Using the National Land Cover Database and LIDAR to reveal urban abandonment in DetroitEmily Thompson, Kirsten de Beurs

Department of Geography and Environmental Sustainability, College of Atmospheric & Geographic Sciences, University of Oklahomaesthompson@ou.edu, kdebeurs@ou.edu

This research was completed as part of a senior capstone research project for the Department of Geography and Environmental Sustainability and the University of Oklahoma.

According to the 2010 census, over 80% of the population of the United States resides in urban areas, prompting continuous urban population growth. From 2000-2010, the U.S. urban population grew by 12.1%, however this change is not uniform in all cities. Several cities, primarily in the “rust belt” and old industrial regions of the country, have been experiencing drastic population losses since reaching their peak populations in the middle of the 20th century. Postwar industrial relocation mixed with demographic tensions and economic downturn have been the major driving forces of drastic population loss. These cities, referred to as shrinking cities, have experience population declines of over 50% since their peak populations and a handful have seen losses of over 15% from 2000-2010. One of the most notable examples of drastic population loss is the city of Detroit, MI. Detroit has experienced a population decline of 61.4% from 1950-2010 and a 24% loss from 2000-2010. In the wake of significant population decline, Detroit has experienced abandonment of homes and other structures, which are left to fall apart and to be demolished by the city. This study investigates the relationship between percent population change and land cover changes experienced by the Detroit Metropolitan region from 2001-2011. In using the National Land Cover Dataset products from 2001 and 2011, we observe that the products are not designed to detect urban areas that have decreased in urban intensity and therefore do not provide an accurate assessment of the land cover. We use LIDAR data to show more accurate urban land cover. By calculating the elevation of a small region, we show that LIDAR has the ability to show the presence of structures.

The study yields no significant relationship between percent population change and the change in urban land cover. There is no relationship between percent population change and the

change in urban land cover in areas where there was a decline in population.

We detect inaccuracies in the classification of urban land cover by the NLCD. This poses a significant problem to the NLCD products as urban areas

are not constant in urban land cover growth. Cities have the ability to change land cover from urban to another

class. Future research should be geared toward developing a method of

classifying urban land cover that is able to detect areas that have decreased in urban intensity.

D. National Land Cover Dataset (NLCD)

E. Weather

A. Overview

B. Study Area

G. Conclusions

E. Light Detection And Ranging (LIDAR)

The total study region encompasses approximately 8,500 km2, while the smaller study region includes approximately 15 km2. The total study region was selected because it encompassed the entire

Detroit Metropolitan region. The small study area was selected for its mixture of urban land cover –

commercial, high and low density residential, and open area. The outward movement of people left large amounts of vacant homes to be

handled by the city. From 1970-1990, it was estimated that as many as 117,000

vacant/abandoned homes were demolished. By 2000, the number of vacant structures accounted for 10% of the total

structures. By 2009, there were as many as 80,000 vacant structures.

Figure 1: The large study region is shown in southeast Michigan. This region encompasses the entire Detroit Metropolitan region.

C. Population Detroit population peaked in 1950 at 1.86 million and has

been declining ever since. Postwar industrial relocation, economic downturn, racial

tensions, government corruption, increasing crime rates and have been contributing factors to the drastic population loss.

Following the 2008 economic crisis, Detroit experienced unemployment rates as high as 29%.

From 2000-2010, the population of Detroit shrank from 951 thousand to 714 thousand.

We compare population data from 2000 and 2010. In the small study area, the population decreased in

each tract from.

The National Land Cover Dataset Land Cover product is divided into 20 different classes.

This study focuses on the four urban classes. Developed, Open Space; Developed, Low

Intensity; Developed, Medium Intensity; and Developed, High Intensity.

Figure 3: Population of the total study area in 2000 versus 2010.

Figure 5: The total study area including census tracts as displayed by the 2001 NLCD Land Cover product.

Figure 10: LIDAR based elevation (m) of the small study region. This includes an inset of an abandoned are with a hillshade to show land cover detail.

Figure 2: The small study (highlighted in purple) region is comprised of five census tracts in the center of Detroit.

Figure 6: The total study area including census tracts as displayed by the 2001 NLCD Land Cover product.

Figure 7: The total study area including census tracts as displayed by the 2011 NLCD Land Cover product.

Using zonal statistics, we calculate the sums of the pixels of the urban class for each census tract. Pixels within the small study area increased in

intensity from 2001-2011 – areas that had little no structures increased in urban intensity.

NLCD failed to provide an accurate measurement of the urban land cover due to fundamental framework.

NLCD products are designed to only detect growth – areas which have increased in urban intensity.

Figure 8: Aerial image of the small study area from 2011.

Figure 9: A comparison between the 2001 and 2011 NLCD Land Cover product for one urban class which displays pixels that have increased in intensity.

We use LIDAR from 2009 to create an elevation of different structures within the small study region. Objects with higher elevations are objects such as trees, houses,

and commercial buildings. The disadvantage to using LIDAR is that there is a limited availability of

imagery. We will use LIDAR in the future to develop a method for detecting and

differentiating between structures in order to determine abandonment.

Figure 4: We calculate the percent population change from 2000-2010 and compare that to the percent change in the number of pixels from the NLCD Land Cover product. This chart displays the results from the comparison to the Developed, Medium Intensity class for the total study area.