diff --git a/datasets/aerosol-difference.data.mdx b/datasets/aerosol-difference.data.mdx
index 3924be981..b4fa8ff79 100644
--- a/datasets/aerosol-difference.data.mdx
+++ b/datasets/aerosol-difference.data.mdx
@@ -35,8 +35,8 @@ layers:
- 0.1
nodata: 0
compare:
- datasetId: houston-urbanization
- layerId: houston-urbanization
+ datasetId: nlcd-annual-conus
+ layerId: nlcd-new-urbanization
mapLabel: |
::js ({dateFns, datetime, compareDatetime}) => {
return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`;
diff --git a/datasets/nlcd-cover.png b/datasets/nlcd-cover.png
new file mode 100644
index 000000000..9e7e75b21
Binary files /dev/null and b/datasets/nlcd-cover.png differ
diff --git a/datasets/nlcd-urbanization.data.mdx b/datasets/nlcd-urbanization.data.mdx
deleted file mode 100644
index 1eb842435..000000000
--- a/datasets/nlcd-urbanization.data.mdx
+++ /dev/null
@@ -1,97 +0,0 @@
----
-id: houston-urbanization
-name: "National Land Cover Database"
-description: "Using the National Land Cover Database (NLCD) to illustrate urbanzation in Houston, TX over a 20-year span."
-media:
- src: ::file ./smog-city.png
- alt: Smog Located In City.
- author:
- name: Galen Crout
- url: https://unsplash.com/photos/y8mIhkw7ZUI
-taxonomy:
- - name: Topics
- values:
- - Land Cover
-infoDescription: |
- ::markdown
- The National Land Cover Database (NLCD) stands as a paramount dataset offering an in-depth overview of the land cover characteristics in the United States. Spearheaded by the Earth Resources Observation and Science (EROS) Center, this database is renewed every two to three years to provide updated and accurate data for the nation.
-layers:
- - id: houston-urbanization
- stacCol: houston-urbanization
- name: Urbanization
- type: raster
- description: "This dataset illustrates the growth in the metropolitan area of Houston, TX from 2000-2019. Note that these values are from 0 to 1."
- initialDatetime: newest
- zoomExtent:
- - 0
- - 20
- sourceParams:
- colormap_name: reds
- nodata: 0
- rescale:
- - 0
- - 1
- legend:
- type: categorical
- stops:
- - color: "#ffffff"
- label: No Data
- - color: "#d73027"
- label: Urbanization
- info:
- source: EROS
- spatialExtent: Houston
- temporalResolution: Annual
- unit: Binary
-
----
-
-
-
-
- ### About
-
- The National Land Cover Database (NLCD) stands as a paramount dataset offering an in-depth overview of the land cover characteristics in the United States. Spearheaded by the Earth Resources Observation and Science (EROS) Center, this database is renewed every two to three years to provide updated and accurate data for the nation.
-
- This is a collective effort between the U.S. Geological Survey (USGS) and the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC, composed of various federal agencies, has a rich legacy spanning over 30 years of generating consistent and pertinent land cover information on a national scale. The NLCD is a testament to their dedication and has emerged as one of the most frequently utilized geospatial datasets within the U.S., catering to an extensive audience ranging from scientists, land managers, city planners, to students.
-
- As of its latest release, the NLCD showcases land cover data and related changes across nine specific epochs, starting from 2001 and culminating in 2021. These datasets are meticulously crafted, ensuring continuity and consistency with the past releases (from 2001-2019). This methodological consistency ensures that the datasets from the different epochs are directly comparable and well-suited for mult-temporal analyses.
-
- ### What NLCD Offers
-
- * Land Cover: This product details the land cover of the Conterminous U.S. at a 30-meter spatial resolution, employing a 16-class legend rooted in the modified Anderson Level II classification system.
-
- * Land Cover Change Index: This visualization tool portrays the transformations that have transpired across all the NLCD epochs, furnishing users with a holistic view of the evolving landscape.
-
- * Urban Imperviousness: A crucial dataset for urbanization studies, it highlights impervious surfaces in urban regions, showcasing them as a percentage of the developed surface at every 30-meter pixel.
-
- * Urban Impervious Descriptor: A more nuanced product that classifies specific urban developments, such as roads, wind tower sites, building locations, and energy production sites. This aids in a more granular analysis of urban features.
-
- ### Access the Data
-
- Visit the [Acess Data](https://www.mrlc.gov/data) page to explore all of the options that NLCD offers.
