Spatial Forecast of Landslides in Three Gorges Based On Spatial Data Mining
نویسندگان
چکیده
منابع مشابه
Spatial Forecast of Landslides in Three Gorges Based On Spatial Data Mining
The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetatio...
متن کاملChange Detection Based on Spatial Data Mining
Spatial data mining (SDM) and change detection (CD) are hot issues in the field of geospatial information processing. Considering the feasibility of discovering knowledge from spatial database and the demands of knowledge for change detection, the paper presents that change detection needs knowledge and technology of SDM should be integrated into applications of change detection. Special knowle...
متن کاملUncertainty-based Spatial Data Mining
Although uncertainties exist in spatial data mining, they have not been paid much attention to. Uncertainty may have an influence on the confidential level, supportable level, and interesting level of spatial data mining. This paper proposes uncertainty-based spatial data mining. First, the concept is given in the integrated contexts of both uncertainty and spatial data mining. The inherent unc...
متن کاملOn Model Based Clustering in a Spatial Data Mining Context
In this paper we present the finite mixture models approach to clustering of high dimensional data. The mixture resolving approach to cluster analysis has been addressed in a number of different ways; the underlying assumption is that the patterns to be clustered are drawn from one of several distributions, and the goal is to identify the parameters of each and (perhaps) their number. Finite mi...
متن کاملFuzzy Spatial Data Mining
A fuzzy spatial data mining technique has been developed to extract relationships describing relative position of classes of objects from raster images. Several different rule forms are described which represent different types of directional relationships between classes of objects. The method has been tested with hand-generated, synthetic, and sonar imagery.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2009
ISSN: 1424-8220
DOI: 10.3390/s90302035