Scholarlink

<p>This study identifies optimal locations for biochar production facilities in Irbid Governorate, Jordan, using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) to address sustainable waste management. Limited by data availability, it focuses on plant-based agricultural waste. A supervised classification of 2022 Landsat-8 imagery, using the Maximum Likelihood Algorithm, categorized land into five classes—built-up, rangeland, water, crops, and forests—with 91% accuracy (Kappa = 0.892). ArcGIS-based MCDA integrated key factors, including land use, proximity to biomass, transportation networks, slope, and hydrological features, to create a suitability map. The map highlights areas with gentle slopes, accessible biomass, and low environmental impact. Results show 38 potential sites, with biomass production concentrated in 8.2% of the governorate, mainly in central and southern regions due to good accessibility. Northern areas are less suitable due to topography, urban growth, and protected zones. Combining GIS and MCDA proves effective for planning sustainable biochar infrastructure, aiding climate-resilient waste management and circular economy goals in arid regions. These findings highlight spatial technologies’ potential to guide policy and expand eco-friendly solutions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Assessing site suitability for biochar facilities in Irbid Governorate, Jordan using GIS and multicriteria decision analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月27日

查看全文
  • Shereen A. Abusmier,
  • Mohammad M. Jaber,
  • Abdulrahman Maina Zubairu,
  • Mohammed Mustafa,
  • Emran Abu Murshid

摘要

This study identifies optimal locations for biochar production facilities in Irbid Governorate, Jordan, using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) to address sustainable waste management. Limited by data availability, it focuses on plant-based agricultural waste. A supervised classification of 2022 Landsat-8 imagery, using the Maximum Likelihood Algorithm, categorized land into five classes—built-up, rangeland, water, crops, and forests—with 91% accuracy (Kappa = 0.892). ArcGIS-based MCDA integrated key factors, including land use, proximity to biomass, transportation networks, slope, and hydrological features, to create a suitability map. The map highlights areas with gentle slopes, accessible biomass, and low environmental impact. Results show 38 potential sites, with biomass production concentrated in 8.2% of the governorate, mainly in central and southern regions due to good accessibility. Northern areas are less suitable due to topography, urban growth, and protected zones. Combining GIS and MCDA proves effective for planning sustainable biochar infrastructure, aiding climate-resilient waste management and circular economy goals in arid regions. These findings highlight spatial technologies’ potential to guide policy and expand eco-friendly solutions.