{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["026:00"], "contactPoint": {"@type": "vcard:Contact", "fn": "Elizabeth Foughty", "hasEmail": "mailto:elizabeth.a.foughty@nasa.gov"}, "description": "DISTRIBUTED ANOMALY DETECTION USING SATELLITE DATA FROM\r\nMULTIPLE MODALITIES\r\n\r\nKANISHKA BHADURI*, KAMALIKA DAS**, AND PETR VOTAVA***\r\n\r\nAbstract. There has been a tremendous increase in the volume of Earth Science data over the\r\nlast decade from modern satellites, in-situ sensors and different climate models. All these datasets\r\nneed to be co-analyzed for finding interesting patterns or for searching for extremes or outliers.\r\nInformation extraction from such rich data sources using advanced data mining methodologies is\r\na challenging task not only due to the massive volume of data, but also because these datasets\r\nate physically stored at different geographical locations. Moving these petabytes of data over the\r\nnetwork to a single location may waste a lot of bandwidth, and can take days to finish. To solve this\r\nproblem, in this paper, we present a novel algorithm which can identify outliers in the global data\r\nwithout moving all the data to one location. The algorithm is highly accurate (close to 99%) and\r\nrequires centralizing less than 5% of the entire dataset. We demonstrate the performance of the\r\nalgorithm using data obtained from the NASA MODerate-resolution Imaging Spectroradiometer\r\n(MODIS) satellite images.", "distribution": [{"@type": "dcat:Distribution", "description": "DISTRIBUTED ANOMALY DETECTION USING SATELLITE DATA FROM MULTIPLE MODALITIES", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/Paper_9_.pdf", "format": "PDF", "mediaType": "application/pdf", "title": "Paper 9 .pdf"}], "identifier": "DASHLINK_231", "issued": "2010-10-13", "keyword": ["ames", "dashlink", "nasa"], "landingPage": "https://c3.nasa.gov/dashlink/resources/231/", "modified": "2025-03-31", "programCode": ["026:029"], "publisher": {"@type": "org:Organization", "name": "Dashlink"}, "title": "DISTRIBUTED ANOMALY DETECTION USING SATELLITE DATA FROM MULTIPLE MODALITIES"}