scholarly journals INTERCEPTION AND INFILTRATION OF RAINWATER ON THE LAND OF EX FOREST FIRE ON TAHURA R. SOERJO LEDUG BLOCK

2019 ◽  
Vol 2 (1) ◽  
pp. 29
Author(s):  
Oktavian Dwi Suhermanto ◽  
Tatag Muttaqin ◽  
Nugroho Tri Waskitho
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Soil Infiltration ◽  
Infiltration Capacity ◽  
Hydrological System ◽  
Fire Area

Forest fires often occur in many islands of indonesia including in Kalimantan, Sumatra, Java, Sulawesi and other regions. These fires can lead to damage for ecosystems, flora and fauna, even ecosystem hydrology. One of the hydrological system that was disturbed is the interception and infiltration. Interception is the ability of trees to retain water rain then rereleased in steam. Infiltration is the process of water absorbing into the soil, infiltration capacity is the soil’s ability of absorbing water per unit of time. This research is to know the rest of the tree's ability to retain water, and knowing the infiltration of ex forest fire area on TAHURA R. Soerjo, Ledug blocks. This research was carried out on 17-23 January 2019 in ex forest fire area on TAHURA R. Soerjo, with an elevation of 1100-1200 masl. In the ex forest fire area there are 2 dominant trees species to do measurements of interception, there are Tutup (Mallotus paniculatus) and Klerek (Sapindus rarak DC). The results of the interception on Klerek tree is 10% and Tutup is 60%.  For the capacity of the infiltration is 27, 6 mm/hour. 

scholarly journals Forest Fire in East Nusa Tenggara during 2015-2019: Comparison to Forest Fire in Kalimantan and Sumatera

2021 ◽  
Vol 893 (1) ◽  
pp. 012010
Author(s):  
Sumaryati ◽  
D F Andarini ◽  
N Cholianawati ◽  
A Indrawati
Keyword(s):  
Carbon Monoxide ◽  
Forest Fire ◽  
Forest Fires ◽  
Forest Biomass ◽  
Comparison Method ◽  
Atmospheric Environment ◽  
Annual Average ◽  
Statistical Comparison ◽  
Fire Area ◽  
Total Column

Abstract East Nusa Tenggara is one of the provinces in Indonesia that has big forest fires following some provinces in Kalimantan and Sumatra. However, forest fires in East Nusa Tenggara have less attention in forest fires discussion in Indonesia. This study aims to analyze forest fires in East Nusa Tenggara and their impact on reducing visibility and increasing carbon monoxide (CO) from 2015 to 2019. In this study, hotspot, forest fire area, Oceanic Niño Index, visibility, and CO total column data were used to analyze the forest fires using a statistical comparison method in East Nusa Tenggara, Kalimantan, and Sumatra. The result shows that the number of hotspots in East Nusa Tenggara less than in Kalimantan and Sumatra for the same forest fire area. The forest fires in East Nusa Tenggara do not harm the atmospheric environment significantly. East Nusa Tenggara dominantly consists of savanna areas with no peatland, hence, the forest biomass burning produces less smoke and CO. Furthermore, the forest fire in East Nusa Tenggara has not an impact on decreasing visibility and increasing CO total column, in contrast, visibility in Sumatra and Kalimantan has fallen to 6 km from the annual average, and CO total column rise three times of normal condition during peak fire.

scholarly journals Forest Fires in the Ural Federal district and their impact on the environment

2020 ◽  
pp. 4-12
Author(s):  
В.К. Куплевацкий ◽  
Н.Ш. Шабалина
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Federal District ◽  
Economic Damage ◽  
Environmental Damage ◽  
Minimum Area ◽  
Forest Protection ◽  
Significant Damage ◽  
Fire Area ◽  
Chelyabinsk Region

