Climate and Land Use Change Effects on Sediment Production in a Dry Tropical Forest Catchment

Montoya, Juan Pablo García; Giráldez, Juan Vicente; Vanwalleghem, Tom

doi:10.3390/w13162233

Cited by 6 publications

(3 citation statements)

References 52 publications

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“…The water area is 1.7-3 km 2 , except in 2019, which was decreased to 0.00 km 2 . This change in land cover is due to climate change phenomena such as La Niña and El Niño [30]. El Niño is a phenomenon of warming sea surface temperatures above average conditions in the central Pacific Ocean.…”

Section: Spatial Distribution Of Lulc During 2013-2021mentioning

confidence: 99%

Urban tourism expansion monitoring by remote sensing and random forest

Andyana,

As-syakur,

Sunarta

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Tourism and urban areas experienced rapid development at the beginning of the 21st century. This condition is caused by natural, cultural, and artificial tourist destinations and adequate infrastructure support. Tourist destinations in urban areas add to urbanization because apart from being the center of government, trade, and industry, it is also a tourist destination that can attract tourists. Monitoring the development of urban tourism is carried out in the cities of Denpasar and Bali, as well-known destinations at the world level. The development of the urban area can be detected through multi-temporal and multispectral remote sensing imagery in combination with machine learning technology. This study aims to determine the spatial distribution of urban tourism development from 2013 to 2021. This study uses remote sensing and machine learning methods with the Random Forest (RF) algorithm on Google Earth Engine (GEE) cloud computing. The RF algorithm is one of the non-parametric classification algorithms which is widely applied in remote sensing data classification because of its insensitivity to excessive noise and training data and its good performance. The material used is Landsat 8, especially on the Operational Land Imager (OLI) sensor. The result showed that integrating remote sensing, GEE cloud computing, and machine learning, especially the RF algorithm, effectively monitors urban tourism expansion. The overall accuracy of the RF model with simple training data is above 90%. We found that within nine years, vegetated land was changed into an urban area of 20.23 km2. For this reason, special attention is needed from the government to make regulations on spatial planning and control over land conversion so that there will still be green open spaces in the future.

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Section: Spatial Distribution Of Lulc During 2013-2021mentioning

confidence: 99%

Urban tourism expansion monitoring by remote sensing and random forest

Andyana,

As-syakur,

Sunarta

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…Localized variations in topography and land use patterns contribute to diverse impacts, necessitating region-specific assessments and adaptive measures. Addressing the consequences of El Niño on vegetation and soil conditions is crucial for sustainable land management and agricultural resilience in Malaysia [28]. Reduced vegetation cover can make soils more susceptible to erosion.…”

Section: 2challengementioning

confidence: 99%

“…The rates of natural erosion are typically the lowest in hyper-arid and arid regions, but they can still fluctuate significantly due to extreme events, particularly warm El Niño-Southern Oscillation (ENSO) conditions or earthquakes [27]. Besides, based on Juan et al, reduced vegetation coverage and vegetation stress was seen during El Nino events due to the absence of rain [28]. There is a notable absence of comprehensive reports that have quantified the effects of converting natural forests to economic forests on soil erosion, soil organic carbon (SOC), and total nitrogen (TN) [4].…”

Section: 2challengementioning

confidence: 99%

Navigating Soil Erosion Challenges in Malaysia: Insights, Prospects, and Solutions

Chin,

Maharjan,

Emalya

2023

Civil Sustain. Urban Eng.

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The escalating global demand for forest products, driven by economic growth and a growing population, has led to increased forest conversion activities. Forest conversion involves transforming forested areas to meet industrial demands, resulting in severe ecological consequences. This review focuses on the state of soil erosion practices in Malaysia, which is a pressing issue with wide-ranging impacts on soil health, agricultural sustainability, and the environment. Malaysia's geographical location exposes it to the El Nino phenomenon, characterized by disrupted climate patterns and altered rainfall intensities, indirectly contributing to soil erosion. During El Nino events, diminished vegetation cover, primarily due to rainfall deficits, increases soil susceptibility to erosion, emphasizing the need for adaptive erosion control measures. Soil erosion poses a significant challenge to the sustainability of agriculture and terrestrial ecosystems. Malaysia has made efforts to address this issue by implementing soil and water conservation practices like terraces, grassed waterways, strip cropping, and conservation tillage, which effectively reduce erosion rates. However, these methods face challenges due to the variations in natural erosion rates driven by extreme events. Additionally, the conversion of natural forests to economic forests remains an underexplored concern in Malaysia, hindering the development of tailored soil erosion control strategies. Addressing soil erosion demands a comprehensive approach that includes research, policy support, and empowering farmers to adopt soil conservation practices. Soil erosion affects ecosystems, water resources, and urban development, necessitating multifaceted solutions to preserve both environmental sustainability and agricultural productivity in the face of evolving environmental challenges.

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