/algorithm could be applied on any swath data product available in LANCE for any location in the world.

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Remote sensing-based determination of understory grass greening stage over boreal forest

Cited by 8 publications

References 23 publications

Applicability of Remote Sensing-Based Vegetation Water Content in Modeling Lightning-Caused Forest Fire Occurrences

Applicability of Remote Sensing-Based Vegetation Water Content in Modeling Lightning-Caused Forest Fire Occurrences

A Percentile Method to Determine Cold Days and Spells in Bangladesh

Processing of Near Real Time Land Surface Temperature and Its Application in Forecasting Forest Fire Danger Conditions

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