На основе актов и книг учета лесных пожаров, а также статистической отчетности проанализированы показатели фактической горимости лесов за 2016–2020 гг. Установлено, что за 2020 г. на территории Уральского федерального округа зафиксировано 2182 лесных пожара. При этом пройденная огнем площадь составила 167,2 тыс. га. Указанные показатели несколько превышают значения количества и пройденной огнем площади по округу за последние 5 лет: 1961 случай и 124,6 тыс. га соответственно. Наибольшее количество лесных пожаров зафиксировано в 2020 г. в челябинской области – 587 случаев, а наименьшее – в Ямало-Ненецком автономном округе – 111 случаев. При этом максимальной пройден- ной огнем лесных пожаров площадью в 2020 г. характеризуется Ханты-Мансийский автономный округ – Югра – 144,7 тыс. га. Минимальная пройденная огнем площадь зафиксирована в Тюменской области – 1,6 тыс. га. Площадь среднего пожара за 2020 г. по округу составила 76,64 га, при этом в Ханты-Мансийском авто- номном округе – Югре она равнялась 308,0 га, а в Тюменской области – 6,98 га. Экономический ущерб от лесных пожаров составил по округу 4 109 793, 16 тыс. руб., при этом на тушение было затрачено 575 481,57 тыс. руб. Значительный размер ущерба от лесных пожаров, а также экологический ущерб вызывают необходи- мость дальнейшего совершенствования охраны лесов. On the bases and books of forest fire accounting, as well as statistical reporting the indicators of actual forest fire rates for 2016–2020 were and lyzed. It was established that in 2020 2182 forest fires were recorded in the Ural Federal Distict. While the area covered by fire was 167,2 th/ga. These indicators slightly exceed the value of the number and the area covered by fire over the past five years in the district. The latter account for 1961 cases and 124,6 thousands of ha respectively. The largest number of forest fires was recorded in 2020 in Chelyabinsk region – 587 cases, the least in the Yamalonenets autonomous okrug – 111 cases. At the same time the maximum area covered by forest fires in 2020 is charaiterized by the Khanty-Mansiysk autonomous okrug – Yugra – 144,7 thousands of has. The minimum area covered by the fire was recorded in the Tyumen region – 1,6 th. ha. The average fire area in 2020 around the Okrug was 76,64 ha, at the same time in the Khanty-Mansiysk autonomous okrug – Yugra, it is 308,0 ha, but in the Tyumen region – 6,98 ha. The economic damage from forest fires amounted to 4 109 793,16 th of roubes, at the same time 575 481,57 th of ronbes were spent fire suppressing significant damage from forest fires as well as environmental damage necessitates futher forest protection improvement.

scholarly journals Forest Fire Recognition Based on Feature Extraction from Multi-View Images

2021 ◽  
Vol 38 (3) ◽  
pp. 775-783
Author(s):  
Di Wu ◽  
Chunjiong Zhang ◽  
Li Ji ◽  
Rong Ran ◽  
Huaiyu Wu ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Forest Fire ◽  
Forest Fires ◽  
Recognition Rate ◽  
Color Space ◽  
Image Features ◽  
Dynamic Features ◽  
Feature Extraction Method ◽  
Fire Area ◽  
Fire Recognition

Forest fire recognition is important to the protection of forest resources. To effectively monitor forest fires, it is necessary to deploy multiple monitors from different angles. However, most of the traditional recognition models can only recognize single-source images. The neglection of multi-view images leads to a high false positive/negative rate. To improve the accuracy of forest fire recognition, this paper proposes a graph neural network (GNN) model based on the feature similarity of multi-view images. Specifically, the correlations (nodes) between multi-view images and library images were established to convert the input features of graph nodes into the correlation features between different images. Based on feature relationships, the image features in the library were updated to estimate the node similarity in the GNN model, improving the image recognition rate of our model. Furthermore, a fire area feature extraction method was designed based on image segmentation, aiming to simplify the complex preprocessing of images, and effectively extract the key features from images. By setting the threshold in the hue-saturation-value (HSV) color space, the fire area was extracted from the images, and the dynamic features were extracted from the continuous frames of the fire area. Experimental results show that our method recognized forest fires more effectively than the baselines, improving the recognition accuracy by 4%. In addition, the multi-source forest fire data experiment also confirms that our method could adapt to different forest fire scenes, and boast a strong generalization ability and anti-interference ability.

scholarly journals Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Hydrology ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 169
Author(s):  
Luca Folador ◽  
Alessio Cislaghi ◽  
Giorgio Vacchiano ◽  
Daniele Masseroni
Keyword(s):  
Forest Fires ◽  
Hydrological Response ◽  
Soil Infiltration ◽  
Infiltration Capacity ◽  
Flood Peak ◽  
Burned Areas ◽  
In Situ Data ◽  
The Impact ◽  
Fire Conditions

Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions.

scholarly journals A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 768
Author(s):  
Jin Pan ◽  
Xiaoming Ou ◽  
Liang Xu
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Learning Strategy ◽  
Early Stage ◽  
Fire Detection ◽  
Surveillance Systems ◽  
Region Detection ◽  
Decision Network ◽  
Fire Smoke ◽  
Weakly Supervised

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods.

scholarly journals Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data

2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Change ◽  
Fire Severity ◽  
Dynamic Change ◽  
Burned Area ◽  
Fire Event ◽  
Vegetation Dynamic ◽  
Area Index ◽  
Sentinel 2

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

scholarly journals Empirical Research on Climate Warming Risks for Forest Fires: A Case Study of Grade I Forest Fire Danger Zone, Sichuan Province, China

