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Article

The Influence of Power on Post-Buyout Land Management Practices

by
Sumaira Niazi
1,
Elyse Zavar
1,*,
Alex Greer
2 and
Sherri Brokopp Binder
3
1
Department of Emergency Management and Disaster Science, University of North Texas, Denton, TX 76205, USA
2
Department of Emergency Management and Homeland Security, University at Albany, Albany, NY 12222, USA
3
BrokoppBinder Research & Consulting, Allentown, PA 18102, USA
*
Author to whom correspondence should be addressed.
Histories 2025, 5(1), 14; https://doi.org/10.3390/histories5010014
Submission received: 29 December 2024 / Revised: 28 February 2025 / Accepted: 10 March 2025 / Published: 20 March 2025
(This article belongs to the Section Environmental History)
Browse Figures
Versions Notes

Abstract

:
U.S. government agencies execute home relocation programs, known as buyouts, in flood-prone areas to reduce hazard exposure. By converting the buyout properties into open space, these governmental agencies assume ownership and management responsibilities. As with all landscapes, the post-buyout landscape reflects power dynamics and institutional forces that shape how the land is managed, perceived, and used. For acquired properties, historic housing polices, disaster risk reduction strategies, and the social construction of the land have all accumulated over time on the post-buyout landscape and influence contemporary land management practices. To understand the influence of power and social capital on post-buyout land management, this study analyzes land management practices and compares them with the socioeconomic characteristics of buyout neighborhoods in Harris County, Texas, USA, a county with a fifty-year buyout history. Results indicate that homeownership status, race, and ethnicity were related to post-buyout land management to varying degrees, thus reflecting differing degrees of social capital in buyout neighborhoods and therefore power to shape the management of post-buyout open space.

1. Introduction

Floods are among the most frequent and costly hazards in the U.S., resulting in extensive losses to natural and anthropogenic features every year (FEMA 2008). Governments utilize both structural and nonstructural risk reduction practices to mitigate future flood hazards and increase community resilience or use their ability to absorb disruptions and retain functionality (Tyler et al. 2019). Given the cost of repeated infrastructural elevations, river channelization, and levee repair, which will only increase as global climates warm, many communities are implementing nonstructural mitigation measures, such as household relocations, as a climate adaptation technique (NOAA 2013). In the U.S., these relocation programs, often termed buyouts, acquire homes at pre-storm value to remove households from floodplains or other hazardous zones (FEMA 2008). This mitigation strategy has relocated over 40,000 homes over the last four decades in the U.S. (Mach et al. 2019) and is growing in popularity in other countries such as Australia, Canada, Fiji, Japan, and New Zealand (Cottar et al. 2021; Harker 2016; McMichael et al. 2019; Piggott-McKellar and Vella 2023; Pinter et al. 2019). In the U.S., local or state government agencies administer buyout programs and offer property owners the pre-flood market value of their damaged properties, which are later converted into open spaces (FEMA 2008). Federal grants pay to demolish and remove infrastructure from the acquired land; however, the management of the resulting open space is typically the responsibility of the local government (Smith et al. 2023). Open space post-buyout land uses must be within federal guidelines; however, land use decisions occur at the local government level and range from low-utility vacant lots to well-maintained community parks (Zavar and Hagelman 2016). These open space management decisions, and even those concerning who is at risk to flood hazards to begin with, are not arbitrary; rather, they reflect long-established, historic, institutional forces that shape housing patterns, hazard exposure, and risk reduction opportunities (Elliott et al. 2020; Loughran and Elliott 2021; Zavar and Fischer 2021). Therefore, power plays a critical role in who lives where, what hazards they encounter, and if that risk is abated.
Power affords a social group control over the political, economic, and social structures with a society (Baker 2024). With this power, the dominant social group can exert control over a wide range of activities that govern everyday life, including policy, access to resources, and cultural norms. The results of this power accrue and persist on the landscape; thus, historic power dynamics influence, shape, and determine contemporary actions. People sharing the same sociodemographic characteristics as the dominant social group gain benefits or privileges from this power. Conversely, those with sociodemographic characteristics that differ from the dominant social group are at minimum disadvantaged, or harmed, by these social constructions, policies, and resource allocations. Race, ethnicity, immigration status, homeowner status, income, education, gender identity, and sexual orientation are just some of the identities that historically have, and continue to, marginalize groups (Baker 2024). Hazard risk exposure, hazard mitigation, and post-buyout open space land management are all shaped by these same power dynamics (Elliott et al. 2020; Loughran and Elliott 2021; Zavar and Fischer 2021).
These power dynamics, as evidenced through the range of post-buyout land uses, are especially visible in Harris County, Texas, which houses one of the country’s oldest and largest buyout programs due to the high occurrence of flooding and hurricanes (HCFCD 2023). In response to 2017’s Hurricane Harvey, the Harris County Flood Control District (HCFCD) expanded its nearly fifty-year buyout program to acquire more homes. This has resulted in thousands of acquired properties for the local government to manage. A growing body of literature has highlighted transparency issues regarding program eligibility and timelines (Lynn 2017), questions regarding the voluntariness of buyouts (de Vries and Fraser 2017; de Vries and Fraser 2012), and inequitable or discriminatory practices during the selection and implementation period of buyout programs (de Vries and Fraser 2017; Elliott et al. 2020; Green and Olshansky 2012; Loughran et al. 2019; Siders 2019a). However, this is one of the first studies to explicitly examine issues of equity and power in post-buyout land use management, as the limited research available focuses on buyout program participation or where people relocate to (Elliott et al. 2020; Elliott and Wang 2023; de Vries and Fraser 2012; Green and Olshansky 2012; Kraan et al. 2021). This is particularly relevant to Harris County, given the diverse demographics and socioeconomic statuses present in the county, which hosts over 4.7 million people (U.S. Census Bureau 2022).
Understanding the relationship between power, sociodemographic characteristics, and open space management is critical, as the resulting land use of a buyout shapes the mitigation potential of the open space and can affect adjacent residents through the (dis)amenities of the post-buyout landscape. Therefore, the objective of this study was to analyze post-buyout land use management practices and compare the uses and aesthetics of buyout properties with the sociodemographic characteristics of the adjacent neighborhood at the block group level in Harris County, Texas. Specifically, this study examined how power dynamics, represented by sociodemographic characteristics, influence post-buyout land use management practices in Harris County, Texas. This research contributes new knowledge to an understudied area of mitigation and contributes to community-wide resilience goals that seek to address the uneven impacts of climate change.

