Remote Sensing & Automation
P
r
i
n
c
i
p
a
l
C
o
m
p
o
n
e
n
t
A
n
a
l
y
s
i
s
Reducing spectral redundancy in a Landsat 8 scene of the Aurora volcano in Guatemala.
Automation of Landsat 8 Mosaic
Using PCI Catalyst python library to automate the extraction, atmospheric correction, and creation of a mosaic dataset from Level-1 Landsat 8 images.
Mississippi Delta Sediment Discharge
Custom Visual Enhancement
True Colour Composite (RGB - 432)
Custom False Colour Composite (RGB -643) Using Spectral Reflectance Histograms to Isolate Objects of Interest
Automation of Landsat 8 Vegetation Change Detection
Using python to process Level-2 Landsat 8 scenes for a study area over multiple years.
NDVI computed for each year.
Each clipped to the study area.
Ground truth files used to determine NDVI thresholds
Pixels extracted using the threshold.
Difference between each image provided to assess vegetation trends.
Using ArcPy to compute Vegetation Indices and Band Ratios.
Comparing the two methods for analyzing features and phenomena of interest.
Landscape Conductivity Using Circuitscape
Using circuit theory to better understand the movement of species within a landscape.