Mapping and monitoring changes in mesic ecosystem dynamics in a topographically complex semi-arid system
Nicholas Kolarik, Boise State University, nicholaskolarik@u.boisestate.edu (Presenter)
Nawaraj Shrestha, Boise State University, nawarajshrestha@boisestate.edu
Jodi Brandt, Boise State University, jodibrandt@boisestate.edu
Relatively small surface water bodies and mesic resource areas are fundamental for biodiversity conservation in semi-arid systems, but are threatened by climate change and development. Newer earth observation datasets like Sentinel-1 and -2 provide opportunities to map these key resources at meaningful spatial scales, but are insufficient for measuring decadal-scale changes. Conversely, the Landsat time series has decades of data, but images are coarse relative to many of the water resource areas that sustain dryland systems, resulting in mixed pixels inadequate for effective monitoring. We developed a workflow that uses 10 m classifications produced from fusion of the Sentinel-1 and -2 time series (2017-present) to estimate sub-pixel proportions of Landsat 7 and 8 time series observations (2004 - present). Using machine learning regression models, we quantified water resource proportions (WRP) of surface water, mesic areas, and upland land covers within each 30 m Landsat pixel. We incorporate ancillary covariates to account for varying topographic conditions, land cover, and climate. Preliminary results indicate that our approach consistently estimates sub-pixel proportions of Landsat pixels more accurately compared to spectral mixture analysis (SMA) (differences in MAE for surface water up to 7.96%, and RMSE up to 17.01% and differences in MAE for mesic vegetation MAE differences up to 4.28% and RMSE 6.75%). We tested the ability of our time series to characterize historical water resource availability at three case study sites with known restoration histories by applying Bayesian change point analyses to identify influences of interventions. Our approach allows us to hindcast observations of Sentinel products and measure water resource dynamics with greater precision over larger temporal scales. We envision these WRP data to be useful for measuring the impacts of conservation interventions, disturbance recovery, or more nuanced land use changes that pre-date the Sentinel time series.
Poster: Poster_Kolarik_2-10_130_35.pdf
Associated Project(s):
Poster Location ID: 2-10
Presentation Type: Poster
Session: Poster Session 2
Session Date: Wed (May 10) 5:15-7:15 PM
CCE Program: BDEC