1.1. Literature Review

The impacts of climate change and its associated hazards are increasing worldwide (IPCC 2021), causing governments to seek climate adaptation strategies. Relocation has allure for policymakers given the promised cost savings and avoidance of future losses (Eichhorst and Baskin 2009), although these are viewed as last-resort strategies that can have both positive and negative impacts on program participants and surrounding communities (Burkett 2015). Studies generally suggest that buyouts are cost-effective in terms of their direct benefits (BenDor et al. 2020). For example, flood mitigation efforts in the U.S. over the last 23 years have provided national fiscal savings of USD 6 for every USD 1 spent (Nassauer 1997). Moreover, buyouts theoretically can reduce the workload of emergency management organizations and lessen risk exposure to first responders. If utilized properly, the open space created by the buyout program can enhance the natural habitat, increase biodiversity, and promote healthy ecosystems (Nelson and Camp 2020).
Despite these benefits, there are many challenges associated with the implementation of buyout programs and the management of post-buyout open space. Buyouts are often planned after flood events, creating socioeconomic and psychological hardships for people already dealing with the impacts of disaster (Zavar et al. 2022). Transparency issues while selecting properties for inclusion give rise to mistrust in the community, reducing the effectiveness of the program (Binder et al. 2020; Siders 2019a, 2019b). Moreover, voluntary buyout programs historically have been slow to implement, resulting in attrition among homeowners who initially expressed an interest in relocating (Dineva et al. 2022). High rates of attrition often result in the checkerboarding of land, creating hurdles for post-buyout land development (Atoba et al. 2021).
Beyond these implementation challenges, the literature also identifies several equity concerns, especially related to development in high-risk areas and creating affordable housing for those who relocate (Shi et al. 2022). The results of a case-based investigation of Houston’s buyout neighborhoods revealed that federal disaster funding for flood mitigation and recovery has historically favored higher-income communities (Hersher and Benincasa 2019), while lower-income neighborhoods have been more likely to participate in buyout programs (Elliott et al. 2020). Likewise, relying on a cost–benefit approach to drive decision-making and subsequently striving to acquire as many properties as possible has resulted in buyouts being historically implemented more frequently in lower-income flood-prone areas than in higher-property-value coastal areas (Patterson 2018; Song et al. 2017).
Although there is limited research exploring land use post-buyout, existing studies suggest that federal policies, the local government’s land management priorities, historical patterns of land use and land management, and community culture all play key roles in deciding future land uses (Zavar 2015). Owing to these mechanisms, research shows that post-buyout sites in higher-income neighborhoods tend to offer more amenities and higher-utility land uses, such as parks and wetlands, as compared to lower-income neighborhoods (Rigolon 2016; Elliott et al. 2020). This aligns with the larger literature that suggests that neighborhoods of Color and lower-income areas are more likely to contain smaller, more congested parks than whiter areas (Boone et al. 2009; Sister et al. 2010). These variances in utility and amenities are a product of social group power dynamics (Baker 2024) or even the social capital of a group (Clay et al. 2017), which influence how post-buyout open space is managed and maintained.
Given that buyouts are more likely to occur in lower-income neighborhoods and amongst residents of Color (Loughran and Elliott 2021), the management of post-buyout open space can correct past land use decisions and improve residents’ access to services. This opportunity to create high-utility land uses is also important considering that post-buyout land management practices impact peripheral residents considerably, as they live adjacent to and regularly interact with the acquired properties (Binder et al. 2020). To increase the community-wide value and utility of the acquired land, federal agencies and scholars have highlighted several potential post-buyout land uses to promote ecosystem diversity and increase floodwater absorption, such as the creation of wetland habitats (FEMA 1998; Harter 2007; Atoba et al. 2021; Dascher et al. 2023). For instance, increasing tree canopy cover can enhance air quality, reduce the impact of urban heat, and improve ecosystem health (Hirokawa 2010). Even a regularly mowed lawn can offer an aesthetically pleasing space that positively impacts property values (Irwin 2002). Beyond these services, post-buyout open space can offer recreational opportunities through parks, sports fields, and walking trails (Zavar and Hagelman 2016). Open spaces can also serve as gardens, offering both recreational and provisioning services to communities (Vanucchi 2023).
Despite these intentions, most post-buyout open spaces remain mowed vacant lots due to financial constraints and a lack of land use planning prior to the buyout (Zavar and Hagelman 2016). Additionally, there are few documented examples of implementing agencies integrating residents into the post-buyout land use planning process, which can result in uses that do not meet resident wants or needs (Zavar and Hagelman 2016). Based on this growing body of literature, this study seeks to analyze the (in)equities associated with post-buyout land maintenance and use through a case study in Harris County, Texas.

