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Showcase Environmental Studies

Applying drone and satellite data to natural vegetation monitoring for agricultural sustainability

Applying drone and satellite data to natural vegetation monitoring for agricultural sustainability

Primary Author: Amanda Stahl

Faculty Sponsor: Alexander Fremier

 

Primary College/Unit: Agricultural, Human and Natural Resource Sciences

Category: Agricultural and Natural Resource Sciences

Campus: Pullman

 

Abstract:

Principal topic

Conserving natural vegetation along streams is an important on-farm strategy to improve water quality. The Voluntary Stewardship Program (VSP, 2011) requires participating agricultural counties in Washington to monitor and report whether ecosystem functions and values are being maintained or enhanced. Emerging remote sensing technologies could provide accurate, real-time, multiscale spatial data to increase monitoring efficiency and effectiveness. We are piloting drones and analyzing Sentinel-2 satellite images to quantify streamside vegetation condition and designing procedures for seamless integration into monitoring programs to improve agricultural sustainability.

 

Methods

We hypothesize that drone-mounted cameras and Sentinel-2 data can accurately document vegetation condition and change for VSP reporting. To test this, we collected images with two quadcopters (3DR Solo and DJI Matrice) at 9 sites across Whitman County. Drone images were compiled into mosaics and 3D surfaces, each referenced for accurate comparison across dates to document seasonality and resolve vegetation classification. We analyzed Sentinel data seasonally and inter-annually to quantify watershed-scale change dynamics using Google Earth Engine and ArcGIS.

 

Results/Implications

Differing patterns of “greenness” clearly distinguished natural vegetation from agricultural land cover in Sentinel images collected July-October 2016-2019. Drone images captured finer details, including vegetation height, volume, and species. Initial findings illustrate that these data sources can detect the changing quantity and quality of natural areas in agricultural areas. In future work we will streamline satellite data analysis in Google Earth Engine and provide guidelines for drone-based monitoring so that counties and Conservation Districts can analyze data in real-time at regional scales.

 

Two phase (l-v) steady state diffusion of water isotopes: A Rayleigh approximation and aTwo phase (l-v) steady state diffusion of water isotopes: A Rayleigh approximation and applicationpplication

Two phase (l-v) steady state diffusion of water isotopes: A Rayleigh approximation and aTwo phase (l-v) steady state diffusion of water isotopes: A Rayleigh approximation and applicationpplication

Primary Author: Anthony Sorensen

Faculty Sponsor: Peter Larson

 

Primary College/Unit: Arts and Sciences

Category: Agricultural and Natural Resource Sciences

Campus: Pullman

 

Abstract:

 

Principal Topic

Hydrothermal (geothermal) systems are defined by water isotope concentrations and other various geochemical characteristics.  The defining characteristics of a hydrothermal system are volumetrically dependent on the subsurface reservoir. If the volume of H2O is the primary control of water isotopes and hydrothermal system characteristics, then the isotopic evolution of a hot spring fluid is best modeled by the two phase (liquid-vapor) steady state diffusion equation. Volumetric ratios of liquid to vapor (l-v) within the reservoir can be used as an indicator of lifetime remaining in the hydrothermal system and thus can be used to make approximations about the next Yellowstone eruption.

Method

The boiling experiment acted as an analog of a steady state hydrothermal system.  The two-phase steady state diffusion equation was used to model the isotopic evolution of the water isotopes. In this experiment, water isotope analyses were continuously measured using a mass spectrometer, and the results were normalized to the fraction of liquid remaining in the system.

Results/Implications

The models developed from this study have unique applications that include: (a) providing percentage estimates of the liquid reservoir remaining in hydrothermal (geothermal) areas (i.e. time remaining before the next eruption, in Yellowstone) and (b) providing a time constraint (i.e. a rate limiting step) in more complex geochemical modeling. Additionally, understanding the volume of H2O remaining in geothermal systems has the potential to save energy companies enormous sums of money by decreasing the amount of drilling needed in geothermal energy development.