Monitoring Urban Growth and Land Use Change Detection with Gis Techniques In Irbid City, Jordan

Self Cite

The location of a restaurant contributes greatly to its success or failure. Therefore, the factors affecting such location-related decisions must be carefully studied and prioritized systematically. This study aims to adapt the analytical hierarchy process (AHP) for selecting the optimal location for a casual-dining restaurant and determine the critical factors affecting the selection. After a comprehensive review of the literature, this study first determines the factors affecting casual-dining restaurant location selection and then applies AHP steps by soliciting experts' opinions under several criteria and sub-criteria. The AHP model used in the study consisted of seven criteria, twenty-five sub-criteria, and three locations alternatives. The three most important criteria that affect the location selection of the casual-dining restaurant are Costs, Location, and Traffic patterns and accessibility, respectively. To illustrate the framework of using AHP as a tool to select the right location for a casual-dining restaurant, three locations were nominated and ranked according to the calculated weight scores of the criteria. Moreover, the results of the sensitivity analysis show that the location alternatives are not sensitive to the physical characteristics, location, area's future, costs, or, competition criteria, while they were slightly sensitive to the visibility, and traffic patterns criteria. The results of the study provide a range of managerial implications that may guide casual-dining restaurant investors in choosing the optimal location.

Section: Priorities For Alternativesmentioning

confidence: 99%

Optimal location selection of a casual-dining restaurant using a multi-criteria decision-making (MCDM) approach

Alwedyan

2024

Self Cite

“…However, potential limitations between the presented climate data and remote sensingderived LST could include differences in temporal and spatial resolutions, sensor characteristics, data processing techniques, and the need for validation and calibration to ensure accurate correlation. The literature review indicates the strengths of studies employing GIS and Remote Sensing technologies, particularly in the context of coastal resource management, encompassing spatial planning (Alwedyan, 2023), and climate change adaptation (Islam, Yeasmin et al, 2023). Utilizing Land Surface Temperature (LST) information enhances spatial planning, contributing to more effective coastal resource management.…”

Section: 6mentioning

confidence: 99%

The Impact of Land Use Change on Land Surface Temperature 1990-2020 for Environmental Monitoring in Kapota Island, Wakatobi Regency, Indonesia

Surni,

Hanani,

Riniwati

et al. 2024

Small islands have unique ecosystems and are vulnerable to land degradation and ecological threats. Integrating spatial and landscape ecology approaches greatly influences the effectiveness and efficiency of environmental monitoring and future environmental management planning. Uncontrolled land conversion, extreme climate conditions, high biophysical land constraints, and anthropogenic and political factors contribute to biodiversity pressures. This study aimed to measure the impact of land use and land cover changes on the LST, NDVI, and NDWI as well as changes in landscape patterns and structures for environmental monitoring and ecological sustainability on Kapota Island. The LST values in 1990 ranged from 21.50°C to 25.40°C, and from 22.63°C to 32.56°C in 2020. In contrast, the NDVI values in 1990 ranged from -0.765 to 0.754 and from -0.241 to 0.514 in 2020. The surface temperature increased in vegetated areas with low density, as well as in non-vegetated areas and settlements. Habitat fragmentation was relatively high, as indicated by the SHDI value closer to 1. Moving forward, future research should delve deeper into the specific drivers of biodiversity pressures, including uncontrolled land conversion, extreme climate conditions, biophysical constraints, and anthropogenic and political factors. Moreover, efforts should be directed toward maintaining a green cover exceeding 30%, enhancing vegetation density, minimizing land-clearing activities, and encouraging the cultivation of crops with good water storage capabilities. This research lays the foundation for a more nuanced understanding of the intricate dynamics at play on small islands and sets the stage for informed conservation and management strategies.

“…This data may be used to develop strategies to ensure the longterm protection of urban ecosystems. Alwedyan (2023) showed the efficacy of GIS technology in obtaining accurate land use maps and comprehensive change statistics for the city of Irbid. The findings provide important data for formulating policies related to land use and urban expansion in the city, as well as making judgments and developing plans for the supply of adequate infrastructure.…”

Section: Literature Reviewmentioning

confidence: 99%

Vegetation Cover Change Analysis during 1989-2020 of Coastal Barguna District, Bangladesh Using Remote Sensing and GIS Technology

Islam

Yeasmin

Karmaker

et al. 2023

This paper represents an advanced assessment of a satellite imagery-based vegetation transition detection method for Bangladesh's southern district of Barguna. Bangladesh has been identified as the most vulnerable country to the effects of climate change due to deteriorating vegetative cover and urbanization pushing forces. This paper aims to use GIS and remote sensing techniques to estimate vegetation change and determine the conversion pattern in the coastal district of Barguna, Bangladesh, from 1989 to 2020. The major methodology used in this research is NDVI differencing and supervised image classification to validate the conversion over time. With a combination of satellite imagery bands, NDVI uses multi-spectral remote sensing techniques to discover vegetation index, water, empty spaces, and forests. To categorize the canopy into distinct kinds, we use NDVI threshold values of 0, 0.1, 0.15, and 0.2. Our findings reveal significant geographical variations in bare regions, sparse, moderate, and thick vegetation types. We discovered that over the last 31 years, a total of 412.90 km 2 (49.25 percent) of land has been deforested, with the transition rate being particularly high in dense vegetation. This research of vegetation cover change can help predict the recurrence of natural disasters, give humanitarian assistance, and enable innovative protection tactics.