Citation:

Pilant, D., K. Endres, D. Rosenbaum, AND G. Gundersen. US EPA EnviroAtlas Meter-Scale Urban Land Cover (MULC): 1-m Pixel Land Cover Class Definitions and Guidance. Remote Sensing. MDPI, Basel, Switzerland, 12(12):1909, (2020). https://doi.org/10.3390/rs12121909

Impact/Purpose:

The EnviroAtlas MULC provides spatially detailed foundational data for approximately 100 derived EnviroAtlas Community information layers. Some layers are developed at the native one meter MULC resolution and others by U.S. Census block group. While the EnviroAtlas National component is based on NLCD (National Land Cover Database, www.mrlc.gov) land cover data at 30 m spatial resolution (30x30 m pixel dimensions from the Landsat sensor), the EnviroAtlas Community component is based on MULC data at 900 times the spatial resolution. This permits analysis of common landscape features in the 1-10 m range which are unresolvable using 30 m NLCD pixels. Three such layers derived from MULC data are: Percent impervious area in 50m stream buffer; Value of asthma exacerbation cases avoided due to sulfur dioxide removed ($/yr); Percent of busy roadway bordered by < 25 percent tree buffer. Some of many possible applications of MULC include: Knowing the exact location and size of vegetated and non-vegetated spaces; Identifying highly impervious areas that would most benefit from additional trees and other vegetation to mitigate surface runoff and urban heat island effects; Measuring the width and character of urban riparian and street buffers; Locating potential wildlife corridors, gaps and linkages; Planning park development for maximum benefits. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation.

Description:

This article defines the land cover classes used in Meter-scale Urban Land Cover (MULC), a unique, high resolution (one meter2 per pixel) land cover dataset developed for 30 US communities for the US Environmental Protection Agency EnviroAtlas. MULC data categorize the landscape into these land cover classes: Impervious Surface, Tree, Grass-Herbaceous, Shrub, Soil-Barren, Water, Wetland and Agriculture. MULC data are used to calculate approximately 100 EnviroAtlas metrics that serve as indicators of nature’s benefits (ecosystem goods and services). MULC, a dataset for which development is ongoing, was produced by multiple classification methods using aerial photo and LiDAR datasets. The mean overall fuzzy accuracy across the EnviroAtlas communities was 88% and mean Kappa coefficient was 0.84. MULC is available in EnviroAtlas via web browser, web map service (WMS) in the user’s GIS, and as downloadable data at EPA Environmental Data Gateway. Fact Sheets and metadata for each MULC Community are available through EnviroAtlas. Some MULC applications include mapping green and grey infrastructure, connecting land cover with socioeconomic/demographic variables, street tree planting, urban heat island analysis, mosquito habitat risk mapping and bikeway planning. This article provides practical guidance for using MULC effectively and developing similar high resolution (HR) land cover data.

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