-
- ### Citing this Dataset
-
- U.S. Geological Survey (USGS) & Multi-Resolution Land Characteristics (MRLC) Consortium. (2021). National Land Cover Database (NLCD) 2021: Conterminous U.S. Land Cover. Earth Resources Observation and Science (EROS) Center. Retrieved from https://www.mrlc.gov/data
-
- ### Publications
-
- * Danielson, Patrick, Postma, Kory, Riegle, J., Dewitz, Jon A., Deep learning artificial intelligence (AI) for improving classification accuracy for the National Land Cover Database (NLCD) [abs.]
-
- * Wickham, J., Stehman, S.V., Sorenson, D.G., Gass, L., Dewitz, Jon A., Thematic accuracy assessment of the NLCD 2016 land cover for the conterminous United States: Remote Sensing of Environment, v. 257, at https://doi.org/10.1016/j.rse.2021.112357
-
- * Rigge, Matthew B., Shi, Hua, Postma, Kory, Projected change in rangeland fractional component cover across the sagebrush biome under climate change through 2085, v. 12, no. 6, at https://doi.org/10.1002/ecs2.3538
-
- * Rigge, Matthew B., Homer, Collin G., Shi, Hua, Meyer, Debbie K., Bunde, Brett, Granneman, Brian, Postma, Kory, Danielson, Patrick, Case, Adam, Xian, George Z., Rangeland fractional components across the western United States from 1985 to 2018: Remote Sensing, v. 13, no. 4, at https://doi.org/10.3390/rs13040813
-
- * Peng, D., Wang, Y. L., Xian, George, Huete, A.R., Huang, W., Shen, M., Wang, F., Yu, L., Liu, L., Xie, Q., Liu, L., Zhang, X., Investigation of land surface phenology detections in shrublands using multiple scale satellite data: Remote Sensing of Environment, v. 252, at https://doi.org/10.1016/j.rse.2020.112133
-
- * Rigge, Matthew B., Shi, Hua, Meyer, Debbie K., Bunde, Brett, Postma, Kory, Trends of fractional rangeland components across a 1985-2020 time-series [poster], v. Measuring & Monitoring Ecosystems, at http://annualmeeting2021.rangelands.org/presentations-posters/
-
- * Jin, Suming, Dewitz, Jon A., Sorenson, D., Shogib, Rakibul , Granneman, Brian J., Case, Adam, Li, Congcong, Zhe, Z., Danielson, Patrick, Costello, C., Gass, L., National Land Cover Database 2019—A comprehensive strategy for creating the 1986-2019 Forest Disturbance Date Product [abs.], v. Proceedings, at https://agu.confex.com/agu/fm21/meetingapp.cgi/Paper/960755
-
-
-
-
-
diff --git a/datasets/nlcd.data.mdx b/datasets/nlcd.data.mdx
new file mode 100644
index 000000000..9d62451ee
--- /dev/null
+++ b/datasets/nlcd.data.mdx
@@ -0,0 +1,288 @@
+---
+id: nlcd-annual-conus
+name: 'National Land Cover Database LULC Classifications'
+description: "National Land Cover Database Land Use - Land Cover classifications for CONUS, 2001-2021 at 30 m resolution."
+
+media:
+ src: ::file ./nlcd-cover.png
+ alt: Boston, MA skyline.
+ author:
+ name: Eric Kilby
+ url: https://openverse.org/image/a9e174e6-d4e1-4377-81e2-6e71bf1a9602?q=skyline
+taxonomy:
+ - name: Topics
+ values:
+ - Agriculture
+ - Biomass
+ - Environmental Justice
+ - Land Cover
+ - name: Source
+ values:
+ - MRLC
+layers:
+ - id: nlcd-annual-conus
+ stacApiEndpoint: https://openveda.cloud/api/stac
+ tileApiEndpoint: https://openveda.cloud/api/raster
+ stacCol: nlcd-annual-conus
+ name: NLCD Land Use - Land Cover Classification
+ type: raster
+ description: "30 meter LULC classification provided by the NLCD."
