The predictive modeling process involves remotely sensed imagery, Geographic Information System (GIS) data and techniques, and multivariate statistical approaches.
We concluded that ALS data can be used as a potential source of data to "enlarge" small ground sample plots and to be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.
Therefore, we can conclude that ALS can be used as a potential source of data to "enlarge" small ground sample plots that can be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.
Finally, based on our findings, we can conclude that ALS data can be used as a potential source of data to "enlarge" small ground sample plots that could be used for evaluation and calibration of remotely sensed datasets provided by global systems with coarse spatial resolutions.
The availability of new generations of remotely sensed datasets and geographical information system (GIS) models (i.e. GEMS, RothC, and CENTURY) provides new opportunities for predicting soil properties and quality at different spatial scales.
To help in developing a control programme, delineating areas of risk, geographical information system and remotely sensed environmental images were used to developed predictive risk maps of the probability of occurrence of the disease and quantify the risk for infection in Ogun State, Nigeria.
Transmission and prevalence of vector-borne diseases such as malaria are highly influenced by spatial and temporal changes in the environment as described during the last 20 years by geographic information systems (GIS) and remotely sensed (RS) data [3], [4].
According to the basic principle of grid computing, we construct a distributed processing system for processing remotely sensed images.
In this paper, we present the concepts, design and implementation of VDM-RS, a visual data mining system for classifying remotely sensed images and exploring image classification processes.
From a test analysis of our system, TARIES.NET, the whole image-processing system is evaluated, and the results show the feasibility of the model design and the efficiency of the remotely sensed image distributed and parallel processing system.
