Dinâmica da paisagem do Projeto de Assentamento Tarumã Mirim: uma contribuição temporal e preditiva

Abstract

The space dynamic modelling technique stands out by its capacity to show the landscape evolution of the Tarumã Mirim Stablishment Project in a predctive way, assisting studies on the use of natural resources, territorial planning and allowing a view of the presence or absence of specific public policies. That is because the planning of a rural settlement must take into account the land use and its positive or negative impacts generated in this process. The evolution of that landscape since the creation of the PA, in march 1992, makes possible a stochastic projection for 2011, even it was made during the erlier period of 1995 to 2003. That projection was able to report growth rates and removal of vegetation carried out by human action. It was used two scenes of the orbit 231 and section 062 of the years 1995 and 2003, properly cut from the area of study and applying the Markov Chains Theory, supported by remote sensing technique that delimited the area. It was classified the land use and land cover. It was made the cross-tabulation of the classes showing the transition between them and the probability of changes and projection of land use for 2011. From 42,910.760 hectares intended for settlement and farming family in 1995, wich is the baseline time for predictive modeling, it was identified by the classification of land use in order to 1,119.60 ha, in 2003 3,075.30 ha and a projection of land use for 2011 about 10,023.30 ha, and the removal of vegetation cover in 1995 47,069.10 ha, in 2003 45,113.40 ha and the projection of vegetation removed for 2011 (simulation) is about 38,165.40 hectares deforested. The study revealed in its modeling of the dynamics use of land for future scenarios, a concerning situation that should be reviewed and demands a special attention referred to positive and negative environmental and hydrological network, recommended in the plan for environmental control and protection of ciliary forests.