Status: this preprint is currently under review for the journal ESSD.
Improved land mask for satellite remote sensing of oceans and inland waters
Karlis Mikelsonsand Menghua Wang
Abstract. We present an improved medium (250 m) spatial resolution land mask based on augmenting earlier results of Mikelsons et al. (2021) (https://doi.org/10.1016/j.rse.2021.112356) to reflect recent changes in global water surface coverage. This land mask update is critical for remote sensing of coastal oceans and inland waters as this is the first step to properly identify water pixels from land pixels for satellite data processing. We show that clear sky false color imagery derived for monthly and yearly time periods can be effectively used to identify changes to the surface water coverage. In addition, we also use Sentinel-2 satellite imagery to derive more accurate boundaries of new water bodies with complex geometries. We demonstrate improved coverage from satellite ocean color and inland water property retrievals with the improved land mask, including a range of new inland water bodies, as well as changes to the extent of the existing water bodies. The improved land mask can also be used for remote sensing of land, atmospheric, and cryosphere products.
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Overall, this kind of data which updated to recent state of water area is useful for the processing especially for algorithms dedicated to the ocean area. The one-file and one-byte format is convenient to use in processing data from the low-middle resolution global observation sensors. However the seasonal cycle may also affect the OC processing in the coast of the lake or big rivers and need to be considered. This data is indeed valuable in the current state, however it may have more value if it includes information of seasonal cycle orr probability (or coverage) of water cover within the pixels which may be obtained by authors already.
I think this datasets has the publication quality but it may be better to consider the following comments.
Specific comments:
Line-100 "In this study, we use a combination of yearly and monthly clear sky false color imageries from the recent years (2020–2025) ..";Â
 Do you have confirmed that the water areas have not changed except for areas listed in tables in this paper?
Line-123 " we imposed the requirement that more than 90% of high resolution (10 m) imagery pixels":
 Can you clarify that the 90% was applied to only spatial coverage or both spatial and temporal (considering seasonal change) coverage?
Line-295 "Overall, periodic updates are essential to maintain accuracy.":
 Can you propose the update period recommended for the natural and artificial changes?
NOAA National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E/RA3, 5830 University Research Court, College Park, MD 20740, USA
Global Science and Technology, Inc., Greenbelt, MD 20770, USA
NOAA National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E/RA3, 5830 University Research Court, College Park, MD 20740, USA
This work provides an improved medium resolution (~250 m) global land/water mask derived from an earlier data set (doi.org/10.17632/9r93m9s7cw.1), and includes the recent changes in the environment, as well as fixes some artifacts in the earlier data set. It highlights the use of global medium resolution clear sky true and false color imagery to detect changes in global surface water coverage, and helps to improve satellite water color retrievals in many new and recent water bodies.
This work provides an improved medium resolution (~250 m) global land/water mask derived from an...
Overall, this kind of data which updated to recent state of water area is useful for the processing especially for algorithms dedicated to the ocean area. The one-file and one-byte format is convenient to use in processing data from the low-middle resolution global observation sensors. However the seasonal cycle may also affect the OC processing in the coast of the lake or big rivers and need to be considered. This data is indeed valuable in the current state, however it may have more value if it includes information of seasonal cycle orr probability (or coverage) of water cover within the pixels which may be obtained by authors already.
I think this datasets has the publication quality but it may be better to consider the following comments.
Specific comments:
Line-100 "In this study, we use a combination of yearly and monthly clear sky false color imageries from the recent years (2020–2025) ..";Â
 Do you have confirmed that the water areas have not changed except for areas listed in tables in this paper?
Line-123 " we imposed the requirement that more than 90% of high resolution (10 m) imagery pixels":
 Can you clarify that the 90% was applied to only spatial coverage or both spatial and temporal (considering seasonal change) coverage?
Line-295 "Overall, periodic updates are essential to maintain accuracy.":
 Can you propose the update period recommended for the natural and artificial changes?