विधियों की तुलना करें

	Land-Use Change Modeling	Lowry Land-Use Transport Model
क्षेत्र	Human Geography	Human Geography
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	2002	1964
प्रवर्तक	Peter H. Verburg and colleagues (CLUE-S); broader land-change-science community	Ira S. Lowry
प्रकार	Family of spatially explicit models simulating land-use and land-cover change	Spatial-interaction-based land-use and activity allocation model of a metropolitan area
मौलिक स्रोत	Verburg, P. H., Soepboer, W., Veldkamp, A., Limpiada, R., Espaldon, V., & Mastura, S. S. A. (2002). Modeling the spatial dynamics of regional land use: the CLUE-S model. Environmental Management, 30(3), 391–405.	Lowry, I. S. (1964). A Model of Metropolis (RM-4035-RC). RAND Corporation, Santa Monica, CA.
उपनाम	Land Change Modeling, LUCC Simulation, Spatial Land-Use Allocation Modeling, Land-Use Scenario Modeling	Lowry Model, Model of Metropolis, Lowry-Garin Model, Land-Use Transport Interaction Model
संबंधित	4	4
सारांश	Land-use change modeling is the umbrella family of methods that simulate how the land surface is converted between uses — forest to farmland, farmland to city — by combining where change is likely with how much change is demanded. A typical model statistically relates observed change to spatial drivers such as slope, roads, and population, sets future demand for each land-use class from scenarios, and then allocates that demand across space to the most suitable cells, iterating until supply meets demand. The CLUE-S model of Verburg and colleagues, alongside the Land Change Modeler and SLEUTH, exemplifies this demand-plus-allocation architecture that underpins much of land-change science.	The Lowry model is the foundational operational model of urban land use, allocating where people live and where services locate around a given pattern of basic employment using spatial-interaction (gravity) distribution. Devised by Ira S. Lowry at the RAND Corporation in 1964 as 'A Model of Metropolis', it treats the city as a system in which basic jobs attract resident workers, those residents demand local services, and the resulting service jobs attract still more residents — a chain solved by iteration until the whole system balances. It launched the entire field of land-use and transport interaction modelling.