| Abstract |
Lake trophic state is a key ecosystem property that integrates a lake's physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales. |
| Authors |
Michael F. Meyer  , Simon N. Topp , Tyler V. King , Robert Ladwig , Rachel M. Pilla , Hilary A. Dugan , Jack Eggleston , Stephanie E. Hampton , Dina M. Leech , Isabella A. Oleksy  , Jesse Ross , Matthew Ross , R. Iestyn Woolway , Xiao Yang , Matthew R. Brousil , Kate C. Fickas , J. Padowski , Amina I. Pollard , Jingye Ren , Jacob A. Zwart
|
| Journal Info |
Nature Portfolio | Scientific Data , vol: 11
, iss: 1
|
| Publication Date |
1/16/2024 |
| ISSN |
2052-4463 |
Type |
article |
| Open Access |
green
|
| DOI |
https://doi.org/10.1038/s41597-024-02921-0 |
| Keywords |
Lake Management (Score: 0.516669)
|
