Oz Kira

Purpose – This study aims to present a GIS-based spatial decision-support workflow that converts climate-driven agricultural threshold crossing into proactive planning for district-scale housing, renewable-energy infrastructure and open-space protection. Design/methodology/approach – DSSAT-CERES-Wheat is used to define a planning trigger for rain-fed wheat, namely the first year in which simulated yields remain below a locally relevant economic threshold. This trigger activates a GIS workflow in which statutory-plan layers, settlements, transport infrastructure, power lines and protected areas are transformed into suitability surfaces and allocated under development-priority, conservation-priority and neutral policy scenarios. Findings – Scenario maps show that threshold crossing can expose former agricultural land to sharply divergent spatial pathways. Development-priority policies increase urban and rural housing footprints and potential sprawl, while conservation-priority policies preserve open-space continuity. PV allocation depends strongly on grid proximity and therefore competes spatially with both housing and conservation objectives. A weighting and distance-decay sensitivity test shows that allocation shares change substantially, especially under development priority, but the contrast between conservation-oriented and development-oriented policy paths remains interpretable. A retrospective validation against 1995–2025 urban expansion in Ofakim and Netivot shows that most observed expansion occurred in the highest urban-influence class, supporting the urban distance-decay component. Practical implications – The workflow allows planners to stress-test district plans, identify where agricultural conversion pressure may become a district-planning issue and compare compact growth, renewable-energy deployment and biodiversity protection before statutory plans are revised. Originality/value – The paper offers a modular, reproducible workflow that links agricultural-threshold timing with statutory planning constraints and scenario-based allocation, extending built-environment decision support beyond building-scale sustainability toward district-scale land-use transitions.