December 2023
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29 Reads
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5 Citations
International Journal of Applied Earth Observation and Geoinformation
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Publications (3)
June 2023
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55 Reads
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34 Citations
June 2022
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2,276 Reads
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584 Citations
Scientific Data
Unlike satellite images, which are typically acquired and processed in near-real-time, global land cover products have historically been produced on an annual basis, often with substantial lag times between image processing and dataset release. We developed a new automated approach for globally consistent, high resolution, near real-time (NRT) land use land cover (LULC) classification leveraging deep learning on 10 m Sentinel-2 imagery. We utilize a highly scalable cloud-based system to apply this approach and provide an open, continuous feed of LULC predictions in parallel with Sentinel-2 acquisitions. This first-of-its-kind NRT product, which we collectively refer to as Dynamic World, accommodates a variety of user needs ranging from extremely up-to-date LULC data to custom global composites representing user-specified date ranges. Furthermore, the continuous nature of the product’s outputs enables refinement, extension, and even redefinition of the LULC classification. In combination, these unique attributes enable unprecedented flexibility for a diverse community of users across a variety of disciplines. Measurement(s)land use • land coverTechnology Type(s)deep learning Measurement(s) land use • land cover Technology Type(s) deep learning
Citations (3)
... Temporal features characterizing the duration and severity of past disturbance events and forest recovery are commonly used to improve the accuracy of forest structure and land use/land cover models [7,19,74,75]. In total, 152 temporal features were computed using the LandTrendr and CCDC algorithms. ...
- Citing Article
December 2023
International Journal of Applied Earth Observation and Geoinformation
... To verify the quality of the processed satellite data, each image was visually inspected and the spectral curves were evaluated at random points. A CloudScore+ mask product was applied with a scale of 0 to 1, denoting occluded and unoccluded observations, respectively (Pasquarella et al., 2023). Histogram-based thresholding was employed, utilising a cutoff of 0.75 to exclude pixels affected by clouds, cloud shadows, and other image distortions, such as excessive pixel saturation. ...
- Citing Conference Paper
June 2023
... To better understand the spatial characteristics of vertical ground motion, we supplemented the EGMS data with a land cover map (LCM). LCMs are valuable for tracking human activity, natural processes, and the impacts of climate change on land cover (Brown et al., 2022). They enable the detection of changes in urban areas, infrastructure, forests, and water bodies, critical information for policymaking, land development, and resource management (Wang et al., 2023). ...
- Citing Article
- Full-text available
June 2022
Scientific Data