2021 ◽  
Vol 13 (14) ◽  
pp. 7773
Author(s):  
San Wang ◽  
Hongli Li ◽  
Shukui Niu
Keyword(s):  
Wind Speed ◽  
Forest Fire ◽  
Climate Warming ◽  
Forest Fires ◽  
Meteorological Factors ◽  
Sichuan Province ◽  
Danger Zone ◽  
Climatic Regions ◽  
Area Burned ◽  
Forest Fire Danger

The Sichuan province is a key area for forest and grassland fire prevention in China. Forest resources contribute significantly not only to the biological gene pool in the mid latitudes but also in reducing the concentration of greenhouse gases and slowing down global warming. To study and forecast forest fire change trends in a grade I forest fire danger zone in the Sichuan province under climate change, the dynamic impacts of meteorological factors on forest fires in different climatic regions were explored and a model between them was established by using an integral regression in this study. The results showed that the dominant factor behind the area burned was wind speed in three climatic regions, particularly in Ganzi and A’ba with plateau climates. In Ganzi and A’ba, precipitation was mainly responsible for controlling the number of forest fires while it was mainly affected by temperature in Panzhihua and Liangshan with semi-humid subtropical mountain climates. Moreover, the synergistic effect of temperature, precipitation and wind speed was responsible in basin mid-subtropical humid climates with Chengdu as the center and the influence of temperature was slightly higher. The differential forest fire response to meteorological factors was observed in different climatic regions but there was some regularity. The influence of monthly precipitation in the autumn on the area burned in each climatic region was more significant than in other seasons, which verified the hypothesis of a precipitation lag effect. Climate warming and the combined impact of warming effects may lead to more frequent and severe fires.

Associations Between Ambient Particulate Air Pollution and Cognitive Function in Indonesian Children Living in Forest Fire–Prone Provinces

2021 ◽  
pp. 101053952110317
Author(s):  
Bin Jalaludin ◽  
Frances L. Garden ◽  
Agata Chrzanowska ◽  
Budi Haryanto ◽  
Christine T. Cowie ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cognitive Function ◽  
Forest Fire ◽  
Forest Fires ◽  
Regression Models ◽  
Individual Factors ◽  
Aerodynamic Diameter ◽  
Particulate Air Pollution ◽  
Multivariable Models ◽  
Particulate Matter 2.5

Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval [CI] = 0.01% to 0.19%). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI = −2.53% to 0.21%). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI = −2.94% to −0.07%). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.

scholarly journals Characteristics of Korean Forest Fires and Forest Fire Policies in the Joseon Dynasty Period (1392–1910) Derived From Historical Records

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Donghyun Kim
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
East Coast ◽  
Historical Record ◽  
Capital City ◽  
Fire Damage ◽  
Historical Records ◽  
Royal Authority ◽  
Joseon Dynasty ◽  
Fire Stations

This study examined the records of forest fire outbreaks and characteristics over the 518 years of the Joseon Dynasty period (1392–1910) through the analysis of major historical records of Korea. The historical books used in this study were 14 major national historical books, and include the Annals of the Joseon Dynasty (朝鮮王朝實錄), the Diaries of the Royal Secretariat (承政院日記), and the literature was examined, centering on official records of the royal palace in the Joseon Dynasty period. The contents of forest fires recorded in the historical record literature include the overviews of outbreak, forest fire types, and forest fire damage. According to the results of analysis of historical records, the largest forest fire damage was in the forest fire that occurred on the east coast in 1672, in which 65 persons died and in the forest fire that occurred in the same area in 1804, in which 61 persons died and 2600 private houses were destroyed by fire. The causes of fire outbreak were shown to be unknown causes in 42 cases, accidental fires in 10 cases, arson in 3 cases, thunder strike in 3 cases, hunting activities in 2 cases, child playing with fire in 1 case, cultivating activities in 1 case, and house fire in 1 case. Forest fire outbreaks were analyzed by region and by season and according to the results, 56% (39 cases) of the forest fires broke out on the east coast and 73% (46 cases) broke out in the spring. Forest fire policies include those for general forests, those for reserved forests, those for prohibited forests, those for capital city forests, those for royal family’s graves, royal ancestral shrine, and placenta chamber, those for hunting grounds such as martial art teaching fields, and relief policies for people in areas damaged by forest fires, forest fire policies for national defense facilities such as beacon fire stations, and burning and burning control policies for pest control. In conclusion, due to the seriousness of forest fires in the Joseon Dynasty period, the royal authority and local administrative agencies made various forest fire prevention policies, policies for stabilization of the people’s livelihood damaged due to forest fires, and methods to manage major facilities in forests.

Sign in / Sign up

Export Citation Format

Share Document