+ initialDatetime: newest
+ zoomExtent:
+ - 0
+ - 20
+ sourceParams:
+ assets: landcover
+ bidx: [1]
+ nodata: 0
+ resampling: nearest
+ colormap_name: nlcd
+ legend:
+ type: categorical
+ min: "0"
+ max: "255"
+ stops:
+ - color: "#486DA2"
+ label: "Open Water"
+ - color: "#E7EFFC"
+ label: "Perennial Ice/Snow"
+ - color: "#E1CDCE"
+ label: "Developed, Open Space"
+ - color: "#DC9881"
+ label: "Developed, Low Intensity"
+ - color: "#F10100"
+ label: "Developed, Medium Intensity"
+ - color: "#AB0101"
+ label: "Developed High Intensity"
+ - color: "#B3AFA4"
+ label: "Barren Land (Rock/Sand/Clay)"
+ - color: "#6BA966"
+ # label: "Vegetation"
+ label: "Deciduous Forest"
+ - color: "#1D6533"
+ label: "Evergreen Forest"
+ - color: "#BDCC93"
+ label: "Mixed Forest"
+ - color: "#B29C46"
+ label: "Dwarf Scrub"
+ - color: "#D1BB82"
+ label: "Shrub/Scrub"
+ - color: "#EDECCD"
+ label : "Grassland/Herbaceous"
+ - color: "#D0D181"
+ label: "Sedge/Herbaceous"
+ - color: "#A4CC51"
+ label: "Lichens"
+ - color: "#82BA9D"
+ label: "Moss"
+ - color: "#DDD83E"
+ label: "Pasture/Hay"
+ - color: "#AE7229"
+ label: "Cultivated Crops"
+ # label: "Agriculture"
+ - color: "#BBD7ED"
+ label: "Woody Wetlands"
+ - color: "#71A4C1"
+ label: "Emergent Herbaceous Wetlands"
+ compare:
+ datasetId: nlcd-annual-conus
+ layerId: nlcd-annual-conus
+ mapLabel: |
+ ::js ({ dateFns, datetime, compareDatetime }) => {
+ return `${dateFns.format(datetime, 'yyyy')} VS ${dateFns.format(compareDatetime, 'yyyy')}`;
+ }
+ info:
+ source: MRLC
+ spatialExtent: United States
+ temporalResolution: Bi- to Tri-Annual
+ unit: N/A
+
+ - id: nlcd-new-urbanization
+ stacApiEndpoint: https://openveda.cloud/api/stac
+ tileApiEndpoint: https://openveda.cloud/api/raster
+ stacCol: nlcd-new-urbanization
+ name: Urbanization
+ type: raster
+ description: "This is a binary dataset derived from the National Land Cover Database (NLCD) to illustrate new urbanization from 2001-2021, where 0 is no new urbanization and 1 is new urbanization."
+ initialDatetime: newest
+ zoomExtent:
+ - 0
+ - 20
+ sourceParams:
+ colormap_name: reds
+ nodata: 0
+ assets: landcover
+ rescale:
+ - 0
+ - 1
+ legend:
+ type: categorical
+ stops:
+ - color: "#d73027"
+ label: New Urbanization
+ info:
+ source: EROS
+ spatialExtent: CONUS
+ temporalResolution: 20 Year Difference
+ unit: Binary
+
+---
+
+
+ ## Dataset Details
+ - **Temporal Extent:** 2001-2021
+ - **Temporal Resolution:** Inconsistent (every 2-3 years)
+ - **Spatial Extent:** CONUS
+ - **Spatial Resolution:** 30 m
+ - **Data Units:** N/A
+ - **Data Type:** Research
+ - **Data Latency:** N/A
+
+
+
+
+ Comparison of the NLCD land cover classifications over Houston, TX between 2001 and 2021
+
+
+
+
+
+
+
+ ### About
+
+ The National Land Cover Database (NLCD) stands as a paramount dataset offering an in-depth overview of the land cover characteristics in the United States. Spearheaded by the Earth Resources Observation and Science (EROS) Center, this database is renewed every two to three years to provide updated and accurate data for the nation.
+
+ This is a collective effort between the U.S. Geological Survey (USGS) and the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC, composed of various federal agencies, has a rich legacy spanning over 30 years of generating consistent and pertinent land cover information on a national scale. The NLCD is a testament to their dedication and has emerged as one of the most frequently utilized geospatial datasets within the U.S., catering to an extensive audience ranging from scientists, land managers, city planners, to students.
+
+ As of its latest release, the NLCD showcases land cover data and related changes across nine specific epochs, starting from 2001 and culminating in 2021. These datasets are meticulously crafted, ensuring continuity and consistency with the past releases (from 2001-2019). This methodological consistency ensures that the datasets from the different epochs are directly comparable and well-suited for mult-temporal analyses.
+
+
+
+
+
+
+
+
+ Newly urbanized areas per NLCD classifications in the Indianapolis, IN metropolitan area between 2001 and 2021.
