Detecting Land Cover Land Use Change in Las Vegas Sarah Belcher & Grant Cooper December 8, 2014

Introduction Goals: 1.To quantify land use/land cover change for Las Vegas over time 2.Collect necessary data 3.Determine class scheme 4.Use skills obtained through lab exercises 5.Show Results 6.Validation 7.Report

Rapid Population Growth 1950: 48, : 741, : 1,375, : 1,685, : 2,027,868 (Est.) Desert Climate Alluvial Soils Sparse Vegetation Hot, dry summers content /uploads/2014/02/LasVegasStrip.jpg Satellite imagery courtesy of Digital Globe Inc. Study Area

Southern Nevada receives 90% of its water supply from the Colorado River Area has been experiencing drought for the last 14 years Per capita water use has dropped 40% in the past two decades in Las Vegas jpg?__SQUARESPACE_CACHEVERSION=

Study Area Previous studies have been conducted on ISA (impervious surface areas) ISA indicator of non-point source pollution or polluted runoff Changes in ISA useful indicators of spatial extent, intensity and potentially types of LULC change Source: Xian, G. Analysis of Urban Land Use Change in the Las Vegas Metropolitan Area Using Multitemporal Satellite Imagery. ASPRS 2006 Annual Conference.

Methods 30m Landsat (5, 7 & 8) imagery Utilized bands R, G, B, and near IR All collected in the month of July All images stacked in ERDAS Imagine Landsat imagery 7/4/1999

Methods 2010 Census tract for Clark County Arc Map 10.2 used to select tracts for study area and dissolve boundaries Projection changed to WGS 1984 UTM completed in Arc Map 10.2

Methods Each Landsat image subset/clipped based on census tract polygon (AOI) Improve speed for processing and accuracy of supervised classification

Methods Classes: Structures Impervious Undeveloped Vegetation Water Housing 20 training sites per class

Supervised Classification, Maximum Likelihood 6 Classes with housing added

Methods

Thematic Change

Results Fda Total VegetationUndevelopedUrbanWater Vegetation1, , Undeveloped , , , Urban1, , , , Water Total3, , , , *All areas in hectares

Results Undeveloped areas decreased 45% Urban areas increased 41% Water decreased 26% Vegetation increased 69%

Accuracy Assessment Classified Data Reference Data Total VegetationUrbanUndevelopedWater Vegetation70007 Urban Undeveloped Water00055 Total

Limitations Reference data for classification should have should have had imagery for all four years of interest Accuracy assessment should have used an independent source, not the World View 1 imagery Mixed pixels on edges and with roofs/buildings and bare soil

If we Knew What we Know Now… Data can be very challenging to track down Scope creep With more time, we could have: Obtained high resolution imagery for all four years of interest, possibly more to not used Landsat all together Done more detailed analysis – added NDVI’s to look at percentage of vegetation over time