1.2. Harris County, Texas—Case Study

Harris County, Texas, home to Houston, the largest city in Texas (Henson 2020), supports a large buyout program across a diverse population, with over 40% of the population identifying as Hispanic, 68% as white, 21.1% as Black, and 7.7% as Asian (U.S. Census Bureau 2023). Owing to its location on the Gulf Coast and historical zoning patterns, Harris County has a long history of flooding and, on average, has experienced significant flooding every two years (HCFCD 2023; Figure 1). County records show that 48 environmental disasters affected Harris County from 1900 to 2019. However, Hurricane Harvey in 2017 was one of the most damaging, resulting in the flooding of 154,170 homes and a total loss of USD 125 billion (HCFCD 2022). In response to Hurricane Harvey, the HCFCD expanded its long-standing buyout program. Before Hurricane Harvey, the HCFCD acquired approximately 3100 properties and restored more than 1060 acres of land in Harris County’s floodplains with the help of FEMA funding (Zavar et al. 2022). As of May 2023, the HCFCD had completed an additional 1028 buyout properties, with more in progress. These property buyouts in Harris County are distributed across socioeconomically diverse areas, providing an ideal case study site to analyze issues of power and equity in post-buyout land management. With this context, this research addresses the relationship between neighborhood demographics (including race, income, and homeownership status) and post-buyout land management practices.

2. Materials and Methods

To understand how land management practices differ across socioeconomic statuses (SESs) in Harris County, we employed a mixed-methods approach consisting of photo documentation and GIS analysis. We selected these methods as they provide a robust analysis of land use and landscape aesthetics as experienced by individuals living adjacent to these properties or using the amenities offered by the post-buyout open space. First, we identified and photographed post-buyout properties in Harris County. Second, we developed a framework of indicators based on Ode et al. (2008) to evaluate post-buyout land use management. Finally, we conducted spatial analyses in ArcGIS of the sociodemographic composition of buyout neighborhoods using U.S. Census Data American Community Survey 5-year data (2017–2021) compared with the post-buyout land use management practices identified in phase two.

2.1. Phase One—Data Collection

First, our research team identified post-buyout land use properties and management practices using county records. We selected properties using a purposive sampling technique to include diverse geographical distributions (e.g., urban, rural, and suburban) and socioeconomic status ranges, prioritizing clustered properties to ensure we could include as many buyout properties as possible in Harris County (Patton 2014). Following the identification of buyout properties, our research team conducted fieldwork across four one-week visits in Harris County between 2017 and 2022. Following Oldrup and Carstensen (2012), we took photographs of each property using a defined protocol to capture similar details of all the buyout properties. Photographs of each buyout property were taken from the curb or sidewalk as available, and secondary photographs were taken on the properties to capture details (e.g., signs, debris, playgrounds; Zavar et al. 2023). These digital photographs also captured georeferenced locations. We supplemented these coordinates with field notes describing each photograph’s location and geospatial markers, such as cross streets.
Following photo documentation, we classified the buyout properties into 188 buyout zones, which we defined as a collection of spatially adjacent buyout properties managed by the HCFCD that occur within a neighborhood. Following the acquisition, property management falls under the jurisdiction of local administrative authorities (FEMA 1998). The HCFCD is responsible for maintaining all buyout properties in a neighborhood, including mowing, leaf blowing, and tree trimming. The HCFCD provides eight regular lawn mowing sessions during the growth season, and they schedule maintenance by neighborhood (HCFCD 2023). Therefore, organizing our study units by buyout zone reflects maintenance practices. In addition, several post-buyout land uses provide challenges in distinguishing independent parcel boundaries, such as parks or detention basins, which may have been built on hundreds of separate lots and are managed as one open space. According to the requirements of maintenance set by the HCFCD (2023), the size of the land has little influence on county management procedures.
Given that we aimed to gather as many details as possible about each buyout zone for stewardship analysis, there was no limit to the number of photographs taken per zone. The number of pictures for each zone ranges from three to twenty, depending on the size of the zone. In total, we analyzed over 2000 photographs from across the county. The final dataset of photographs represents almost 75% of the total buyout properties in Harris County acquired before 2020.

