DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA
In this paper, we propose a framework to detect human activities by constructing super-resolution images from the MODIS data. The highest resolution of the MODIS images is 250 meters per pixel, which is usually not enough to detect human activities. By magnifying and de-blurring the low resolution M...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.669.849 2023-05-15T14:56:15+02:00 DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA Shizhi Chen Yingli Tian William S. Weiss The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.849 http://media-lab.engr.ccny.cuny.edu/%7Emedia-server/Publications/ASPRS_2012.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.849 http://media-lab.engr.ccny.cuny.edu/%7Emedia-server/Publications/ASPRS_2012.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://media-lab.engr.ccny.cuny.edu/%7Emedia-server/Publications/ASPRS_2012.pdf Satellite Image Human Activity Detection Arctic Ocean Super-Resolution MODIS Data text ftciteseerx 2016-01-08T17:16:26Z In this paper, we propose a framework to detect human activities by constructing super-resolution images from the MODIS data. The highest resolution of the MODIS images is 250 meters per pixel, which is usually not enough to detect human activities. By magnifying and de-blurring the low resolution MODIS image through the Support-Vector Regression, the constructed super-resolution image can achieve 4 to 8 times higher resolution than the original MODIS image. To evaluate the feasibility of the super-resolution MODIS images for the application of human activity detection, we collect a dataset by selecting four land cover types through Google Earth: the land with human activities, the land without human activities, the water without ice, and the land covered with snow and ice. Using a learning-based method, surface reflectance from the super-resolution MODIS image predicts land cover type of a geo-location specified by latitude and longitude. Experimental results demonstrate feasibility of the proposed approach for human activity detection using the super-resolution MODIS images. Text Arctic Arctic Ocean Unknown Arctic Arctic Ocean |
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language |
English |
topic |
Satellite Image Human Activity Detection Arctic Ocean Super-Resolution MODIS Data |
spellingShingle |
Satellite Image Human Activity Detection Arctic Ocean Super-Resolution MODIS Data Shizhi Chen Yingli Tian William S. Weiss DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA |
topic_facet |
Satellite Image Human Activity Detection Arctic Ocean Super-Resolution MODIS Data |
description |
In this paper, we propose a framework to detect human activities by constructing super-resolution images from the MODIS data. The highest resolution of the MODIS images is 250 meters per pixel, which is usually not enough to detect human activities. By magnifying and de-blurring the low resolution MODIS image through the Support-Vector Regression, the constructed super-resolution image can achieve 4 to 8 times higher resolution than the original MODIS image. To evaluate the feasibility of the super-resolution MODIS images for the application of human activity detection, we collect a dataset by selecting four land cover types through Google Earth: the land with human activities, the land without human activities, the water without ice, and the land covered with snow and ice. Using a learning-based method, surface reflectance from the super-resolution MODIS image predicts land cover type of a geo-location specified by latitude and longitude. Experimental results demonstrate feasibility of the proposed approach for human activity detection using the super-resolution MODIS images. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Shizhi Chen Yingli Tian William S. Weiss |
author_facet |
Shizhi Chen Yingli Tian William S. Weiss |
author_sort |
Shizhi Chen |
title |
DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA |
title_short |
DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA |
title_full |
DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA |
title_fullStr |
DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA |
title_full_unstemmed |
DETECTING HUMAN ACTIVITIES IN THE ARCTIC OCEAN BY CONSTRUCTING AND ANALYZING SUPER-RESOLUTION IMAGES FROM MODIS DATA |
title_sort |
detecting human activities in the arctic ocean by constructing and analyzing super-resolution images from modis data |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.849 http://media-lab.engr.ccny.cuny.edu/%7Emedia-server/Publications/ASPRS_2012.pdf |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean |
genre_facet |
Arctic Arctic Ocean |
op_source |
http://media-lab.engr.ccny.cuny.edu/%7Emedia-server/Publications/ASPRS_2012.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.849 http://media-lab.engr.ccny.cuny.edu/%7Emedia-server/Publications/ASPRS_2012.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766328267396087808 |