diff --git a/datasets/planet-indices.data.mdx b/datasets/planet-indices.data.mdx index 67ee805d3..a548d2289 100644 --- a/datasets/planet-indices.data.mdx +++ b/datasets/planet-indices.data.mdx @@ -17,105 +17,267 @@ taxonomy: values: - Community Contributed layers: - - id: marsh-ida - stacCol: marsh-ida - name: Salt Marsh + - id: ida-ndvi + stacCol: ida-ndvi + name: NDVI type: raster - description: 'Salt Marsh Classification Pre-Ida (Southern Louisiana)' + description: 'NDVI Pre-Ian (Southern Louisiana)' initialDatetime: newest zoomExtent: - 0 - 20 sourceParams: - colormap_name: reds - nodata: 0 + colormap_name: rdylgn rescale: - 0 - 1 legend: - type: categorical + type: gradient + min: "-1" + max: "1" stops: - - color: "#ffffff" - label: Non-Salt Marsh - - color: "#d73027" - label: Salt Marsh + - "#a50026" + - "#f46d43" + - "#fee08b" + - "#d9ef8b" + - "#66bd63" + - "#006837" compare: - datasetId: marsh-ida - layerId: marsh-ida + datasetId: planet-indices + layerId: ida-ndvi mapLabel: | ::js ({ dateFns, datetime, compareDatetime }) => { return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; } info: - source: UNEP-WCMC + source: PlanetScope spatialExtent: Southern Louisiana temporalResolution: Monthly unit: Binary - - id: marsh-difference - stacCol: marsh-difference - name: Salt Marsh Difference + - id: ida-ndwi + stacCol: ida-ndwi + name: NDWI type: raster - description: "Difference in Salt Marshes Pre- and Post-Ida" + description: 'NDWI Pre-Ian (Southern Louisiana)' initialDatetime: newest zoomExtent: - 0 - 20 sourceParams: - colormap_name: bwr - nodata: 0 + colormap_name: rdylbu + rescale: + - 0 + - 1 + legend: + type: gradient + min: "0" + max: "1" + stops: + - "#a50026" + - "#f46d43" + - "#fee08b" + - "#d9ef8b" + - "#66bd63" + - "#006837" + compare: + datasetId: planet-indices + layerId: ida-ndwi + mapLabel: | + ::js ({ dateFns, datetime, compareDatetime }) => { + return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`; + } + info: + source: PlanetScope + spatialExtent: Southern Louisiana + temporalResolution: Monthly + unit: Binary + + - id: ida-ndwi-difference + stacCol: ida-ndwi-difference + name: NDWI Difference + type: raster + description: 'NDWI Difference Pre-Ian (Southern Louisiana)' + initialDatetime: newest + zoomExtent: + - 0 + - 20 + sourceParams: + colormap_name: rdbu rescale: - -1 - 1 legend: - type: categorical + type: gradient + min: "-1" + max: "1" stops: - - color: "#FF0000" - label: Loss of Marsh - - color: "#0000FF" - label: Gain of Marsh + - "#67001f" + - "#d6604d" + - "#fddbc7" + - "#d1e5f0" + - "#4393c3" + - "#053061" + info: + source: PlanetScope + spatialExtent: Southern Louisiana + temporalResolution: Monthly + unit: Binary + + - id: ida-ndvi-difference + stacCol: ida-ndvi-difference + name: NDVI Difference + type: raster + description: 'NDVI Difference Pre-Ian (Southern Louisiana)' + initialDatetime: newest + zoomExtent: + - 0 + - 20 + sourceParams: + colormap_name: rdbu + rescale: + - -1 + - 1 + legend: + type: gradient + min: "-1" + max: "1" + stops: + - "#67001f" + - "#d6604d" + - "#fddbc7" + - "#d1e5f0" + - "#4393c3" + - "#053061" + info: + source: PlanetScope + spatialExtent: Southern Louisiana + temporalResolution: Monthly + unit: Binary --- - - -Harmonized Landsat Sentinel-2 (HLS) project from NASA is designed to integrate and harmonize data from multiple satellite sources, specifically the Operation Land Imager (OLI) on Landsat-8/9 and the Mult-Spectral Instrument (MSI) on Sentinel-2A/B satellites. This project aims to create a seamless surface reflectance record that is essential for various Earth Observation and monitoring tasks. + + + ## Dataset Details + - **Temporal Extent:** August 23 - September 9, 2021 + - **Temporal Resolution:** Inconsistent + - **Spatial Extent:** Southern Louisiana + - **Spatial Resolution:** 3 meters + - **Data Units:** N/A + - **Data Type:** Research + - **Data Latency:** N/A + +
+ + + Planet satellite imagery classification of salt marshes pre- and post-Ida for southern Louisiana. + +
+ -- **Temporal Extent:** Landsat-9 2021-10-31; Sentinel-2B 2017-07-06 -- **Temporal Resolution:** ~3 days -- **Spatial Extent:** Global with the exception of Antarctica -- **Spatial Resolution:** 30 m x 30 m -- **Data Units:** Surface Reflectance -- **Data Type:** Research -- **Data Latency:** 2 to 3 days + + + ### About -**Scientific Details:** -HLS project incorporates several advanced scientific methodologies and technologies to harmonize data from the Landsat and Sentinel-2 satellites such as atmospheric correction, geographic co-registration and common gridding, bidirectional reflectance distribution normalization, and cloud-shadow masking. To calculate the Normalized Difference Vegetation Index (NDVI) from the HLS-2 Dataset, we utilize the red and near-infrared bands to assess vegetation health by applyin the formula NDVI = NIR - Red / NIR + Red, where 'NIR' refers to the near-infrared surface reflectance, and 'Red' denotes the red light surface