From 047bd3990f3e745e775334934c89db756d63c08a Mon Sep 17 00:00:00 2001
From: WeathermanTrent <109642752+WeathermanTrent@users.noreply.github.com>
Date: Mon, 25 Nov 2024 15:12:16 -0600
Subject: [PATCH] update documents
---
datasets/marsh-ida.data.mdx | 4 +-
datasets/planet-indices.data.mdx | 121 +++++++++++++++++++++++++++++++
2 files changed, 123 insertions(+), 2 deletions(-)
create mode 100644 datasets/planet-indices.data.mdx
diff --git a/datasets/marsh-ida.data.mdx b/datasets/marsh-ida.data.mdx
index 60331f9e5..2b49ef2da 100644
--- a/datasets/marsh-ida.data.mdx
+++ b/datasets/marsh-ida.data.mdx
@@ -70,10 +70,10 @@ layers:
legend:
type: categorical
stops:
- - color: "#0000FF"
- label: Gain of Marsh
- color: "#FF0000"
label: Loss of Marsh
+ - color: "#0000FF"
+ label: Gain of Marsh
---
diff --git a/datasets/planet-indices.data.mdx b/datasets/planet-indices.data.mdx
new file mode 100644
index 000000000..67ee805d3
--- /dev/null
+++ b/datasets/planet-indices.data.mdx
@@ -0,0 +1,121 @@
+---
+id: planet-indices
+name: "Salt Marsh Distribution from UNEP-WCMC (WILL ADD MORE INFO)"
+description: "ADD INFO"
+media:
+ src: ::file ../stories/ian_goes_cover.jpg
+ alt: Hurricane Ian as seen from space as it makes landfall with the state of Florida. NASA Earth Observatory image.
+ author:
+ name: Joshua Stevens, using GOES 16 imagery courtesy of NOAA and the National Environmental Satellite, Data, and Information Service (NESDIS)
+ url: https://visibleearth.nasa.gov/images/150408/hurricane-ian-reaches-florida
+taxonomy:
+ - name: Topics
+ values:
+ - Natural Disasters
+ - Tropical
+ - name: Source
+ values:
+ - Community Contributed
+layers:
+ - id: marsh-ida
+ stacCol: marsh-ida
+ name: Salt Marsh
+ type: raster
+ description: 'Salt Marsh Classification Pre-Ida (Southern Louisiana)'
+ initialDatetime: newest
+ zoomExtent:
+ - 0
+ - 20
+ sourceParams:
+ colormap_name: reds
+ nodata: 0
+ rescale:
+ - 0
+ - 1
+ legend:
+ type: categorical
+ stops:
+ - color: "#ffffff"
+ label: Non-Salt Marsh
+ - color: "#d73027"
+ label: Salt Marsh
+ compare:
+ datasetId: marsh-ida
+ layerId: marsh-ida
+ mapLabel: |
+ ::js ({ dateFns, datetime, compareDatetime }) => {
+ return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`;
+ }
+ info:
+ source: UNEP-WCMC
+ spatialExtent: Southern Louisiana
+ temporalResolution: Monthly
+ unit: Binary
+
+ - id: marsh-difference
+ stacCol: marsh-difference
+ name: Salt Marsh Difference
+ type: raster
+ description: "Difference in Salt Marshes Pre- and Post-Ida"
+ initialDatetime: newest
+ zoomExtent:
+ - 0
+ - 20
+ sourceParams:
+ colormap_name: bwr
+ nodata: 0
+ rescale:
+ - -1
+ - 1
+ legend:
+ type: categorical
+ stops:
+ - color: "#FF0000"
+ label: Loss of Marsh
+ - color: "#0000FF"
+ label: Gain of Marsh
+---
+
+
+
+
+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.
+
+- **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
+
+
+**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.
+
+
+
+
+
+## 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.
+
+## 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].
+
+
+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].
+
+### 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.
+
+ ## 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)
+
+## License
+[Creative Commons Attribution 1.0 International](https://creativecommons.org/publicdomain/zero/1.0/legalcode) (CC BY 1.0)
+
+
+
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