The purpose of this paper is to analyze the sensitivity of Geographic Information System outputs to errors in inputs derived from Remotely Sensed Data (RSD). The attention is restricted to outputs of suitability models with "per cell " decisions with gridded Geographic Data Bases(GDB) whose cells are larger than the RSD pixels. The procedure for merging RSD into such GDB's involves classification, registration and aggre-gation. The first two steps introduce errors at individual pixels and the last step tends to compensate for such errors
One factor limiting the accuracy of land cover maps derived from classified, remotely-sensed imagery...
Today, validation or accuracy assessment is an integral component of most mapping projects incorpora...
The error matrix is the most common way of expressing the accuracy of remote sensing image classific...
The purpose of this paper is to analyze the sensitivity of Geographic Information System outputs to ...
Different views of spatial resolution and accuracy present a major obstacle to the integration of re...
Remote Sensing and Geographic information System together comprise of Geographic Information Science...
Abstract. The concept of a “true ” ground-truth map is introduced, from which the inaccuracy/error o...
Th is paper reviews the necessary considerations and available techniques for assessing the accuracy...
Remotely sensed data are a key input to GIS-based spatial decision support systems for land cover an...
Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produc...
Aggregation may be used as a means of enhancing remotely-sensed data accuracy, but there is a tradeo...
The purpose of the present study was to review, evaluate and explore methodologies in classifying re...
The concept of a “true” ground-truth map is introduced, from which the inaccuracy/error of any produ...
The error matrix is the most common way of expressing the accuracy of remote sensing image classific...
Land cover maps are typically derived through classification of remotely-sensed data, usually relyin...
One factor limiting the accuracy of land cover maps derived from classified, remotely-sensed imagery...
Today, validation or accuracy assessment is an integral component of most mapping projects incorpora...
The error matrix is the most common way of expressing the accuracy of remote sensing image classific...
The purpose of this paper is to analyze the sensitivity of Geographic Information System outputs to ...
Different views of spatial resolution and accuracy present a major obstacle to the integration of re...
Remote Sensing and Geographic information System together comprise of Geographic Information Science...
Abstract. The concept of a “true ” ground-truth map is introduced, from which the inaccuracy/error o...
Th is paper reviews the necessary considerations and available techniques for assessing the accuracy...
Remotely sensed data are a key input to GIS-based spatial decision support systems for land cover an...
Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produc...
Aggregation may be used as a means of enhancing remotely-sensed data accuracy, but there is a tradeo...
The purpose of the present study was to review, evaluate and explore methodologies in classifying re...
The concept of a “true” ground-truth map is introduced, from which the inaccuracy/error of any produ...
The error matrix is the most common way of expressing the accuracy of remote sensing image classific...
Land cover maps are typically derived through classification of remotely-sensed data, usually relyin...
One factor limiting the accuracy of land cover maps derived from classified, remotely-sensed imagery...
Today, validation or accuracy assessment is an integral component of most mapping projects incorpora...
The error matrix is the most common way of expressing the accuracy of remote sensing image classific...