Using Window Regression to Gap-Fill Landsat ETM+ Post SLC-Off Data

Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach

International Journal of Remote Sensing Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713722504 Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach C. Zhang a; W. Li a; D. Travis b a Department of Geography, Kent State University, b Department of Geography and Geology, Universit...

Filling Landsat ETM+ SLC-off Gaps Using a Segmentation Model Approach

he purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in...

Making Use of the Landsat 7 SLC-off ETM+ Image Through Different Recovering Approaches

Integration of Lidar and Landsat Etm+ Data

Lidar data provide accurate measurements of forest canopy structure in the vertical plane however current lidar sensors have limited coverage in the horizontal plane. Landsat data provide extensive coverage of generalized forest structural classes in the horizontal plane but are relatively insensitive to variation in forest canopy height. It would therefore be desirable to integrate lidar and L...

Survey on Gap Filling Algorithms in Landsat 7 Etm+ Images

In remote sensing images the gapping is a known phenomenon. There are several reasons for image gaps, e.g. shadowed area for SAR data sets, cloud coverage for optical imagery and instrument errors such as SLC-off failure. On May 13, 2003 the Scan Line Corrector (SLC) of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed permanently causing around 20% of pixels per scene not scanned wh...