Land use and land cover change monitoring in Bandırma (Turkey) using remote sensing and geographic information systems

Kaya, İlgi Atay; Görgün, Esra Kut

doi:10.1007/s10661-020-08411-1

Cited by 33 publications

(8 citation statements)

References 45 publications

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“…The information analysis methodology used in this study to assess the spatiotemporal evolution of a landslide risk scenario within the framework of urban planning involved a multidisciplinary approach. Firstly, a comprehensive analysis of land use changes was conducted using remote sensing techniques and Geographic Information Systems [61] to evaluate alterations in land cover over the study period . Secondly, an exhaustive documentary review and historical analysis were carried out to contextualize observed land use changes and identify potential factors contributing to the evolution of the landslide risk scenario [62].…”

Section: Discussionmentioning

confidence: 99%

Challenges for Sustainable Urban Planning: A Spatiotemporal Analysis of Complex Landslide Risk in a Latin American Megacity

Vargas-Cuervo,

Hernández-Peña,

Zafra-Mejía

2024

Sustainability

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This paper analyzes the spatiotemporal evolution of a complex landslide risk scenario in a Latin American megacity, underscoring the key challenges it poses for sustainable urban planning in such cities. This research draws upon multiple studies commissioned by the mayor’s office of the megacity of Bogota, Colombia, and utilizes aerial photographs and satellite imagery from diverse sensor types. The methodology used considered six spatiotemporal analysis scenarios: rural/natural, mining, urban, landslide risk, stabilization and environmental park, and informal reoccupation. The findings reveal a complex interplay between the megacity’s peripheral areas, which face constraints for human settlement, and their potential for construction material exploitation. This complex relationship was further compounded by weaknesses in planning and controlling peripheral occupations, coupled with a burgeoning demand for developable land in a landslide risk context (landslide area: 73 ha). The analysis scenarios highlighted the predominant use of a reactive urban planning approach that addressed events, changes, or problems after they had occurred, rather than proactively anticipating and preventing potential risks at the study site. The detected land-use transformations unveiled different historical moments, culminating in a landslide disaster (804 houses destroyed, 3000 families at risk). This catastrophe necessitated a radical and significant intervention, incurring substantial costs for the megacity administration (USD 26.05 million). This landslide was the largest recorded in the megacity and one of the most extensive in urban areas across Latin America.

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Section: Discussionmentioning

confidence: 99%

Challenges for Sustainable Urban Planning: A Spatiotemporal Analysis of Complex Landslide Risk in a Latin American Megacity

Vargas-Cuervo,

Hernández-Peña,

Zafra-Mejía

2024

Sustainability

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“…A method for predicting a single output value using training data, for example, uses regression to predict a property's price based on training data. Other input variables include location, dwelling size, and other aspects [28].…”

Section: Regressionmentioning

confidence: 99%

Artificial Intelligence Techniques for Observation of Earth’s Changes

Alshari¹,

Gawali²

2023

Satellite Altimetry - Theory, Applications and Recent Advances

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This chapter discusses the primary components that contribute to the observation of Earth’s changes, including Land Observation Satellites, land classification techniques and their stages of development, and Machine Learning Techniques. It will give a comprehensive summary of the development stages of high-resolution satellites. It also details land classification with artificial intelligence algorithms. It will also give knowledge of classification methodologies from various Fundamentals of Machine Learning Classifiers: Pixel-based (PB), Sub-pixel-based (SPB), Object-based (OB), Knowledge-based (KB), Rule-based (RB), Distance-based (DB), Neural-based (NB), Parameter Based (PB), object-based image analysis (OBIA). It includes several different classifiers for LULC Classification. This chapter will include two applications for land observation satellites: The first is land use and land cover change observation with a practical example (study land use and land cover classification for Sana’a of Yemen as a case study from 1980 to 2020). The second application is satellite altimetry monitoring changes in mean sea level. The most significant contributions of it are the integration of these components. This chapter will be crucial in helping future researchers comprehend this topic. It will aid them in selecting the most appropriate and effective satellites for monitoring Earth’s changes and the most efficient classifier for their research.

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“…Therefore, high-resolution imagery on the study area (Li et al 2020) was collected, and combined with results from ground check, using a Garmin 78S GPS. The livelihood maximum classification approach was further adopted to classify and create land use and cover maps for the selected time period (Mekasha et al 2020;Kaya and Görgün 2020).…”

Section: Sampling Designmentioning

confidence: 99%

Characteristics of vegetation as determinant of Timor Friarbird (Philemon inornatus) distribution in Bipolo Lanscape of West Timor Island, Indonesia

et al. 2021

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Abstract. Paga B, Pudyatmoko S, Faida LRW, Yuda IP, Sulaksono N. 2021. Characteristics of vegetation as determinant of Timor Friarbird (Philemon inornatus) distribution in Bipolo Landscape of West Timor Island, Indonesia. Biodiversitas 22: 2617-2635. This study aims to identify vegetation factors as determinants of the distribution of Timor Friarbird (Philemon inornatus) in Timor Island. Timor Friarbird is one of the seven endemics bird species widely distributed in Timor Island, from the eastern region of Timor Leste to western region of Indonesia. This research was conducted at Bipolo Landscape, located in Timor Island, and has diversity of tropical flora diversity surrounding its Natural Tourism Park, which provides Timor Friarbird habitat. The characteristics of vegetation ecology were obtained by sampling design through Biogeography Branch's Sampling Design Tool for ArcGIS, while land use cover type was obtained by maximum likelihood method. The structure and composition of vegetation were observed through nested plot sampling, while Timor Friarbird species were assessed using the combination of point count and line transect method. The result obtained was formulated by discriminant linear regression. The vegetation parameters influencing the presence of Timor Friarbird were tree land use cover, number of trees and their species, pole land use cover, number of poles and their species, sapling land use cover, number of saplings and their species. Timor Friarbird is more likely to be present in the land cover area of poles with a minimum number of individual trees, poles, and saplings (press value Q = 6,63 ? 7). The results of discriminant analysis obtained a new group (nine variables), used collectively as a determinant factor for the presence of Timor Friarbird in their natural habitat on Timor Island

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Land use and land cover change monitoring in Bandırma (Turkey) using remote sensing and geographic information systems

Cited by 33 publications

References 45 publications

Challenges for Sustainable Urban Planning: A Spatiotemporal Analysis of Complex Landslide Risk in a Latin American Megacity

Challenges for Sustainable Urban Planning: A Spatiotemporal Analysis of Complex Landslide Risk in a Latin American Megacity

Artificial Intelligence Techniques for Observation of Earth’s Changes

Characteristics of vegetation as determinant of Timor Friarbird (Philemon inornatus) distribution in Bipolo Lanscape of West Timor Island, Indonesia

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