2.2. Phase Two—Coding

Next, we analyzed the photographs using a deductive coding structure. Using Microsoft Excel, each photograph was assigned to a zone based on geographic location. We developed a codebook to visually assess post-buyout land use, aesthetics, and management practices to classify the post-buyout land use (Zavar and Hagelman 2016) and stewardship (Ode et al. 2008) of each zone (Table 1). The land use codes identify the function of post-buyout open space and describe the utility of each zone, such as a park, athletics, and a detention basin. We defined utility as, “the usefulness of a zone for a particular purpose, taking into account its physical characteristics, location, and regulatory context” (Platt 2014, p. 96). Specifically, we classified the buyout zones as either high-utility land uses, which are those that offer increased social, ecological, or economic value, or low-utility land uses, which include land uses that do not provide risk reduction or amenities to the community, as discussed by Dascher et al. (2023). Notably, some zones contained more than one use and therefore more than one code. The 11 codes representing stewardship evaluate the level of care and aesthetic qualities of zones and describe the management and conservation efforts undertaken by local bodies for these places. Varying degrees of stewardship reflect the management priorities of the local entities responsible for maintenance (Nassauer 1995, 1997; Ode et al. 2008). We further divided stewardship into two types: (1) natural and (2) built environment (Ode et al. 2008; Table 1).
Following coding, we attributed positive and negative values to the stewardship codes based on Nassauer (1995, 1997) to indicate the level of care and management shown for each buyout zone, as shown in Table 1. For example, buyout zones were categorized as (+1) if the grass was mowed, whereas zones with overgrown grass were categorized as (−1). Similarly, in zones where maintenance crews could not access the property for management, whether due to a locked door, gates, or road blockade, the zone was categorized as (−1) for accessibility. Conversely, if the zone was easily accessible for land management, we coded it with a positive value (+1). Having an HCFCD sign was coded as a favorable indication of land management, indicating that officials publicly displayed their responsibility to maintain the properties, and therefore, we assigned a value of (+1). The existence of services such as phone lines and mailboxes indicated that the HCFCD retained development in the zone, thus limiting open space land use options, resulting in a code of (−1). Likewise, we classified any redevelopment activities carried out by residents in the zones as infractions and coded them as (−1) for these violations. In several zones, the photographs captured maintenance crews mowing lawns, and we assigned a (+1) rating to these actions in the active management code.
Once all the stewardship codes were evaluated for positive and negative values, we summarized the scores to create a land management index score for each buyout zone (Figure 2). The scores on this index ranged from −5 to 5, with negative scores indicating poor land management practices and positive scores indicating more normative, aesthetically pleasing practices (Figure 3). For each buyout zone, we calculated descriptive statistics of the land management index scores, including the mean and frequency. These index scores were also used in phase three for spatial analysis, as discussed in Section 3.
Finally, to ensure the reliability and validity of our coding system, we evaluated each photograph’s quality and reported confidence levels of the photographic interpretation of each image (Table 1). To increase intercoder reliability, a minimum of two researchers coded all photographs. Field note observations supplemented the rare instances of low confidence, and research team members who were present during fieldwork discussed observations to reduce uncertainty.

2.3. Phase Three—Spatial Analysis

During phase three, we spatially analyzed the sociodemographic composition of the buyout study zone neighborhoods using ACS 5-year 2017–2021 data (U.S. Census Bureau 2021) in ArcGIS. For demographic analyses, we used census data on race/ethnicity, household income, and home ownership status at the block group level. We classified Harris County block groups by their population majority categories: white, Black, Asian, or Hispanic. We recognize that people who identify their ethnicity as Hispanic may be of any race and note this as a limitation of our study. Utilizing median household income data, we divided the block groups into (1) households earning more than the living wage and (2) households earning less than the living wage. We used the MIT living wage calculator (MIT 2023) to calculate the living wage for Harris County and defined it as the minimum income required to meet basic needs. For housing ownership status, we classified the block groups as either majority renter-occupied or majority owner-occupied. Next, we spatially compared these census demographics with the landscape management index scores developed in phase two using ArcGIS. From this spatial analysis, we identified patterns of post-buyout open space management practices related to socioeconomic characteristics in Harris County, Texas.

3. Results

Of the 188 zones analyzed in this study, approximately 46% were in areas with a majority-white population, 44% were in Hispanic-majority areas, 9% were found in areas with a majority-Black population, and none were in Asian-majority neighborhoods. The analysis did not show significant differences in the land management index scores by race and ethnicity, although the range of index scores and modes identified more nuanced results. For neighborhoods with a majority-Black population, 44% of the study zones had negative land management index scores. However, none of the study zones in Black-majority neighborhoods scored higher than 2 on the land management index; index scores ranged between −5 and 2, with a mode of −1 (Figure 4). Scores among white- and Hispanic-majority neighborhoods were similar, with 79% of Hispanic-majority neighborhoods and 77% of white-majority neighborhoods scoring positive indexes, and both groups scored a mode of 2 on the land management score index. However, Hispanic-majority neighborhoods had more scores above 2 on the index than white-majority neighborhoods, indicating improved maintenance and care of the open space. Taken together, these data show that white- and Hispanic-majority neighborhoods more frequently experienced positive land management index scores and higher positive index values, suggesting more aesthetically pleasing practices in these neighborhoods when compared to Black-majority neighborhoods.
We further analyzed the relationship between race, ethnicity, and open space maintenance using two indicators previously identified in the literature: lawn mowing and trash dumping (Nassauer 1995, 1997). Beginning with lawn mowing, we compared race/ethnicity and grass length. Our results showed that Black-majority populations had the highest percentage of buyout zones with tall (unmown) grass at 50% of zones, while 37% of white-majority and 24% of Hispanic-majority neighborhoods were coded as having tall grass. Therefore, the predominantly Hispanic neighborhoods reported the largest percentage of buyout study zones with mowed lawns (76%).
Concerning the presence of garbage and trash in the buyout zones, we identified that Hispanic-majority areas had the highest percentage of buyout zones with trash and/or debris accumulation (45%), as compared to white-majority neighborhoods (17%) and Black-majority neighborhoods (12%) (Figure 5). In lower-income neighborhoods, 55% of buyout study zones had trash and/or debris, compared to only 22% of the buyout study zones in higher-income areas. These results indicate that rates of litter and illegal dumping vary based on the socioeconomic status of the neighborhood.
Next, we analyzed the status of land utility by comparing it against racial and ethnic demographics (Figure 6). Across all races, low-utility land uses outnumbered high-utility land uses. The buyout zones with a Black population majority had the highest ratio of overall low-utility land uses but had a lower percentage of vacant lots (69%) as compared to the white- (76%) and Hispanic-majority areas (76%). Mobile homes were only present on post-buyout land in Hispanic-majority population areas, while new construction was observed only in white-majority population areas. High-utility land uses were less common in Black-majority areas (only 6% of all zones were categorized as high-utility), while white-majority areas had the highest frequency of high-utility land uses (18%). The white-majority neighborhoods also reflected more types of high-utility land uses, while detention basins were the only high-utility land use present in Black-majority neighborhoods. Hispanic-majority areas had the highest frequency of parks among the study zones, but overall high-utility zones remained infrequent in these areas as well (Figure 6).

