Large Area Scene Selection Interface (LASSI) | Zendy

Shan Franks | Zendy; Jeffrey G. Masek | Zendy; Rachel Headley | Zendy; John Gasch | Zendy; Terry Arvidson | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Large Area Scene Selection Interface (LASSI)

Author(s) -

Shan Franks,

Jeffrey G. Masek,

Rachel Headley,

John Gasch,

Terry Arvidson

Publication year - 2009

Publication title -

photogrammetric engineering and remote sensing

Language(s) - English

Resource type - Journals

eISSN - 2374-8079

pISSN - 0099-1112

DOI - 10.14358/pers.75.11.1287

Subject(s) - weighting , orthophoto , remote sensing , selection (genetic algorithm) , set (abstract data type) , land cover , computer science , interface (matter) , data set , geography , geological survey , cloud computing , footprint , cloud cover , data mining , cartography , artificial intelligence , land use , geology , meteorology , engineering , archaeology , capillary number , capillary action , medicine , paleontology , civil engineering , radiology , programming language , operating system

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004 to 2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat-7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm’s sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research