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Using Google Earth Imagery to Target Assessments of Ephemeral Gully Erosion
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Soil Erosion Research Under a Changing Climate, January 8-13, 2023, Aguadilla, Puerto Rico, USA .(doi:10.13031/soil.23080)Authors: David A Reece, John A Lory, Timothy L Haithcoat, Brian K Gelder, Richard M Cruse
Keywords: Aerial imagery, Conservation compliance, Ephemeral gully, Remote sensing, Soil erosion
Abstract
Sustaining civilizations requires preventing losses of agricultural topsoil through processes such as water and wind erosion. It is estimated that ephemeral gully erosion, a type of water erosion, contributes 40% of the total water-erosion soil loss from row-crop fields. Identification and tracking of gullies requires monitoring fields over time; Google Earth provides high-quality imagery that can potentially meet both the temporal and spatial criteria for ephemeral gully monitoring. Our primary objective was to determine the probability that an ephemeral gully erosion feature could be reliably identified as an area of concern based on Google Earth imagery and/or other publicly available remotely sensed imagery. We visited 72 fields in seven Missouri counties between mid-April and mid-June in 2018 (n=26), 2019 (n=21), or 2020 (n=25) to verify the presence of erosion features. Aerial imagery with an estimated ground sampling distance between 2.1 and 2.7 cm pixel-1 was obtained from all locations with an unmanned aerial vehicle (UAV). From this imagery, ephemeral gullies were observed in 24 of the fields and all ephemeral gullies in those fields were then delineated. Additionally, we reviewed all imagery available in Google Earth from 2010 to 2020, delineating ephemeral gully features in the study area based on a definitive and less stringent criterion (Figure 1).
We also obtained 2008 and 2015 imagery from a second public source for the study area. The data derived from these imagery sources were tested, both individually and in combination, in two ways. First, one random feature was chosen and the degree of overlap was measured using Euclidean distance with pixelated lines and different buffers. Combining all imagery sources, using the less stringent method of delineation, and a 15-m buffer resulted in a mean overlap rate of 91%. Second, based on the results of the first analysis, all lines in the field were tested for simple intersection. The less stringent strategy for delineation, coupled with using a 15-m buffer, had a true positive rate of 81% and identified 100% of the ephemeral gullies at 63% of the locations. There were false positives in 38% of the fields with a mean rate across locations of 15%. These results were superior to the definitive approach, as well as using a 3-m buffer. Adding public data from other sources improved the true positive rate while also increasing the false negative rate. At one location, all publicly available image sources failed to identify the single ephemeral gully in the field. This research represents a proof of concept that Google Earth and other publicly available imagery of sufficient quality can be used to target in-field ephemeral gully assessment in row crop fields in the humid regions of the US. Validation work is needed before this approach can be broadly adopted with confidence, given the many uncontrollable factors that can affect the efficacy of this approach.
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