3.1. Economic Status and Land Management Practices

We then compared household economic status with land management practices in the study zone neighborhoods. We spatially compared Harris County’s median household income at the block group level with the landscape management index score (Figure 7). We observed that over 65% of the buyout study zones occurred in lower-income areas, while the remaining 35% occurred in higher-income areas. The analysis of the land management index score as it related to the economic status of Harris County residents did not show significant differences between lower- and higher-income areas. Among the higher-income population, 75% had a positive landscape management score (0–5), while 73% of the lower-income community had a positive landscape management score. However, the mode of the land use management index score in the majority-higher-income areas was 3, whereas for the majority-lower-income areas, it was 2 (Figure 7).
We also examined the association between the Harris County residents’ economic status and open space management using two indicators: grass mowing and garbage dumping (Nassauer 1995, 1997). Beginning with lawn mowing, we compared median household income status and grass length. Our data indicated that there is not much variation in the state of grass mowing between regions with higher- and lower-income majorities (Figure 8). Regarding the prevalence of trash and garbage in the buyout zones, we found that majority-lower-income regions have a larger percentage of trash (44%) than majority-higher-income areas (17%). These findings suggest that littering and unlawful dumping rates differ according to the neighborhood’s socioeconomic standing.

3.2. Economic Status and Land Use Utility

Next, we examined land use utility across income levels in relation to economic status. We observed eleven types of open space land uses in the buyout zones comprising six categories of low-utility land uses, including buyout zones fenced by adjacent neighbors serving as parking lots, hosting sheds, vacant lots, neighborhood-managed lots, mobile homes, and new construction, and five categories of high-utility land uses, including trails, parks, detention basins, sports grounds, and land returned to nature. There was a stronger presence of low-utility (83%) than high-utility (17%) uses across all incomes. We found that 74% of all buyout zones were managed as vacant lots. Parking lots were not present in higher-income areas but were the second-most common low-utility land use in lower-income areas (8%). Additionally, we noticed a variety of unofficial land uses that adjacent neighbors were applying, such as hosting sheds and mobile homes, which are not in keeping with the open space management policies defined by FEMA (1998). These unofficial land uses accounted for 3% of majority-higher-income buyout zones and 10% of majority-lower-income buyout zones.
Overall, high-utility land uses were observed less frequently than low-utility uses in the buyout zones (Figure 9). Only 12% of buyout zones in the majority-lower-income areas had high-utility land uses and 25% of buyout zones in the majority-higher-income areas had high-utility uses, thus indicating more investment in high-utility land uses in more affluent areas. Athletics spaces, such as soccer fields and basketball courts, were found to be the most prevalent high-utility land use type in majority-higher-income buyout zones, accounting for 10% in these zones, while accounting for 3% of land uses in majority-lower-income buyout zones. Buyout zones left to return to nature, which offer ecosystem benefits to the community, were the second-most frequent land use in both higher- (5%) and lower-income (4%) areas. Meanwhile, majority-higher-income buyout zones had a greater percentage of parks (5%) and trails (3%), as compared to majority-lower-income areas, which were 2% and 1% parks and trails, respectively.

3.3. Homeownership Status and Post-Buyout Land Management

Finally, we examined homeownership status compared with post-buyout land management. The results from the spatial analysis indicate that 45% of renter-occupied properties had negative post-buyout land management, whereas 23% of owner-occupied properties scored negatively. Buyout zones with majority owner-occupied status had a mode of 2 in terms of landscape management index score, while renter-majority areas had a mode of −1 (Figure 10).

