Chart and table of population level and growth rate for the Houston metro area from 1950 to 2025.

In 2017, Hurricane Harvey caused substantial loss of life and property in the swiftly urbanizing region of Houston, TX. Now in its wake, researchers are tasked with investigating how to plan for and mitigate the impact of similar events in the future, despite expectations of increased storm intensity and frequency as well as accelerating urbanization trends. Critical to this task is the development of automated workflows for producing accurate and consistent land cover maps of sufficiently fine spatio-temporal resolution over large areas and long timespans. In this study, we developed an innovative automated classification algorithm that overcomes some of the traditional trade-offs between fine spatio-temporal resolution and extent – to produce a multi-scene, 30m annual land cover time series characterizing 21 years of land cover dynamics in the 35,000 km2 Greater Houston area. The ensemble algorithm takes advantage of the synergistic value of employing all acceptable Landsat imagery in a given year, using aggregate votes from the posterior predictive distributions of multiple image composites to mitigate against misclassifications in any one image, and fill gaps due to missing and contaminated data, such as those from clouds and cloud shadows. The procedure is fully automated, combining adaptive signature generalization and spatio-temporal stabilization for consistency across sensors and scenes. The land cover time series is validated using independent, multi-temporal fine-resolution imagery, achieving crisp overall accuracies between 78–86% and fuzzy overall accuracies between 91–94%. Validated maps and corresponding areal cover estimates corroborate what census and economic data from the Greater Houston area likewise indicate: rapid growth from 1997–2017, demonstrated by the conversion of 2,040 km2 (± 400 km2) to developed land cover, 14% of which resulted from the conversion of wetlands. Beyond its implications for urbanization trends in Greater Houston, this study demonstrates the potential for automated approaches to quantifying large extent, fine resolution land cover change, as well as the added value of temporally-dense time series for characterizing higher-order spatio-temporal dynamics of land cover, including periodicity, abrupt transitions, and time lags from underlying demographic and socio-economic trends.

The Houston data center market is experiencing robust growth, driven by the city's burgeoning energy sector, expanding technology footprint, and strategic location within a major US economic hub. The market, exhibiting a Compound Annual Growth Rate (CAGR) of 4.70%, is projected to reach significant scale in the coming years. While the exact 2025 market size (XX) isn't provided, considering similar markets and the 4.70% CAGR, a reasonable estimation for the 2025 market value would place it in the range of $250 million to $350 million USD. This valuation accounts for factors like increasing cloud adoption, the rise of edge computing necessitating localized data storage, and the robust demand from hyperscale providers seeking strategic locations. The forecast period from 2025-2033 suggests continued expansion, with potential market sizes reaching well over $500 million USD by 2033, depending on sustained economic growth and infrastructure investments. Key drivers include the strong presence of energy companies requiring substantial data processing capabilities, the expanding financial technology sector, and the increasing need for low-latency data processing to support emerging technologies like IoT and AI. Trends such as hyperscale data center development, the growing adoption of colocation services, and the increasing focus on sustainable and energy-efficient data center infrastructure are further shaping the market. While potential restraints exist such as competition for skilled labor and land availability, the overall growth trajectory for the Houston data center market remains positive, supported by the region's economic strengths and strategic importance. This continued growth makes the Houston data center market an attractive investment opportunity for both established players and new entrants. Key drivers for this market are: Growing Adoption of Cloud Services is expected to flourish the market, Increasing Growth in Wholesale Datacenter Multi-tenant Spaces to propel demand (albeit from a lower base); Increased Emphasis on Compliance with Data Regulations and Cost-Effective Nature of Multi-tenant Facilities to Drive Adoption among SME's. Potential restraints include: Dependence on Regulatory Landscape & Stringent Security Requirements. Notable trends are: High Adoption Of Hyperscale Data Center.

United States - Real Gross Domestic Product Growth: Private Services-Providing Industries in Houston County, TX was 19630.97000 % Chg. from Preceding Period in June of 2025, according to the United States Federal Reserve. Historically, United States - Real Gross Domestic Product Growth: Private Services-Providing Industries in Houston County, TX reached a record high of 20173.89000 in December of 2024 and a record low of 54.87000 in October of 1974. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Real Gross Domestic Product Growth: Private Services-Providing Industries in Houston County, TX - last updated from the United States Federal Reserve on July of 2025.

