In this chapter, we present two approaches for clustering spatial functional data. The first one is the model-based that uses concept of density random variables. second hierarchical based on univariate statistics data such as mode or mean. These take into account features data: observations are spatially close and share a common distribution associated methodologies illustrated by an applicati...

Extended Abstract. Inferences for spatial data are affected substantially by the spatial configuration of the network of sites where measurements are taken. Consider the following standard data-model framework for spatial data. Suppose a continuous, spatially-varying quantity, Z, is to be observed at a predetermined number, n, of points ....[ To Countinue Click here]

The information needed for River Basin Management covers a wide range of hydrological and environmental data and methods. Since all measurement data are spatial and time related, spatial services fulfill the requirements in a decision making process best. In this work an open data structure for storing spatial temporal related data is proposed. Based on the data structure the modeling process c...

A possible set of requirements for a future GIS spatial data structure is that it should have no topological gaps in it at any time, that it should be locally updateable and hence permit real-time updating, editing and querying, that full object insertion and deletion should be supported (i.e. dynamism), that a primitive object on the map should equal one object in the data structure, that obje...

Modeling spatial interactions that arise in spatially referenced data is commonly done by incorporating the spatial dependence into the covariance structure either explicitly or implicitly via an autoregressive model. In the case of lattice (regional summary) data, two common autoregressive models used are the conditional autoregressive model (CAR) and the simultaneously autoregressive model (S...

estimation and mapping of forest resources are preconditions for management, planning and research. in this study, we applied kriging interpolation of geostatistics for estimation and mapping of forest stock at-tributes in a natural, uneven-aged, unmanaged forest in the caspian region of northern iran. the site of the study has an area of 516 ha and an elevation that ranges from 1100 to 1450 m ...