Global land mask for satellite ocean color remote sensing

Mikelsons, Karlis; Wang, Menghua; Wang, Xiao-Long; Jiang, Lide

doi:10.1016/j.rse.2021.112356

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

i

Global land mask for satellite ocean color remote sensing

2021
By Mikelsons, Karlis ; Wang, Menghua ; Wang, Xiao-Long ; ...
Source: Remote Sensing of Environment 257 (2021) 112356

[PDF-5.10 MB]

Select the Download button to view the document

This document is over 5mb in size and cannot be previewed

Details You May Also Like

Details:

Journal Title:

Remote Sensing of Environment
Personal Author:

Mikelsons, Karlis ; Wang, Menghua ; Wang, Xiao-Long ; Jiang, Lide

Mikelsons, Karlis ; Wang, Menghua ; Wang, Xiao-Long ; Jiang, Lide Less -
NOAA Program & Office:

CIRA (Cooperative Institute for Research in the Atmosphere) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research)

CIRA (Cooperative Institute for Research in the Atmosphere) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) Less -
Description:

We develop a methodology to derive a global medium resolution (250 m) land mask from several existing data sources. In particular, a number of improved land mask data sets have been developed from satellite measurements recently, though some artifacts and omissions still remain. We show how combining global land mask data from multiple independent data sources can decrease the frequency of artifacts, and improve the data consistency and quality. We use the ocean color product imagery derived from measurements of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) to evaluate and validate the new global land mask implemented in the Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system, and demonstrate the improvements in the derived global ocean color data coverage. Results show that when using the new proposed land mask the accuracy of global ocean color data coverage is significantly improved over coastal and inland waters. The new land mask more accurately represents the current global land coverage status, providing more complete and consistent global land/water coverage data set for ocean color remote sensing and for various other satellite Earth observing applications.
Keywords:

[+]

Coastal Waters Landsat MODIS Ocean Color Remote Sensing VIIRS Water Mask
Source:

Remote Sensing of Environment 257 (2021) 112356
DOI:

https://doi.org/10.1016/j.rse.2021.112356
Document Type:

Journal Article
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:9cc6a4001714952ce92cf7fefcf15d0d35b222ee4ee93a44fe14903a3aa416c4
Download URL:

https://repository.library.noaa.gov/view/noaa/30701/noaa_30701_DS1.pdf
File Type:

No Additional Files

More +

Global land mask for satellite ocean color remote sensing

Details:

Supporting Files

You May Also Like