We introduce the Local Intersectional Visual Spaces (LIVS) dataset, a benchmark for multi-criteria alignment, developed through a two-year participatory process with 30 community organizations to support the pluralistic alignment of text-to-image (T2I) models in inclusive urban planning. The dataset encodes 37,710 pairwise comparisons across 13,462 images, structured along six criteria—Accessibility, Safety, Comfort, Invitingness, Inclusivity, and Diversity—derived from 634 community-defined concepts. Using Direct Preference Optimization (DPO), we fine-tune Stable Diffusion XL to reflect multi-criteria spatial preferences and evaluate the LIVS dataset and the fine-tuned model through four case studies: (1) DPO increases alignment with annotated preferences, particularly when annotation volume is high; (2) preference patterns vary across participant identities, underscoring the need for intersectional data; (3) human-authored prompts generate more distinctive visual outputs than LLM-generated ones, influencing annotation decisiveness; and (4) intersectional groups assign systematically different ratings across criteria, revealing the limitations of single-objective alignment. While DPO improves alignment under specific conditions, the prevalence of neutral ratings indicates that community values are heterogeneous and often ambiguous. LIVS provides a benchmark for developing T2I models that incorporate local, stakeholder-driven preferences, offering a foundation for context-aware alignment in spatial design.

After a disaster strikes, the disaster victims usually become isolated and unable to utilize communication services for an extended period of time. Therefore, it is essential to establish a communication network that can operate when there is no power or infrastructure. In this paper, we focus on Satellite/Solar-powered Mesh Integrated Networks (SMIN), which are composed of a communication satellite, Earth Stations (ESs) and solar-powered Mesh Routers (MRs). A SMIN can connect to external networks via satellite and provide communication services in a large area through the wireless mesh network (WMN). To maximize the amount of communication traffic from the WMN, we aim to optimize the number of ESs and its deployment. When the number of ESs increases, the hop count between a MR and its closest ES decreases, thus resulting in an improved connectivity in the route. However, since the ESs share the bandwidth of satellite, allocated bandwidth to each ES decreases as the number of ESs increases. Therefore, we aim to optimize the number and deployment pattern of ESs. Additionally, we validate the amount of aggregated traffic that can be sent to the satellite through numerical analysis.