Summary & Purpose
The objective of this project was to develop a repeatable workflow in Google Earth Engine to produce high-resolution (10m) land cover maps for the Eastern Upper Peninsula of Michigan. We used multi-temporal Sentinel optical and radar data from 2019 in Google Earth Engine, and Random Forest classification algorithms, to make two classifications: a) an “upland-lowland” forest map, consisting of upland forest, lowland forest, and water; and b) a “forest type” map” consisting of coniferous forest, deciduous forest, non-forest, and water. To train and validate the classifications, we used a field-based reference dataset of over 500 field data points collected by Sault Tribe during July – September 2019. Overall classification accuracy for the upland-lowland classification was 74.9%. Overall classification accuracy for the forest type classification was 86.0%. Close inspection of local scale patterns in the maps identified considerable areas of localized errors, and therefore these products are considered a “beta” (i.e. preliminary) version best utilized as proof of concept of the analytical approach. This error could be minimized by using a larger reference dataset (i.e. more field data collection). In particular, focusing on smaller spatial areas, such as a specific county or forest boundary, coupled with more dense reference data collection within that specific area, would likely result in very accurate maps of forest type at 10-m resolution that could be used to link species data (e.g. marten, snowshoe hare) with land cover patterns. The methodology and Google Earth Engine code that we have developed can be used for future work. In this archive, we provide the map products, and the field reference dataset, and GEE code and R scripts can be provided upon request.
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.tif, .png, .pdf
The maps in .tif format can be used in a GIS program. The maps in .jpg format can be opened in any image viewer program.
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Spaete, Lucas; Brandt, Jodi; Clark, Eric; and Fagan, Danielle, "Land Cover Maps of the Eastern Upper Peninsula, Michigan, Using Radar-Optical Fusion of Multi-Temporal Imagery in Google Earth Engine" (2020). Human Environment Systems Datasets. 1.