Cherishing Human-Elephant Landscapes with GIS-LBS: A LUCIS-Based Negotiation Framework for Human-Elephant Coexistence in Sri Lanka

Conflicts over land and ecological heritage increasingly require planners to treat plans not as fixed blueprints but as negotiated agreements over space, values, and future risk. Collaborative and communicative planning traditions emphasise that durable spatial decisions emerge through iterative bargaining – where maps, scenarios, and design proposals act as shared “boundary objects” that help parties externalise trade-offs and explore mutually beneficial solutions (HEALEY, 2020; BAR-SINAI, 2013). However, while negotiation is widely discussed in planning theory, it is still weakly operationalised in everyday practice, especially in multi-stakeholder settings shaped by power asymmetries, competing mandates, and contested evidence (RUMING, 2012; KARTZIOS et al., 2022). A further challenge is that many land–ecology conflicts behave as complex systems: outcomes emerge from interacting processes, feedback loops, and adaptation across actors and environments, often producing nonlinear change and shifting hotspots over time. In urban science and complexity perspectives suggest that such contested socio-ecological landscapes require an Urban Informatics stance – integrating big data, sensing, and computing to support dynamic, evidence-updated decision-support systems and applications, rather than relying solely on conventional land-use allocation logic and periodic plan revisions (BATTY, 2013; SHI, GOODCHILD, BATTY et al., 2021). Methodologically, many planning support tools remain oriented toward spatial optimisation or impact assessment, rather than negotiation itself. Multi-criteria frameworks (e.g., AHP) can formalise stakeholder priorities, yet weights often remain expert-driven and opaque. Game-theoretic approaches offer a complementary lens by representing stakeholders as strategic actors with distinct objectives and utilities, enabling systematic testing of stability (e.g., near-equilibrium outcomes) and efficiency (e.g., Pareto- improving compromises) across alternative spatial strategies (ZARREH GROGAN, 2025). Importantly, negotiation-oriented modelling must remain participatory and transparent, supporting learning and trust rather than acting as a technocratic “black box” (CUHADAR, 2004). Human-Elephant Conflict (HEC) in Sri Lanka is a particularly urgent arena for such negotiation-capable, informatics-oriented planning support. HEC is not only a conservation challenge but also a land-use and spatial justice problem in mixed agricultural–settlement landscapes that overlap elephant home ranges and corridors (GUNAWANSA et al., 2023). These landscapes are continuously reshaped by cultivation cycles, settlement expansion, infrastructure, and seasonal resource conditions – interacting with elephant movement to create persistent yet evolving conflict patterns – thereby reinforcing the need for dynamic, evidence-driven planning beyond static master-plan prescriptions. This paper advances a GIS-LBS–enabled negotiation framework that couples (i) LUCIS-based suitability and conflict mapping (CARR ZWICK, 2007) with (ii) LBS-derived GPS elephant movement as an empirical validation lens, and (iii) game-theoretic analysis to evaluate negotiated outcomes across three strategy families: coexistence, partial separation, and full separation. By explicitly linking spatial modelling, movement evidence, and negotiation analytics, the framework provides a transparent basis to “cherish heritage” through evidence-based, politically feasible landscape sharing – supported by adaptive, data-informed planning applications – rather than purely separation-oriented interventions.