4. Discussion

Post-buyout land management is typically the responsibility of local administrative authorities, with local funds supporting the long-term management of the properties (BenDor et al. 2020), yet the management of these properties is subject to historical and cultural power influences. The existing body of literature extensively documents that communities of Color, lower-income residents, and renters are more vulnerable to hazards due to a range of social group power dynamics including historic discriminatory housing policies, unaffordable hazard insurance, and lack of access to resources to mitigate future hazards (e.g., Emrich et al. 2020; Fothergill and Peek 2004; Loomis 2018). The intersections of these sociodemographic characteristics only increase social and physical vulnerabilities.
Our analysis reflects some of this history (Elliott et al. 2020), yet the results are more nuanced than previously represented in the post-buyout land management literature. Our findings show that socioeconomic characteristics—specifically race, income, and homeownership status— influenced land management aesthetics and stewardship. The study results illustrated that Hispanic-majority, higher-income, and owner-majority buyout zones all experienced higher instances of manicured lawns in Harris County, while areas with a Black population majority had the highest ratio of tall grass. Notably, areas with white and Hispanic population majorities shared similar outcomes, reflecting the intersections of race and ethnicity, especially in Harris County, Texas, which hosts a large Hispanic population (U.S. Census Bureau 2023). It is important to note that these maintenance practices are the responsibility of the local government and reflect social group power dynamics rather than the actions of individual group members residing in the neighborhoods.
Although the historic distribution of resources has an impact on current land management techniques, present HCFCD policies strongly influence stewardship, especially trash removal (HCFCD 2023). It was evident during our fieldwork that the buyout lots tended to receive more care and additional services from neighboring residents who took it upon themselves to maintain the lots adjacent to their properties. This highlights the systematic inequities, as it often depends on the residents’ financial capabilities or availability to dedicate their own time to managing neighboring properties (Heynen et al. 2006). According to the deeds in Homeowners Association neighborhoods, some communities can pay for additional maintenance services or demand additional services. Any Municipal Utility District (MUD) can request and take over mowing in their area, while neighboring residents can also temporarily rent adjacent buyout lots to maintain for their personal use (HCFCD 2023). It is critical to recognize that affluent communities often have more resources available to improve the aesthetics of their areas, which may protect property values (Duncan and Duncan 2001). In contrast, a lack of investment in lower-income areas can result in declining property prices and have a detrimental impact on the community’s well-being.
Traditionally, research on land use management has suggested that homeowners tend to be more engaged than renters in maintaining their neighborhoods due to their monetary incentive and place attachment (Yun 2012; Rohe and Stewart 1996). Therefore, homeowners often invest their time and also push city management authorities for neighborhood management. Renters, on the other hand, might not feel as attached to their areas, owing in part to housing insecurity and restricted decision-making power (Freeman and Manturuk 2019). These variances can result in variable degrees of maintenance, appearance, and facility availability in various communities. Our study buyout zones exhibited similar trends, where areas with mostly homeowners had higher post-buyout land use management index scores than neighborhoods with mostly renters. This suggests resident engagement and social capital plays a role in influencing post-buyout land use management practices in Harris County, Texas. Social capital utilizes relationships and networks to provide resources, support structures, and opportunities that otherwise might not be available to marginalized groups, therefore generating collective action that challenges existing power dynamics (Auer et al. 2020).
The maintenance of buyout lots also includes trash removal (HCFCD 2023), yet litter and illegal dumping, especially construction materials and mattresses, were observed. Illegal dumping is a major policy concern for local governments because it not only harms the environment but also deteriorates public health and reduces property values (Gardinetti 2022). Our research indicated that areas with Hispanic-majority populations experienced more accumulation of debris and trash as compared to non-Hispanic communities. Similarly, areas with a lower-income majority were observed to have a larger presence of debris and trash as compared to majority-higher-income-areas. The high volume of dumping is proof of the significant differences in governmental policies and practices.
Beyond maintenance, the utility of the 188 buyout zones varied. High-utility post-buyout land uses, such as parks, gardens, and detention basins, can maximize community mitigation practices and increase resilience to future hazards and climate-induced disasters (Zavar and Hagelman 2016; Dascher et al. 2023). For instance, constructing detention basins and wetlands in post-buyout open spaces improves the absorption capacity for excess water, thereby reducing future flood risk. Additionally, it filters runoff, thus improving the quality of water in streams (Zavar and Hagelman 2016). However, the literature suggests that these high-utility uses are rare and maybe even less common in lower-income areas and neighborhoods of Color (Elliott et al. 2020; Zavar and Hagelman 2016). The empirical evidence from this study indicated such trends in Harris County, where lower-income communities and communities of Color contained fewer high-utility land uses as compared to higher-income, white, and Hispanic communities.
However, the two parks observed in this study created or expanded by buyouts are in lower-income neighborhoods of Color. During our fieldwork, we observed residents of all ages using the recreation amenities at both parks, which also incorporate detention basins into the design to reduce flood risk for the surrounding neighborhoods. The development of both parks involved many local government departments, community groups, and area partners, highlighting the need for engaged stakeholders to drive the construction of high-utility uses, particularly in historically underserved neighborhoods. This is consistent with previous literature calling for more engagement with residents (Manda et al. 2023) and research on the role of engaged community members, or magnetic agents, who can spearhead the development of post-buyout land uses (Zavar and Hagelman 2016). Despite these two parks, across Harris County, there is a prevalence of low-utility post-buyout land uses, especially in communities of Color. There are many potential reasons behind these trends, including hurdles in the development and management of land use due to the checkerboarding of land and financial constraints at the government level for the development of high-utility land uses including parks and trails (Zavar and Hagelman 2016). Residents with more trust in local government, political power, and resources may be more likely to persuade those in power to invest those limited resources into their neighborhoods. Regardless of the reasons, the prevalence of low-utility land uses minimizes the amenities and risk reduction benefits available to the buyout-adjacent neighborhood (Zavar et al. 2022).
The open space acquired through the implementation of buyout programs can be used to develop sustainable amenities for residents, which can not only provide the community with the opportunity to protect areas from future flood losses but also serve as a source of recreation and environmental protection (Dascher et al. 2023). For instance, community gardens, parks, water reservoirs, and trails provide many benefits for residents adjacent to buyout properties (Zavar et al. 2022). These amenities may even increase home values for adjacent properties (Bin et al. 2008). Despite the benefits, high-utility uses are infrequent, especially in historically underserved areas. Research indicates that higher-income neighborhoods have better access to amenities such as parks and green spaces as compared to lower-income areas (Rigolon 2016). Yet our results found that in terms of amenities in buyout zones, all residents of Harris County, regardless of economic status, race, or ethnicity, are lacking amenities and higher-utility land uses. Given that the HCFCD operates one of the largest buyout programs in the country, alongside the high percentage of properties remaining in the floodplain (HCFCD 2023), post-buyout land use development may remain a lower priority at this time.

