The landscape patterns are the results of the human activity that adapts the land cover and its use (LUC) to constraints or economic opportunities encountered by various actors. The temporal and spatial arrangement of LUC has a strong influence on environmental risks (natural habitat and biodiversity, water quality protection, soil erosion). Its knowledge allows to develop prospective simultation models to assess the impact of different scenarios on the evolution of the land use and land cover change (LUCC). This paper presents a methodology based on stochastic models to identify, locate and simulate the temporal LUCC of regions differentiated by spatial association of land use successions. We compare the association of land use successions by means of "neutral" models. The concept of a "neutral" model has been introduced in ecology for describing the characteristics of coexisting populations in a territory. Every individual - whatever its species it belongs to in the ecosystem - undergoes the same constraints without taking precedence over another. We propose in this proposal an improvment of our pst works with a simulation model process based on Hidden Markov Model at 2 order. Precisely, we propose a territorial simulation method that takes into account the dynamics of temporal and spatial patterns of previous crop successions oserved in different sub-regions. Three steps are proposed by "Arpentage_S" : 1- We carry out a classification of the territory in homogeneous patches with respect to their LUC. 2- The simulation of the LUC succession is the made on these patches at the pixel level taking into account the crop successions that were practiced the previous two years. 3- The differences between simulated land use, step by step - year per year, and observed data measured the trend changes. This difference measurment make possible the detection breaks in the process of landscape managment according to the constraints or opportunities for farmers. 4- Difference between modelling land use changes and measured land use changes are spatialzed to be mapped using the pixel recognition rate on a rasterized representation of the territory. To test our method, we assess our modeling Arpentage_S on local a dataset (110 km2) that come from surveys in the Vittel-Contrexeville territory (East of France) with a 16 years temporal exhaustive data. This territory is focused on water quality and biodiversity management issues. We recongnize 4 landscape units based on similar temporel and spatial dynamics, and we evaluate the capacity of our territorial simulation method. To conclude we propose to include this proposal in the trend of landscape agronomy as a contribution for agronomists to land use science. PS : Our ArpentAge_S model is free, as on open access licence.