Nature-driven placemaking, underpinned by biophilic design, provides transformative potential for urban environments in arid or dry-continental regions. In Sect. 2, “Community-Level Interventions”, we demonstrate how Geographic Information Systems (GIS) can guide the strategic planning of nature-oriented streetscapes in Tashkent, Uzbekistan, by combining multi-temporal remote sensing with structured stakeholder engagement. First, we apply a 5-year Normalized Difference Vegetation Index (NDVI) analysis (2020–2024) to classify urban vegetation into four cover classes and compute district-level proportions of bare, sparse, and vegetated areas. These maps reveal that existing biophilic walking routes closely align with high-NDVI corridors along the canal network, while several districts show declines in sparse vegetation, pinpointing priority zones for greening. A pixel-wise ΔNDVI map further identifies localized “hotspots” of loss and gain. Building on these empirical insights, we present an integrative, reproducible workflow—illustrated in a detailed process flow (Fig. 4)—that merges GIS analytics with participatory design. Community validation through Mahalla Committee workshops and professional charrettes confirms the accuracy of our corridor detections and refines on-the-ground planting proposals. Policy integration steps, in collaboration with the Municipal Planning Department, translate our statistical findings into updated GIS layers and budget targets for district greening quotas. We conclude by offering a replicable roadmap for scaling this biophilic framework across Central Asian cities (e.g. Samarkand, Bukhara, Namangan), recommending the establishment of a regional Green Cities Consortium, embedding biophilic metrics into city master plans, and mobilizing community data streams for continual route optimization. This chapter’s novel contribution is a concise, empirically validated model—grounded in both “big-data” mapping and local knowledge—for designing resilient, culturally resonant biophilic streetscapes in extreme-climate contexts.