Being considered as a basic necessity and a key element in the development of sustainable communities, housing is a major concern for the Algerian government. Algiers is facing for the last years a challenging housing shortage and as a way to overcome this problem, many housing projects have been launched. However, the pressing need to address this crisis has disregarded what the pattern of landscape will be, how the existing infrastructures will accommodate with such housing projects and how they will impact on human well-being. This research aims to advance the challenges of planning for sustainability by proposing a methodological approach in a context of high lack of data to support decision-makers in the elaboration of affordable housing projects. The main objective is to trade off urban growth with residential satisfaction and the preservation of natural resources. We developed two Cellular Automata (CA) based residential development scenarios to identify suitable locations for future affordable housing projects: Urban densification scenario (UD) and Constrained urban sprawl scenario (CUS). Both scenarios are based on indicators of residential preferences and measures taken in order to counter the negative effects of urbanization. Results reveal the low capacity of Algiers to meet the housing shortage according to the conditions set for each scenario. The scenarios were evaluated by quantifying their spatial patterns using a preselected set of six class-level landscape metrics. Results show a combination of aggregated and dispersed patterns growth for both scenarios meeting trade-offs among the advantages and the challenges of urban densification and urban sprawl. Then, Standard deviation and regression analysis were conducted to assess the accuracy of CA simulation and the evaluation of pattern changes in the simulated scenarios. The resulting values indicate the good performance of CA and confirm its effectiveness in predicting the future locations of housing projects.

住房被认为是可持续社区发展的基本必需品和关键要素，是阿尔及利亚政府的主要关注点。阿尔及尔在过去几年面临着严峻的住房短缺问题，作为克服这一问题的一种方式，许多住房项目已经启动。然而，解决这场危机的迫切需要忽视了景观格局、现有基础设施将如何适应此类住房项目以及它们将如何影响人类福祉。本研究旨在通过在数据严重缺乏的情况下提出一种方法论方法来支持决策者制定经济适用房项目，从而推进可持续性规划的挑战。主要目标是在城市发展与居住满意度和自然资源保护之间取得平衡。我们开发了两个基于元胞自动机 (CA) 的住宅开发场景，以确定未来经济适用房项目的合适地点：城市致密化场景 (UD) 和受限城市蔓延场景 (CUS)。这两种情景都是基于居住偏好指标和为应对城市化的负面影响而采取的措施。结果表明，根据为每种情景设定的条件，阿尔及尔应对住房短缺的能力较低。这些场景是通过使用一组预选的六个级别景观指标量化它们的空间模式来评估的。结果显示，两种情景的聚合和分散模式增长相结合，满足了城市致密化和城市扩张的优势和挑战之间的权衡。然后，进行标准偏差和回归分析，以评估CA模拟的准确性和模拟场景中模式变化的评估。结果值表明 CA 的良好性能，并证实其在预测住房项目未来位置方面的有效性。