The Houston data center market is experiencing robust growth, driven by the city's burgeoning energy sector, robust financial services industry, and expanding technological infrastructure. A significant factor contributing to this expansion is the increasing demand for cloud computing, edge computing, and colocation services from various end-users including cloud providers, IT companies, and enterprises across sectors like energy, finance, and media. The market is segmented by data center size (small, medium, large, massive, mega), tier type (Tier 1 & 2, Tier 3, Tier 4), and absorption (utilized – further broken down by colocation type (retail, wholesale, hyperscale) and end-user (cloud & IT, information technology, media & entertainment, government, BFSI, manufacturing, e-commerce, other) – and non-utilized). While precise market sizing for Houston specifically is unavailable, given the national CAGR of 4.70% and the strong economic drivers within the city, a conservative estimate would place the 2025 Houston market size in the range of $500 million to $750 million, considering the substantial investments in data center infrastructure. This figure reflects the significant demand within the region and its position as a major hub in the southern United States. The growth trajectory is expected to continue over the forecast period (2025-2033), fueled by increasing digital transformation initiatives across industries and the rising adoption of advanced technologies. However, potential restraints include the availability of skilled labor, power costs, and land constraints within the city limits. Despite these challenges, the long-term outlook for the Houston data center market remains positive, with strategic investments in infrastructure and supportive government policies further stimulating growth. Competition among major players such as Digital Realty Trust Inc, Equinix Inc, and others will intensify, pushing innovation and improved service offerings to cater to the diverse requirements of the expanding Houston market. Regional variations within the Houston area itself, including access to fiber optics and power grids, will further shape the competitive landscape and distribution of data center facilities. Recent developments include: May 2024 - Two multinational corporations have announced a new collaboration to create energy-efficient and sustainable solutions for data centers as the market experiences significant growth. ExxonMobil and Intel are working to design, test, research and develop new liquid cooling technologies to optimize data center performance and help customers meet their sustainability goals. Liquid cooling solutions serve as an alternative to traditional air-cooling methods in data centers., May 2023 - Netrality Data Centers, the biggest privately-owned company of essential interconnection facilities in the U.S., revealed the growth of its Houston data center located at 1301 Fannin Street. The new expansion includes two additional data halls covering 17,000 square feet and offering more than 2.5 megawatts of critical capacity.. Notable trends are: High Adoption Of Hyperscale Data Center.

Graph and download economic data for All-Transactions House Price Index for Houston-The Woodlands-Sugar Land, TX (MSA) (ATNHPIUS26420Q) from Q1 1976 to Q1 2025 about Houston, appraisers, HPI, TX, housing, price index, indexes, price, and USA.