+
+
+
+
+
+ ### What NLCD Offers
+
+ * Land Cover: This product details the land cover of the Conterminous U.S. at a 30-meter spatial resolution, employing a 16-class legend rooted in the modified Anderson Level II classification system.
+
+ * Land Cover Change Index: This visualization tool portrays the transformations that have transpired across all the NLCD epochs, furnishing users with a holistic view of the evolving landscape.
+
+ * Urban Imperviousness: A crucial dataset for urbanization studies, it highlights impervious surfaces in urban regions, showcasing them as a percentage of the developed surface at every 30-meter pixel.
+
+ * Urban Impervious Descriptor: A more nuanced product that classifies specific urban developments, such as roads, wind tower sites, building locations, and energy production sites. This aids in a more granular analysis of urban features.
+
+
+
+
+
+
+
+ ### Access the Data
+
+ Visit the [Access Data](https://www.mrlc.gov/data) page to explore all of the options that NLCD offers.
+
+
+
+
+
+
+
+ ### Citing this Dataset
+
+ U.S. Geological Survey (USGS) & Multi-Resolution Land Characteristics (MRLC) Consortium. (2021). National Land Cover Database (NLCD) 2021: Conterminous U.S. Land Cover. Earth Resources Observation and Science (EROS) Center. Retrieved from https://www.mrlc.gov/data
+
+
+
+
+
+
+
+ ## 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
+
+ Homer, C., Dewitz, J., Fry, J., Coan, M., Hossain, N., Larson, C., et al. (2007). Completion of the 2001 National Land Cover Database for the conterminous United States. Photogrammetric Engineering and Remote Sensing, 73(4), 337–341.
+
+ Homer, C., Fry, J. A., & Barnes, C. A. (2012). The national land cover database. US geological survey fact sheet, 3020(4), 1–4.
+
+ Homer, C., Dewitz, J., Yang, L., Jin, S., Danielson, P., Xian, G., et al. (2015). Completion of the 2011 national land cover database for the conterminous United States – Representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81(5), 345–354. https://doi.org/10.14358/PERS.81.5.345
+
+
+
+
+
+
+
+ ### Other Publications
+
+ Danielson, Patrick, Postma, Kory, Riegle, J., Dewitz, Jon A., Deep learning artificial intelligence (AI) for improving classification accuracy for the National Land Cover Database (NLCD) [abs.]
+
+ Jin, Suming, Dewitz, Jon A., Sorenson, D., Shogib, Rakibul , Granneman, Brian J., Case, Adam, Li, Congcong, Zhe, Z., Danielson, Patrick, Costello, C., Gass, L., National Land Cover Database 2019—A comprehensive strategy for creating the 1986-2019 Forest Disturbance Date Product [abs.], v. Proceedings, at https://agu.confex.com/agu/fm21/meetingapp.cgi/Paper/960755
+
+ Rigge, Matthew B., Homer, Collin G., Shi, Hua, Meyer, Debbie K., Bunde, Brett, Granneman, Brian, Postma, Kory, Danielson, Patrick, Case, Adam, Xian, George Z., Rangeland fractional components across the western United States from 1985 to 2018: Remote Sensing, v. 13, no. 4, at https://doi.org/10.3390/rs13040813
+
+ Wickham, J., Stehman, S.V., Sorenson, D.G., Gass, L., Dewitz, Jon A., Thematic accuracy assessment of the NLCD 2016 land cover for the conterminous United States: Remote Sensing of Environment, v. 257, at https://doi.org/10.1016/j.rse.2021.112357
+
+
+
+
+
+
+
+ ## Data Stories Using This Dataset
+
+ **Implications for Heat Stress**
+
+ **Aerosols and Their Impacts on Houston, TX**
+
+ **Wildfires Affect Local Weather, Climate, and Hydrology**
+
+
+
+
+
+
+
+
+ ## 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
diff --git a/stories/camp-fire-burn-scar.stories.mdx b/stories/camp-fire-burn-scar.stories.mdx
index c73e8d82e..3484568a5 100644
--- a/stories/camp-fire-burn-scar.stories.mdx
+++ b/stories/camp-fire-burn-scar.stories.mdx
@@ -103,8 +103,8 @@ taxonomy:
+ />
Figure 3: Aerosol Optical Depth Compared Decadally from 2000-2009 & 2010-2019 vs the Urbanization of the Houston metro from 2000-2019. The left portion of the map shows the subtracted difference in AOD over the last 20 years over the Houston metropolitan area.