Advancing sustainable urban development in Amman through Earth observation Technology

Situation

Amman, Jordan is proactively pursuing environmental sustainability to build a future-proof urban ecosystem

The Greater Amman Municipality (GAM) has established robust strategic foundations, including the Amman Green City Action Plan (2021), Amman Climate Plan (2019), Resilience Strategy (2017), and a Smart City Roadmap.

Despite these efforts, Amman faces significant urban development challenges, such as spatial inefficiencies, fragmented growth patterns, and complex urban planning constraints. These issues exacerbate the city's vulnerability to climate change impacts, affecting urban liveability and service provision for its growing population. The project specifically addresses these challenges by modeling urban development scenarios to assess climate risks to populations and services, and by enhancing understanding of Amman's potential for urban greening and Nature-Based Solutions (NBS) to combat inefficient land use and green space scarcity.

The World Bank's support aims to leverage spatial analytics to align Amman's dynamic urbanization with GAM's transformative agenda and strategic objectives. A critical aspect is to enhance the role of geospatial data, digital tools, and institutional expertise in urban and transport planning, and resource management, to facilitate evidence-based policymaking. Jon Kher Kaw, Senior Urban Development Specialist at the World Bank, highlights that "Earth observation is a game-changer, providing policymakers with new ways to analyse and access critical spatial data and information that may not be available for many developing economies".

Solution

A portfolio of EO-based solutions to promote sustainable urban growth was prepared by our team of partners

Operating under the ESA GDA AID Urban Sustainability program, our team of geospatial experts including Gisat, the Austrian Institute of Technology, and the German Aerospace Center (DLR) have provided comprehensive Earth Observation (EO)-based datasets, spatial analytics, and modeling technologies to assist the Greater Amman Municipality (GAM). 

The solution integrates EO data for urban analytics and predictive modeling, focusing on assessing Nature-Based Solutions (NBS) potential through a city-wide green areas inventory and developing urban development scenarios. Core information products involve:

Land Use Land Cover (LULC)

Prepared for 2010 and 2020 providing an overview of Amman's land use with 19 distinct classes. This product is crucial for understanding historical urban development trends and serves as input for agent-based modeling.

Urban Green Areas

Detects urban greenery at 0.5m resolution using a deep learning model (GreenDetector). Data for 2019 and 2022 provides foundational insights for urban green analytics.

Settlement Extent and Change, Percent Impervious Surface (PIS) and Settlement Change Tracker

Based on open products developed by DLR colleagues, these datasets, covering 1985-2021, track Amman's expansion and densification. They reveal growth towards the North-East and South, with noticeable densification in North-Eastern and Southern areas. In addition advanced Tracker provides up-to-date urbanisation information (6-month updates from 2016-2023). It allows an operational monitoring of settlement expansion hotspots.

Urban Green Analytics (NBS Potential)

This service integrates high-resolution Urban Green Areas with LULC, administrative units, and population forecasts to analyze greenery availability, accessibility, and inclusivity. Analysis revealed significantly more green areas in western districts and a clear east-west gradient in accessibility.

Urban Development Scenarios

Agent-Based Modeling using UD_InfraSim model provided by AIT colleagues allows users to simulate and analyze urban development scenarios. It helps forecast impacts of various development options, such as comparing urban densification versus sprawling scenarios, and economic development shifts.

Results

The deployment of Earth Observation technology has provided critical spatial intelligence for Amman, informing strategic planning, investment prioritization, and policy dialogues.

The EO-based approach has been successfully integrated into the World Bank's work program, supporting the development and optimization of the Bus Rapid Transit (BRT) system and associated transit-oriented development. EO data guided investment planning, focusing on improving pedestrian mobility, mitigating urban heat islands, and promoting densification along the BRT corridor.

The visualization of long-term urban trends has effectively showcased EO capabilities, depicting urbanization beyond administrative boundaries and identifying informal urbanization hotspots. The Agent-Based Model (ABM) simulation, generating "what if" scenarios, provides a general direction and signals urgency to policymakers.

Key insights from the analytical services included:

• Urban Green Analytics: Revealed an unbalanced distribution of green spaces, with more in western districts and a sharp east-west gradient in accessibility. Projections showed potential worsening of green inclusivity disparities by 2035 if no proactive greening actions are taken.
• Urban Development Scenarios: Comparative analysis showed that an urban sprawling scenario would lead to more than double the area endangered by higher potential risk due to topography compared to densification. An economic development shift scenario resulted in an almost 20% increase in new sealed areas.

Scalable EO service demonstrated high responsiveness, efficiency, and flexibility providing Greater Amman Municipality (GAM) with both strategic and operational insights, indicating significant integration potential to provide complex solution.

GDA Urban D5.1 Final Report: WP41 Users Feedback, Assessment and Future Planning (September 2023)