5. Conclusions

This study offers one of the first examinations of the relationship between post-buyout land use management practices in Harris County, Texas, and power via neighborhood sociodemographic characteristics. To evaluate this dynamic, we used a novel mixed-method approach that included photo documentation, visual content analysis, and comparative spatial analysis to analyze land management practices. Although previous research on post-buyout land use suggests land management practices vary by the sociodemographic characteristics of the neighborhoods (e.g., Elliott et al. 2020; Zavar and Hagelman 2016), this study contributes to the literature by providing empirical evidence of land management practices on post-buyout properties in a diverse county of the U.S. It offers a critical perspective of how the sociodemographic characteristics of buyout neighborhoods influence the land stewardship of the resultant open space.
Our analysis identified several patterns in Harris County’s post-buyout land use management practices influenced by historic and contemporary power dynamics. First, our 188 study zones demonstrated that white- and Hispanic-majority neighborhoods experienced more aesthetically pleasing land management practices than Black-majority neighborhoods. We observed, as is consistent in the literature, debris and trash more frequently in lower socioeconomic neighborhoods and higher-utility land uses, such as wetlands, parks, and trails, less frequently in lower-income areas. However, our results indicate a lack of amenities and higher-utility land uses across all buyout zones in Harris County. Although suggested in the literature, this study is the first to confirm that neighborhoods of Color and neighborhoods with high rates of renters more frequently experience reduced stewardship, as demonstrated by tall grass and litter, yet the Hispanic-majority areas experience more regular mowing and lawn care, suggesting race is a more influencing factor than ethnicity in Harris County, Texas.
Based on these empirical data and previous academic research studies, we propose the following suggestions to improve post-buyout land use practices with an equity focus that reduces power imbalances. First, community engagement in designing post-buyout management practices through co-production addresses many of the observed buyout land use issues. The goal of co-production is to generate knowledge through collaboration and equal participation of researchers and stakeholders, the sharing of skills and resources, and the development of pertinent and actionable solutions (Bezerra et al. 2023). Although community engagement is frequently viewed as a one-way process of transmitting knowledge to the community or raising awareness in society, co-production involves collaboration from the stage of problem formation to the stage of implementation, resulting in more practical and meaningful solutions (Stilgoe et al. 2014). Collaboration between researchers, local government administration, and stakeholders on the sharing of knowledge, experiences, resources, and skills, as well as the dissemination of results in policy and practice, can yield long-term effects on post-buyout land use development problems.
Second, interdepartmental collaboration and coordination have the utmost significance for the complex projects of urban development (Tzeng and Huang 2011). One such project, the Shady Lane Park playground, has already been successfully implemented in a Hispanic-majority area (NRPA 2023) after Tropical Storm Allison in 2001. However, the need is to adopt this interdepartmental collaboration strategy in multiple projects for sustainable city growth. It is an excellent example of community engagement, participatory design, and long-term collaboration among numerous departments, including the Harris County Flood Control Authority, the Houston Parks and Recreation Department, the Houston Public Works and Engineering Department, the National Recreation and Park Association, and others. The community participated in the project from its conception to its completion (NRPA 2023). It was jointly funded by Texas Parks and Wildlife, Gametime, and NRPA. Sharing expertise, sources, and knowledge not only solved flood problems through the structural development of a detention basin but also provided much-needed amenities to surrounding communities (NRPA 2023). In the future, such multifaceted projects should be promoted to not only help communities with their recreational needs but also distribute the financial burden of development among multiple departments. Nevertheless, community engagement at all stages will make projects more socially equitable.
Third, adequate funding for the development of high-utility land uses is critical to any project’s success. Scholarship stresses the value of dedicated financial aid provided by local governments to facilitate environmental justice and upgrade target communities of lower SES (Cohn et al. 2017). However, the rehabilitation of neighborhoods with lower SES should be managed in a way that may not cause gentrification, as this will further raise these communities but increase the land value and eventually impact the cost of living. As such, a balanced approach is required that devotes resources to underserved areas without displacing long-term residents (Zimmermann and Lee 2021).
Although this study identifies needed research on post-buyout land management practices, an understudied area, there are some limitations to this work. First, this study focuses on etic perspectives of land management. Future research should involve interviews with stakeholders to develop a deeper understanding of land management practices and how people interact with these landscapes. Second, given that our study was cross-sectional, changes in the type and condition of land use over a period could not be recorded. Future work should consider longitudinal practices and identify factors that influence change in land management over time. A third limitation is that this is a case study and is limited to one geographic area. The results may not be generalizable outside of this location. Consequently, we suggest repeating this study in other communities implementing buyouts. Post-buyout land use practices may also differ depending on rural versus urban areas, the government’s experience implementing hazard mitigation programs, the level of community engagement in the community, and the acreage/distribution of acquired properties. As buyout programs continue to increase in the face of climate change, additional research is needed to understand this hazard risk reduction technique and the associated (in)equities involved at each stage of these programs.

