2005Unpublished venueRequires access

Scale characteristics of remote sensing information: a case of shoreline

Zhang Huaguo, Donglin Li, Weigen Huang

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Abstract

The scale issue is the most important item in the remote sensing application. The scale affects the information contents of the remote sensing imagery. Usually, the scale is determined by the sensor resolution. In this paper, a series satellite remotely sensed images with different resolutions are adapted to study the scale characteristics of remote sensing. The results show that the natural shoreline is a representative fractal object, and its length is dependent on the scale or the remote sensing resolution. The scale fractal characteristics are the important to monitoring of shoreline. The length at a special scale can be calculated from property remote sensing images based on the study, which is meaningful for coastal remote sensing surveying.. I. INTRODUCTION The scale issue is the most important item in the remote sensing application. The scale affects the information contents of the remote sensing imagery. Usually, the scale of remote sensing information is determined by the sensor resolution. The results of remote sensing monitoring for the same object with different resolution images are discrepant. For example, the length of shoreline is related to the measure scale, here is the resolution of sensor. The shoreline derived from high resolution image is longer than that derived from lower resolution image.

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The scale issue is the most important item in the remote sensing application. The scale affects the information contents of the remote sensing imagery. Usually, the scale is determined by the sensor resolution. In this paper, a series satellite remotely sensed images with different resolutions are adapted to study the scale characteristics of remote sensing. The results show that the natural shoreline is a representative fractal object, and its length is dependent on the scale or the remote sensing resolution. The scale fractal characteristics are the important to monitoring of shoreline. The length at a special scale can be calculated from property remote sensing images based on the study, which is meaningful for coastal remote sensing surveying.. I. INTRODUCTION The scale issue is the most important item in the remote sensing application. The scale affects the information contents of the remote sensing imagery. Usually, the scale of remote sensing information is determined by the sensor resolution. The results of remote sensing monitoring for the same object with different resolution images are discrepant. For example, the length of shoreline is related to the measure scale, here is the resolution of sensor. The shoreline derived from high resolution image is longer than that derived from lower resolution image.

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Available abstract

The scale issue is the most important item in the remote sensing application. The scale affects the information contents of the remote sensing imagery. Usually, the scale is determined by the sensor resolution. In this paper, a series satellite remotely sensed images with different resolutions are adapted to study the scale characteristics of remote sensing. The results show that the natural shoreline is a representative fractal object, and its length is dependent on the scale or the remote sensing resolution. The scale fractal characteristics are the important to monitoring of shoreline. The length at a special scale can be calculated from property remote sensing images based on the study, which is meaningful for coastal remote sensing surveying.. I. INTRODUCTION The scale issue is the most important item in the remote sensing application. The scale affects the information contents of the remote sensing imagery. Usually, the scale of remote sensing information is determined by the sensor resolution. The results of remote sensing monitoring for the same object with different resolution images are discrepant. For example, the length of shoreline is related to the measure scale, here is the resolution of sensor. The shoreline derived from high resolution image is longer than that derived from lower resolution image.

Key concepts: Remote sensing, Scale (ratio), Shore, Image resolution, Computer science, Satellite imagery, Satellite, Resolution (logic)

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