Automated cloud and cloud shadow identification in Landsat MSS imagery for temperate ecosystems
نویسندگان
چکیده
منابع مشابه
Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing
The use of Landsat data to answer ecological questions is greatly increased by the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow. The method uses a neural network approach to determine cloud, cloud shadow, water, snow/ice and cl...
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Accurate masking of cloud and cloud shadow is a prerequisite for reliable mapping of land surface attributes. Cloud contamination is particularly a problem for land cover change analysis, because unflagged clouds may be mapped as false changes, and the level of such false changes can be comparable to or many times more than that of actual changes, even for images with small percentages of cloud...
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Detecting clouds in satellite imagery is becoming more important with increasing data availability, however many earth observation sensors are not designed for this task. In Satellite pour l’Observation de la Terre 5 (SPOT5) High Resolution Geometrical (HRG) imagery, the reflectance properties of clouds are very similar to common features on the earth’s surface, in the four available bands (gre...
متن کاملAutomated Production of Cloud-free and Cloud Shadow-free Image Mosaics from Cloudy Satellite Imagery
The humid tropical region is always under partial or complete cloud covers. As a result, optical remote sensing images of this region always encounter the problem of cloud covers and associated shadows. In this paper, an operational system for producing cloud-free and cloud shadow-free image mosaics from cloudy optical satellite imagery is presented. The inputs are several cloudy images of the ...
متن کاملObject-based Cloud and Cloud Shadow Detection in Landsat Images for Tropical Forest Monitoring
Clouds and cloud shadows often obscure parts of images acquired by optical space-borne sensors. The clouds and cloud shadows need to be detected and labeled as missing data. This enables subsequent methods to make their own decisions about how the missing data should be handled. Here we propose an automatic method to detect daytime cloud and cloud shadows in the context of tropical forest monit...
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ژورنال
عنوان ژورنال: Remote Sensing of Environment
سال: 2015
ISSN: 0034-4257
DOI: 10.1016/j.rse.2015.08.006