reflectance, both harmonized from the Landsat and Sentinel satellites. - + Planet Labs’ SmallSat imagery, captured by the PlanetScope Dove satellite constellation, is a highly valuable commercial satellite remote sensing product, frequently leveraged for rapid damage assessment and environmental monitoring. Known for its frequent overpasses, with revisit times on the order of a couple of days, and an impressive spatial resolution of 3 meters, this imagery offers exceptional capabilities for monitoring changes in landscapes and infrastructure. The PlanetScope constellation has near-global coverage daily across the visible and near-infrared channels, providing extensive data for timely and precise analysis of up to 140-150 million square kilometers. + + - -## Source Data Product Citation -Claverie, M., Ju, J., Masek, J. G., Dungan, J. L., Vermote, E. F., Roger, J.-C., Skakun, S. V., & Justice, C. (2018). The Harmonized Landsat and Sentinel-2 surface reflectance data set. Remote Sensing of Environment, 219, 145-161. -## Disclaimer -All data provided in VEDA has been transformed from the original format (TIFF) into Cloud Optimized GeoTIFF ([COG](https://www.cogeo.org/)). Careful quality checks are used to ensure data transformation has been performed correctly. + + + + ### What PlanetScope Data Offers -## Key Publications -Su Ye, John Rogan, Zhe Zhu, J. Ronald Eastman, A near-real-time approach for monitoring forest disturbance using Landsat time series: stochastic continuous change detection, Remote Sensing of Environment, Volume 252, 2021,112167, ISSN 0034-4257, (https://doi.org/10.1016/j.rse.2020.112167)[https://doi.org/10.1016/j.rse.2020.112167]. + * High-Resolution Imagery: With a 3-meter spatial resolution, the PlanetScope Dove satellite imagery provides detailed views of landscapes, enabling precise assessments of building and vegetation damage. + + * Frequent Revisit Times: The satellite constellation’s ability to capture imagery on the order of every couple of days makes it highly effective for monitoring rapid changes, such as those caused by natural disasters. + + * Extensive Coverage: Collecting up to 2 million square kilometers of imagery daily, the Dove constellation ensures broad coverage across visible and near-infrared channels. + * Building and Vegetation Damage Assessment: The high-resolution and frequent imagery facilitate quick identification and analysis of damage to infrastructure and vegetation, aiding in damage determination and response efforts. -Su Ye, Zhe Zhu, Guofeng Cao, Object-based continuous monitoring of land disturbances from dense Landsat time series, Remote Sensing of Environment, Volume 287, 2023, 113462, ISSN 0034-4257, (https://doi.org/10.1016/j.rse.2023.113462)[https://doi.org/10.1016/j.rse.2023.113462]. + + + + + + + ### Access the Data -### Other Relevant Publications -Ye, S., Zhu, Z., & Suh, J. W. (2024). Leveraging past information and machine learning to accelerate land disturbance monitoring. Remote Sensing of Environment, 305, 114071. + Visit Planet's [home page](https://www.planet.com) to explore options for data access. This data was made available through the NASA [Commercial Satellite Data Acquisition (CSDA) Program](https://earthdata.nasa.gov/about/csda/vendor-planet). You can access the CDSA data explorer [**HERE**](https://csdap.earthdata.nasa.gov). + + + + + + - ## Acknowledgment -This work has been supported by the USGS-NASA Landsat Science Team (LST) Program for Toward Near Real-time Monitoring and Characterization of Land Surface Change for the Conterminous US (140G0119C0008) + ### Citing this Dataset + + Image © 2024 Planet Labs PBC. Planet Application Program Interface: In Space for Life on Earth. https://api.planet.com. + + + -## License -[Creative Commons Attribution 1.0 International](https://creativecommons.org/publicdomain/zero/1.0/legalcode) (CC BY 1.0) + + + + ## Disclaimer + + All data provided in VEDA has been transformed from the original format (TIFF) into Cloud Optimized GeoTIFFs ([COG](https://www.cogeo.org)). Careful quality checks are used to ensure data transformation has been performed correctly. + + + + + + + + ### Key Publications + + Marshall, W and C. Boshuizen, 2013: Planet Labs' Remote Sensing Satellite System. Proc. of the 2013 Small Satellite Conference, Utah State University. https://digitalcommons.usu.edu/smallsat/2013/all2013/7/ + + + + + + + + ### Other Publications + + Molthan, A., L. A. Schultz, K. M. McGrath, J. E. Burks, J. P. Camp, K. Angle, J. R. Bell, and G. J. Jedlovec, 2020: Earth Remote Sensing in NWS Severe Weather Damage Assessments. *Bull. Amer. Meteor. Soc.*, **101**, 221–226. https://www.jstor.org/stable/27028125 + + + + + + + + ## Data Stories Using This Dataset + + **How Hurricane Ida’s Impact on Wetlands Endangers Inland Communities** + + + + + + + + ## License + + [Creative Commons Attribution 1.0 International](https://creativecommons.org/publicdomain/zero/1.0/legalcode) (CC BY 1.0) - + \ No newline at end of file