Impact of Land use Changes on Landslides Occurrence in Urban Area: The Case of the Constantine City (NE Algeria)

Bourenane, Hamid; Bouhadad, Youcef

doi:10.1007/s10706-021-01768-1

Cited by 11 publications

(5 citation statements)

References 49 publications

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“…3). This observed warming trend is likely linked to a notable decrease in built-up areas from 1981 to 2014, indicating potential urban development or changes in land use practices (Bourenane & Bouhadad, 2021).…”

Section: Results Anddiscussion Temporal Variation Of Climatic Parametersmentioning

confidence: 99%

Analysis of Climate Change Effect on Extreme Precipitation Event in Constantine Algeria

Sara Sahnoune,

Khellaf Imane,

Meghzili Marwa

2024

RS Global - IJITSS

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Extreme precipitation events are critical climatic indicators that offer substantial insights into climate change and its variability. This study aims to investigate whether climate change has impacted precipitation frequencies in the Constantine region of Algeria, known for its semi-arid climate with hot-dry summers and cold-wet winters. Temporal variations of monthly air temperature and precipitation were analyzed from 1981 to 2014. Statistical analysis identified a threshold for estimating monthly extreme precipitation during the period from 1981 to 2005 using the Gumbel distribution method. Additionally, a climatic projection of precipitation for return periods of 50 (t = 50) and 100 (t = 100) years was conducted to forecast extreme precipitation values in the future. The results indicate a gradual increase in precipitation levels during the study period, with values generally remaining below extreme thresholds. This suggests no significant escalation in the occurrence of extreme precipitation events. Furthermore, the findings highlight that climate change has had a more pronounced impact on altering air temperature than on influencing extreme precipitation trends.

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Section: Results Anddiscussion Temporal Variation Of Climatic Parametersmentioning

confidence: 99%

Analysis of Climate Change Effect on Extreme Precipitation Event in Constantine Algeria

Sara Sahnoune,

Khellaf Imane,

Meghzili Marwa

2024

RS Global - IJITSS

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“…In 2011, the population density was 614 people/km2, but in 2020, it increased to 671 people/km2, which impacts the growing population pressure on land. Paying attention to the physical condition of the area, the increase in pressure will result in a higher risk of landslides [16,17].…”

Section: Figure 1 Landslide Incident In Karanganyarmentioning

confidence: 99%

Community adaptive capacity in facing landslide disaster

Wijayanti,

Zamani,

Osza

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Tawangmangu District is located on the slopes of Mount Lawu, with most of its area being at an altitude of +- 1200m above sea level. Tawangmangu District has an uneven slope, and the eastern region has a +- 40% slope. This resulted in the area in Tawangmangu District frequently experiencing landslides. Data from the Karanganyar Regional Disaster Management Agency (BPBD) for 2022 shows more than 11 landslides. The resulting impacts are different but certainly result in morphological changes in the Tawangmangu District according to the type of landslide that occurred. Living in areas with a high risk of landslides is challenging for the community, so people must adapt to a vulnerable environment. This study aims to analyze the adaptive capacity of the community against landslides. The study area covers ten villages in the Tawangmangu District. The study area covers seven villages. The evaluation uses a quantitative descriptive method based on human, social, natural, physical, and financial factors. The results obtained show that there are variations in the adaptive capacity of the community, which depend on the intensity of exposure.

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“…L ANDSLIDES, typically a consequence of climate change [1] and urban expansion [2], are one of the most common natural disasters today and cause severe troubles to human life and infrastructures all over the world. For example, a severe landslide occurred in mid-2020 in Vietnam, causing dozens of deaths.…”

Section: Introductionmentioning

confidence: 99%

“…For example, a severe landslide occurred in mid-2020 in Vietnam, causing dozens of deaths. 1 Landslides cause roads to be blocked, which causes hurdles not only in the traffic flow but also generate various traffic problems in the form of congestion [3]. Therefore, there is a need to detect and warn of landslides as quickly as possible to identify proper counter-measures so that possible unfortunate consequences can be avoided.…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies deal with two related problems of landslides, termed landslide detection and landslide prediction, in which the methods built upon machine learning and deep learning are quite common [4], [5]. However, practical applications of such methods are often limited due to the fact that deep learning models often require enormous labeled data to § Equal contribution 1 Source: https://blogtuan.info/2022/05/20/serious-landslide-on-the-routeda-lat-mui-ne/ work well while landslides may only occur several times a year, thus it may take years to collect a sufficient amount of data. Besides, as landslides tend to occur in mountainous areas, collecting landslide images are difficult due to the danger as well as the lack of equipment in such underdeveloped areas.…”

Section: Introductionmentioning

confidence: 99%

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Integrative Few-Shot Classification and Segmentation for Landslide Detection

Tran-Anh

Bui-Quoc

et al. 2022

IEEE Access

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There has been an ongoing demand for monitoring landslides due to the heavy economic losses and casualties caused by such natural disasters. In this paper, we introduce a swift landslide detection system that can detect and segment landslides occurring on roads. To tackle the challenges of data collection, we propose an automatic annotation procedure to create a new landslide dataset consisting of 2963 images, termed the LandslidePTIT dataset. Additionally, we construct a novel deep learning architecture that can perform both classification and segmentation tasks well from a few annotated images of landslides. Specifically, the model consists of four main modules that are delicately designed to solve the few-shot segmentation problem using landslide images, namely hypercorrelation construction, attentive squeeze block, a cross-feature layer, and broadcast and squeeze layer. Experimental results exhibit the superiority of the proposed methods in comparison with competitive baselines, in terms of both quantitative and qualitative manners.

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Impact of Land use Changes on Landslides Occurrence in Urban Area: The Case of the Constantine City (NE Algeria)

Cited by 11 publications

References 49 publications

Analysis of Climate Change Effect on Extreme Precipitation Event in Constantine Algeria

Analysis of Climate Change Effect on Extreme Precipitation Event in Constantine Algeria

Community adaptive capacity in facing landslide disaster

Integrative Few-Shot Classification and Segmentation for Landslide Detection

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