1. Devesh Khosla Graduate Student - UA MSGIST September 20th, 2017
Optimizing Management of Invasive Buffelgrass Using Satellite & Climate Data
Devesh Khosla
Graduate Student - UA MSGIST
September 20th, 2017

2. LEARNING OBJECTIVES
To provide a brief introduction on my previous work related to GIS.
To describe the research being conducted as part of my thesis project.
To explain my future trajectory and ideas in GIS.

3. 2011
2017
Defense Research Development Organization (DRDO) SASE Branch in Chandigarh, India
(January 2011 to June 2011)

4. DRDO PROJECT Change detection on the Himalayan region
Improved change vector analysis used as a change detection technique which finds threshold by double window flexible pace search and also finds the change type discrimination.
Slope matching technique to remove shadow due to mountain (topographic correction).
Studied the effect of pan sharpening using Gram Schmidt on improved change vector analysis after applying the proper topographic correction.
Accuracy of land cover change was further compared with MODIS data.

5. 2011
2017
Research/Volunteer for Dr. Cynthia Wallace at the United States Geology Survey (USGS), University of Arizona
(April 2017 to present)

6. THESIS PROJECT
Prediction and treatment of Buffelgrass
The goal is to promote Buffelgrass management in the southern region of the United States, specifically the states of Arizona and California.
Utilizing remote sensing data to detect where the invasive plants are located and when they are photosynthetically active.
Implementing this technique automatically and complementing with mobile App and web-based GIS.

7. INTRODUCTION
Wildfire and Invasive Species in Southwestern Deserts
Nonnative grasses becoming established in deserts:
Red brome (in the Mojave)
Buffelgrass (in the Sonoran)

8. WHY IS THIS IMPORTANT?
Grasses transform desert into flammable grassland: fire-adapted grasses re-establish quickly, pushing out native species like Saguaro cactus.
Spread of grasses not directly a result of climate change, but global warming may allow them to further spread in the desert and extend to higher elevations.
So….we need to predict, monitor, and apply proper treatment to stop the growth of Buffelgrass in Southern part of USA.

9. STUDY AREA

10. With Treatment
Without Treatment

11. Processed AZ data and working on CA data.
METHODOLOGY
Processed AZ data and working on CA data.
Identify temporal patterns of new infestations
Explore options for web-based app to optimize treatment
Case study Ajo

12. SWreGAP Vegetation Map
CLaRe Metrics at SNP-E
SWreGAP Vegetation Map
Average correlation values across a suite of CLaRe values for native vegetation in Saguaro National Park
Greenness (NDVI)
CLaRe = 0
PPT Value (inches)

13. SWreGAP Vegetation Map
CLaRe Metrics at SNP-E
SWreGAP Vegetation Map
Average correlation values across a suite of CLaRe values for native vegetation in Saguaro National Park
CLaRe = 1
Greenness (NDVI)
CLaRe = 0
PPT Value (inches)

14. CLaRe Metrics at SNP-E Sonoran-Paloverde Mixed Cacti Desert Scrub
SWreGAP Vegetation Map
Average correlation values between MODIS NDVI and cumulative lagged precipitation for native vegetation compared to averages for various densities of buffelgrass. Note that small amounts of buffelgrass can dramatically increase the correlation values.

15. NEXT STEPS….
Ajo Study Area focus
Evaluate CLaRe metrics to identify temporal pattern of new infestations, areas prone to invasive spread.
Validate using data available online via phone app developed by Malusa et al.
Design options for data served on web-based app to optimize timing of herbicide treatment.
App can be utilized by agencies and/or organizations (e.g., Department of Transportation) to determine timely treatment.

16. Dr. Cynthia Wallace
Dr. Christopher Lukinbeal
AGIC Education & Training Symposium
U.S. Geological Survey
University of Arizona