Work Description

Date: 21 June, 2023

Dataset Title: GIS Layers: Rain Garden Development Analaysis Dataset

Dataset Creators: A. Lojko, Y. Zhang, M. Whitcomb, E. Yang, N. Dacic, J.Holmes

Dataset Contact: Alexander Lojko alojko@umich.edu

For a detailed description of the methodology and research performed, please refer to our report: "Washtenaw County Green Infrastructure Development Analysis" (https://dx.doi.org/10.7302/7058)

Files contained here:
There is one file (.lpkx) that can be opened with ArcGIS:

- 'GIS_Layers_Washtenaw_RainGarden_Priority', contains all the layers related to the social inequality, water quality and wildlife connectivity analysis.
The file is split into 4 layers:

1. Wildlife Corridors: This layer contains information on where new green infrastructure can be constructed in order to best improve connectivity between forested areas for wildlife. The main feature is the 'Wildlife Corridors'. This shows corridors (i.e., vector based lines) to best connect isolated forested areas. The different colors of the corridors indicate the priority value that is assigned to them. Corridors that connect small isolated forested areas that are nearby each other are assigned the highest priority values.

2. Social Inequality: This layer is a priority map based on the sum of the priority values assigned in 'Priority_ONLY_Household_Poverty', 'Priority_Only_Urban_Heat_Island' and 'Priority_Only_Green_Infrastructure_Distance'. This metric combines social inequality criteria such that areas with the strongest heat island effect, highest poverty and furthest distance from existing green infrastructure are assigned the highest values.

3. Creeksheds and Future Runoff: This layer contains climate change projections on the future change of runoff as well as information on Creekshed pollutants.

4. Runoff / Water Quality: This layer provides a priority map of where to construct new rain gardens based on areas that are most at risk of flooding (high impermeability) and poorest water quality areas are assigned the highest priority values.

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Some Details on the Data & Methodology:

Methodology:

The data is analyzed using Arc GIS pro.

Different data products are used, including Priority Maps, Vector-Based Wildlife Connectivity Map and Climate Change Projection Maps.

We give a brief description of the methodology used to create these maps:

- Priority Maps: For the Social Inequality Priority Map, three criteria are used to determine a metric for social inequality: % of Population (with someone under 18 in their household) that lives below the poverty line, distance to existing green infrastructure and the intense of the urban heat island effect.
Data related to these metrics are fed into Arc GIS and rasterized (i.e., Converted into Pixels, in this case, 1 x 1 km pixels). We then apply a value to these three metrics at each pixel, with higher values indicating higher priority.
The three metrics are summed up to create a final priority map called 'Priority_Final_Social_Inequality' in the Social inequality layer.

This methodology is also used for 'Runoff / Water Quality'. The difference being is that the surface impermeability and the quality of water bodies are used as metrics to convert into priority values.

- Vector-Based Wildlife Connectivity: Forested areas in Washtenaw County are identified and the Cost Connectivity Analysis function in ArcGIS is used to identify paths by which different isolated forested areas could be connected. The highest priority connections ('wildlife corridors') are the ones that connect small isolated forested areas together over small distances. In contrast, already existing large forested areas that require long paths to connect to nearby forested areas are assigned the lowest priority.

- Climate Change Projection Maps: The data provided is already in a raster format for analysis. We use 'TerraClimate' data to create climate change projection maps of water-runoff in ArcGIS using the equation: Runoff = (Precipitation intensity) x (Area) x (Runoff coefficient)

Data:

References to the datasets used in the creation of our data product:

Please refer to our document for a link to the datasets: https://dx.doi.org/10.7302/7058

The following lists the data used for the GIS analysis:
● County boundary
○ Southeast Michigan Council of Governments (SEMCOG) County Boundaries
Map
■ This dataset includes polygons for seven counties in Southeast Michigan,
for use in GIS analysis.

● Land use
○ SEMCOG Land Use Map
■ The dataset includes the land-use types within seven counties of
Southeast Michigan. For our use, the land use types have been clipped to
be within the boundaries of Washtenaw county.

● Poverty status
○ American Community Survey (ACS) Poverty Status Map
■ This dataset includes estimated poverty status data from the most recent
ACS five year data. Poverty status is quantified by the percentage of the
population whose income in the last 12 months falls below the Federal
poverty line.

● Road Networks
○ SEMCOG Roads Map
■ This dataset includes roads across Southeast Michigan.

● Precipitation data
○ Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Ver. 3
■ Daymet provides 1 km.2 gridded weather data across North America. We
used 2011-2020 annual accumulated precipitation data to calculate the
10-year average daily precipitation intensity.
■ See: Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R.
Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface
Weather Data on a 1-km. Grid for North America, Version 3. ORNL
DAAC, Oak Ridge, Tennessee, USA.
https://doi.org/10.3334/ORNLDAAC/1328

○ TerraClimate
■ This dataset provides 4 km.2 gridded monthly climatologies for 1981-
2010, 2°C warming (future projection), and 4°C warming (future
projection)
■ See: Abatzoglou, J., Dobrowski, S., Parks, S. et al. TerraClimate, a highresolution global dataset of monthly climate and climatic water balance
from 1958–2015. Sci Data 5, 170191 (2018).
https://doi.org/10.1038/sdata.2017.191

● Hydrologic Units
○ USGS National Hydrogeography
■ This dataset provides hydrologic units at multiple levels. We used the
Michigan 12-digit Hydrologic Unit data.

● Tree Cover
○ USA NLCD Tree Canopy Cover
■ This dataset includes a percentage of tree cover across the USA.
○ US Forest Service (USFS) 2016 Cartographic Tree Canopy Cover
■ This dataset provides a 30 x 30 m. resolution map of tree cover
percentages across the United States. We used the “Cartographic”
dataset to best accommodate our visualizations.

● Urban Heat Island Effect
○ Urban Heat Island Severity Map
■ The dataset includes 30 x 30 m. pixels of the severity of the urban heat
island effect across US cities for the summers of 2018 - 2019.

● Parks Layer
○ Map of Parks in South-East Michigan
■ Much like the land use dataset, the layer provides the locations of parks
within South-East Michigan. This layer comes with additional detailed
information such as whether parks are privately owned or accessible to
the public.

● Forest Canopy Height
○ Global Land Analysis & Discovery (GLAD) Global Forest Canopy Height, 2019
■ This dataset provides a 30 x 30 meter resolution global map of forest
canopy heights

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Related publication(s):
Lojko, A., Yang, E., Holmes, J., Whitcomb, M., Dacic, N., Zhang, Y., Bassis, J., and Rood, R., 2023. Washtenaw County Green Infrastructure Development Analysis. [https://dx.doi.org/10.7302/7058]
Dacic, N., Lojko, A., Zhang, Y., Yang, E., Whitcomb, M., Bassis, J., and Rood., R.B., 2023 'Modernizing the Climate Science Curriculum: Engaging in Local Government Collaboration Projects', In Preperation for the Bulletin of American Meteorological Society

Use and Access:
This data set is made available under 'Attribution 4.0 International (CC BY 4.0)'

To Cite Data: Lojko, A., Zhang, Y., Whitcomb, M., Yang, E., Dacic, N., & Holmes, J. (2023). GIS Layers: Rain Garden Development Analaysis Dataset. University of Michigan - Deep Blue [doi pending]