Author Contributions

Conceptualization, S.N. and E.Z.; methodology, S.N., E.Z., A.G. and S.B.B.; formal analysis, S.N., E.Z., A.G. and S.B.B.; writing—original draft preparation, S.N., E.Z., A.G. and S.B.B.; writing—review and editing, S.N., E.Z., A.G. and S.B.B.; visualization, S.N., E.Z., A.G. and S.B.B.; funding acquisition, E.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded in part by the National Science Foundation Humans, Disasters, and the Built Environment 1844351: RAPID: Exploring the Design and Implementation of Buyout Programs in Post-Disaster Settings and the Gulf Research Program Early Career Fellowship.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the University of North Texas (protocol code 18-327 approved on 14 August 2018).

Informed Consent Statement

Not applicable, for non-participant observation was used in this study.

Data Availability Statement

Data will be made available upon contacting the corresponding author.

Acknowledgments

We express our sincere gratitude to the study participants for their time and willingness to share their experiences. We also thank Prabin Sharma, Georgia Green, Krystian Murray, and Ellen Christensen for their assistance with fieldwork and the anonymous reviewers for their constructive feedback.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Site map of Harris County, Texas, depicting the case study buyout zones.
Figure 1. Site map of Harris County, Texas, depicting the case study buyout zones.
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Figure 2. Examples of study zones with land management index scores.
Figure 2. Examples of study zones with land management index scores.
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Figure 3. Range of land management index scores per study zone (n = 188).
Figure 3. Range of land management index scores per study zone (n = 188).
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Figure 4. Land management index score by race and ethnicity.
Figure 4. Land management index score by race and ethnicity.
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Figure 5. Land management as indicated by grass mowing and trash removal compared with buyout zone race and ethnicity characteristics in Harris County, Texas.
Figure 5. Land management as indicated by grass mowing and trash removal compared with buyout zone race and ethnicity characteristics in Harris County, Texas.
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Figure 6. Land use distribution for high-utility and low-utility with race or ethnicity distribution in Harris County, Texas.
Figure 6. Land use distribution for high-utility and low-utility with race or ethnicity distribution in Harris County, Texas.
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Figure 7. Frequency distribution of the landscape management score index by household income.
Figure 7. Frequency distribution of the landscape management score index by household income.
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Figure 8. Land management status as indicated by grass mowing and trash removal in Harris County, Texas.
Figure 8. Land management status as indicated by grass mowing and trash removal in Harris County, Texas.
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Figure 9. Land use distribution for high-utility and low-utility land uses based on household income in Harris County, Texas.
Figure 9. Land use distribution for high-utility and low-utility land uses based on household income in Harris County, Texas.
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Figure 10. Frequency distribution of landscape management score index for renter-/owner-occupied housing in Harris County, Texas.
Figure 10. Frequency distribution of landscape management score index for renter-/owner-occupied housing in Harris County, Texas.
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Table 1. Concepts describing landscape characteristics and respective theories used to support the deductive coding structure designed by authors for data analysis.
Table 1. Concepts describing landscape characteristics and respective theories used to support the deductive coding structure designed by authors for data analysis.
Concept CodesTheory References
Land use
(1)
Park
(2)
Detention Basin
(3)
Trails
(4)
Return to Nature
(5)
Vacant lot
(6)
Athletics
(7)
Informal use
(8)
Other
Visual Structure of
Landscape 		(Ode et al. 2008)
Stewardship Natural Environment
(1)
Mowed grass (+1)
(2)
Tall grass (−1)
(3)
Fallen tree limbs (−1)
Built Environment
(1)
Trash (−1)
(2)
Signs (+/−1)
(3)
Cultural Elements (+1)
(4)
Fence (+1)
(5)
Accessibility (+/−1)
(6)
Active management (+1)
(7)
Utilities (−1)
(8)
Violations (−1)
Aesthetics of Care(Nassauer 1995, 1997)
Confidence Level
(1)
High
(2)
Medium
(3)
Low
Intercoder
Reliability 		(O’Connor and Joffe 2020)
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Niazi, S.; Zavar, E.; Greer, A.; Brokopp Binder, S. The Influence of Power on Post-Buyout Land Management Practices. Histories 2025, 5, 14. https://doi.org/10.3390/histories5010014

AMA Style

Niazi S, Zavar E, Greer A, Brokopp Binder S. The Influence of Power on Post-Buyout Land Management Practices. Histories. 2025; 5(1):14. https://doi.org/10.3390/histories5010014

Chicago/Turabian Style

Niazi, Sumaira, Elyse Zavar, Alex Greer, and Sherri Brokopp Binder. 2025. "The Influence of Power on Post-Buyout Land Management Practices" Histories 5, no. 1: 14. https://doi.org/10.3390/histories5010014

APA Style

Niazi, S., Zavar, E., Greer, A., & Brokopp Binder, S. (2025). The Influence of Power on Post-Buyout Land Management Practices. Histories, 5(1), 14. https://doi.org/10.3390/histories5010014

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