Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking

التفاصيل البيبلوغرافية
العنوان: Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking
المؤلفون: Ian M. Howat, Y. Ahn
المصدر: IEEE Transactions on Geoscience and Remote Sensing. 49:2838-2846
بيانات النشر: Institute of Electrical and Electronics Engineers (IEEE), 2011.
سنة النشر: 2011
مصطلحات موضوعية: Matching (statistics), geography, Rift, geography.geographical_feature_category, Pixel, Computer science, Data editing, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Multi-image, Glacier, Glaciology, Sea level rise, Null (SQL), Thematic Mapper, General Earth and Planetary Sciences, Electrical and Electronic Engineering, Ice sheet, Algorithm, Remote sensing
الوصف: Observations of ice motion are critical for constraining ice sheet mass balance and contribution to sea level rise, as well as predicting future changes. A wealth of imagery now exists for measuring ice motion from space, but existing repeat-image feature-tracking (RIFT) algorithms require the selection of several location- and data-specific parameters and manual data editing and are therefore not efficient for processing large numbers of image pairs for differing regions. Here, we present the multiple-image/multiple-chip RIFT algorithm which does not involve any user-defined local/empirical parameters and has a higher matching success rate than conventional single-image single-chip correlation matching. We also present an efficient method for applying RIFT to null-value striped data, such as the Landsat-7 Enhanced Thematic Mapper Plus. This method offers the potential for fully automated processing of large data sets.
تدمد: 1558-0644
0196-2892
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::ad8aff39fba27ecb5bc2dae835c52408
https://doi.org/10.1109/tgrs.2011.2114891
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........ad8aff39fba27ecb5bc2dae835c52408
قاعدة البيانات: OpenAIRE