Cloud detection algorithm comparison and validation for operational Landsat data products

https://ntrs.nasa.gov/api/citations/20190028663/downloads/20190028663.pdf

The Harmonized Landsat and Sentinel-2 surface reflectance data set

Increasing human populations around the global coastline have caused extensive loss, degradation and fragmentation of coastal ecosystems, threatening the delivery of important ecosystem services1. As a result, alarming losses of mangrove, coral reef, seagrass, kelp forest and coastal marsh ecosystems have occurred1–6. However, owing to the difficulty of mapping intertidal areas globally, the distribution and status of tidal flats—one of the most extensive coastal ecosystems—remain unknown7. Here we present an analysis of over 700,000 satellite images that maps the global extent of and change in tidal flats over the course of 33 years (1984–2016). We find that tidal flats, defined as sand, rock or mud flats that undergo regular tidal inundation7, occupy at least 127,921 km2 (124,286–131,821 km2, 95% confidence interval). About 70% of the global extent of tidal flats is found in three continents (Asia (44% of total), North America (15.5% of total) and South America (11% of total)), with 49.2% being concentrated in just eight countries (Indonesia, China, Australia, the United States, Canada, India, Brazil and Myanmar). For regions with sufficient data to develop a consistent multi-decadal time series—which included East Asia, the Middle East and North America—we estimate that 16.02% (15.62–16.47%, 95% confidence interval) of tidal flats were lost between 1984 and 2016. Extensive degradation from coastal development1, reduced sediment delivery from major rivers8,9, sinking of riverine deltas8,10, increased coastal erosion and sea-level rise11 signal a continuing negative trajectory for tidal flat ecosystems around the world. Our high-spatial-resolution dataset delivers global maps of tidal flats, which substantially advances our understanding of the distribution, trajectory and status of these poorly known coastal ecosystems. Analyses of over 700,000 satellite images to map the global extent of tidal flats over the past thirty years, and enable assessments of the status and likely future trajectories of these coastal ecosystems.

The global distribution and trajectory of tidal flats

Fmask 4.0: Improved cloud and cloud shadow detection in Landsats 4–8 and Sentinel-2 imagery

Interest in knowing more about the Earth’s land cover and how it has changed over time motivated the mission and sensor design of early terrestrial remote sensing systems. Rapid developments in com...

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2018.1452075

Land cover 2.0

Iceberg calving is an efficient mechanism for ice mass loss, and rapidly calving glaciers are often considered to be inherently unstable. However, the physical controls on calving are not well understood. Recent studies hypothesize that the presence of a rigid ice melange (composed of icebergs, bergy bits, and sea ice) can reduce iceberg calving by providing “backstress” to the terminus. To test this hypothesis the authors use remote sensing techniques to construct a time series model of calving rate and size and composition of the adjacent ice melange. The authors describe a semi-automated routine for expediting the digitization process and illustrate the methods for Helheim Glacier, East Greenland, using 2008 data. Ice velocities of the glacier terminus and ice melange are derived with feature-tracking software applied to radar imagery, which is successfully tracked year-round. Object-based image analysis (OBIA) is used to inventory icebergs and sea ice within the ice melange. The authors find that the model successfully identifies the calving rate and ice melange response trends associated with seasonal increases in terminus retreat and advance and shows seasonal trends of ice melange potentially providing seasonal backstress on the glacier terminus.

Application of satellite remote sensing techniques to quantify terminus and ice mélange behavior at helheim glacier, East Greenland

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD developed a cloud validation dataset from 96 unique Landsat 8 images called the L8 Biome dataset. These images were selected from various locations around the world, and are evenly divided between eight unique biomes and three different cloud cover categories. The images are curated by biome and cloud cover to reduce bias in any one region or cloud cover density. While these validation images were subjectively designed by a single analyst, they provide useful information for quantifying the accuracy of clouds flagged by various cloud masking algorithms. Each mask is provided in ENVI binary format, and includes all bands from the original Landsat Level-1 data product (GeoTIFF), and its associated Level-1 metadata (MTL.txt file).

L8 Biome Cloud Validation Masks

Ice mélange, a conglomeration of icebergs and sea ice, persists in front of some marine-terminating glaciers. Depending upon local fjord geometry and other environmental conditions, an ice mélange can sometimes compact and jam. Here, the impact of the ice mélange on iceberg calving is assessed at a fast-moving glacier with a unique flow regime – Helheim Glacier, southeast Greenland (HG). Satellite remote sensing is used to quantify the ice mélange and the glacier terminus position, and additional ancillary data – wind speed, moorings, sea surface temperature (SST) and bed topography – are used to assess potential controls on iceberg calving. Iceberg jams were measured on a 2 to 35-day interval, but often did not correlate with the rate of calving. Isolated calving events were more likely during a jam, but most jams were in winter, when calving is most infrequent. At HG, SST and seasonality are the stronger drivers of iceberg calving.

Characterization of Ice Mélange and its Implications to Terminus Stability at Helheim Glacier, Southeast Greenland

/pdf/the-future-of-landsat-data-products-analysis-ready-data-and-x3jglojkzp.pdf

Steve Foga

Papers

Cloud detection algorithm comparison and validation for operational Landsat data products

Application of satellite remote sensing techniques to quantify terminus and ice mélange behavior at helheim glacier, East Greenland

L8 Biome Cloud Validation Masks

Characterization of Ice Mélange and its Implications to Terminus Stability at Helheim Glacier, Southeast Greenland

The future of landsat data products: analysis-ready data and essential climate variables