Culex quinquefasciatus is mosquito species of significant public health importance due to its ability to transmit multiple pathogens that can cause mosquito-borne diseases, such as West Nile fever and St. Louis encephalitis. In Harris County, Texas, Cx. quinquefasciatus is a common vector species and is subjected to insecticide-based management by the Harris County Public Health Department. However, insecticide resistance in mosquitoes has increased rapidly worldwide and raises concerns about maintaining the effectiveness of vector control approaches. This concern is highly relevant in Texas, with its humid subtropical climate along the Gulf Coast that provides suitable habitat for Cx. quinquefasciatus and other mosquito species that are known disease vectors. Therefore, there is an urgent and ongoing need to monitor the effectiveness of current vector control programs. In this study, we evaluated the impact of vector control approaches by estimating the effective population size of Cx. quinquefasciatus in Harris County. We applied Approximate Bayesian Computation to microsatellite data to estimate effective population size. We collected Cx. quinquefasciatus samples from two mosquito control operation areas, 415 and 802, during routine vector monitoring in 2016 and 2017. No county mosquito control operations were applied at area 415 in 2016 and 2017, whereas extensive adulticide spraying operations were in effect at area 802 during the summer of 2016. We collected data for eighteen microsatellite markers for 713 and 723 mosquitoes at eight timepoints from 2016 to 2017 in areas 415 and 802, respectively. We also investigated the impact of Hurricane Harvey's landfall in the Houston area in August of 2017 on Cx. quinquefasciatus population fluctuation. Although we did not detect significant effects of vector control interventions, we found considerable influences of the winter season and a major hurricane on the effective population size of Cx. quinquefasciatus. The fluctuations in effective population size in both areas showed a significant seasonal pattern. Additionally, the significant population expansion following Hurricane Harvey in 2017 supports the necessity for post-hurricane vector-control interventions. Methods Mosquito collection Adult Cx. quinquefasciatus are routinely collected by Harris County Public Health (HCPH) personnel from Houston, Texas, United States. The samples used in this study were collected four times per year in 2016 and 2017 from two operational areas, 415 and 802. Samples from a single time point were collected within a one week time frame. Mosquitoes were stored at −80 ℃ until processing. There were no mosquito control operations by HCPH in area 415 during 2016 and 2017. In contrast, 26 malathion spraying operations were performed on ten separate dates, and ten permethrin spraying operations were performed on five separate dates during the summer of 2016 at area 802. Neither site was subjected to adulticidal spraying in 2017. From area 415, mosquito samples collected in weeks 14, 23, 38, and 46 in 2016 and in weeks 2, 20, 32, and 42 in 2017 were included in this study. From area 802, mosquito samples collected in weeks 14, 23, 39, and 48 in 2016 and in weeks 12, 20, 31, and 42 in 2017 were included. DNA extraction For each timepoint and location, 95 individuals were included. Total DNA was extracted and purified from each individual mosquito. The whole mosquito body was homogenized using a Qiagen® TissueLyser (Qiagen, Germantown, Maryland). Mosquito tissues were individually transferred into a well of a 96-well plate, which included a negative control. DNA extraction and purification were performed on the BioSprint® 96 workstation (Qiagen, Hilden, Germany) following their standard protocol. The final DNA product was stored at 4 ℃. Species diagnostic Morphological species identification was conducted by personnel from HCPH as the primary filtering for the field-collected adult Cx. quinquefasciatus. To confirm the result of morphological identification, species diagnostic polymerase chain reaction (PCR) was performed on each sample (Crabtree et al., 1995), using the PQ10 and the CP16 primers. Each 20 µL reaction included 10 µL 2× Thermo Scientific™ PCR Master Mix (Thermo Fisher Scientific, Carlsbad, California), 10 ng PQ10 primer, 10 ng CP16 primer, 20 ng template DNA, and nuclease-free water. The PCR program was set up following protocol by Crabtree et al. (1995) and was performed on the Eppendorf™ Mastercycler X50a thermocycler (Eppendorf, Hamburg, Germany). PCR products were visualized on a 2% agarose gel. Those samples that failed to show a clear 698-bp band were not used for microsatellite genotyping and data analysis in the following steps. Microsatellite Genotyping Eighteen microsatellite loci for Cx. quinquefasciatus (Fonseca et al., 2004, Smith et al., 2005, Edillo et al., 2007, Hickner et al., 2010) were amplified in multiplex PCR reactions. The forward primers were labeled using one of three fluorescent dyes, FAM, HEX and NED. Primers for six loci were multiplexed in a single reaction, with each primer in equimolar concentrations of 0.2 µM. Each 50 µL amplification reaction included 25 µL 2× QIAGEN® Multiplex PCR Master Mix, 5 µL 10× Primer Mix, 20ng DNA and nuclease-free water (with 3mM MgCl2 in final concentration). The thermoprofile for the multiplex PCR was: 2 min at 95 ℃, followed by 30 cycles performed for 30 sec at 95 ℃; 90 sec at 57 ℃; and 30 sec at 72 ℃, and a final cycle for 30 min at 72 ℃. The PCR products were submitted to the DNA Analysis Facility on Science Hill at Yale University for fragment analyses. Genotyping was performed using Genemarker (Hulce et al., 2011). Data Analysis Microchecker version 2.2.3 was used to check for microsatellite null alleles (Van Oosterhout et al., 2004). Loci CX4, CX10, and CX11 were not included in subsequent analyses, as null alleles were detected in these three loci. Due to low amplification efficiency, data of CX5 from area 802 was also not included in downstream analysis. Microsatellite genotyping data were converted to Genepop format with GenAlEx version 6.503 (Peakall and Smouse, 2012). Data were loaded into DIYabc version 2.1.0 (Cornuet et al., 2014). This software package implements approximate Bayesian computation inferences about population history (Cornuet et al., 2014). We tested four basic demographic scenarios in our study, which included variations of population size (bottleneck, expansion, decline, or constant)for two time periods. For each scenario, 2,000,000 simulated datasets were generated, with specific mutation models and prior distributions for parameters. The summary statistics of each simulated dataset were compared with those of the observed dataset. More specifically, we used three single-sample statistics, including the mean number of alleles, mean genetic diversity (Nei, 1987), mean allele size variance across loci, and three two-sample statistics, including the fixation index (FST) (Weir and Cockerham, 1984), mean index of classification (Rannala and Mountain, 1997, Pascual et al., 2007), and Euclidean distance between every two samples (Goldstein et al., 1995). Through this process, the posterior probability of each scenario was calculated, and the most likely scenario was identified. The effective population size of Cx. quinquefasciatus from each site of the Houston area was obtained by estimating the posterior distribution for the most likely scenario. We set two weeks as the average generation time of Cx. quinquefasciatus, as the life cycle from egg to adult stage usually takes 10 to 14 days (Manimegalai and Sukanya, 2014). The minimum value for effective population size (Ne) was set as 0 and the maximum value for 1,000,000, except for the bottleneck scenario. The prior range for Ne at earlier time points was between 0 and 1,000,000, while the prior range of Ne at the latter time points was between 0 and 200,000 for the bottleneck scenario. We tested three time points from spring in 2016 to winter in 2017 per area to find the effects of the winter season. Genotyping data from weeks 14 and 23 in 2016 and week 2 in 2017 were used for area 415, while genotyping data from weeks 14 and 23 in 2016 and week 12 in 2017 were used for analysis for area 802. First, we performed the parameter estimation with a prior normal distribution, where parameters had a mean value and a standard deviation within a range between extremum values (minimum and maximum). We also performed the parameter estimation with a uniform prior distribution to test if different prior distributions affect the choice of best demographic scenario. In this case, the prior distribution had minimum and maximum values but without the mean value and standard deviation. Next, we performed Ne estimation from three time points from 2016 and three timepoints from 2017 at area 802 to evaluate the effects of Hurricane Harvey on the Ne of the mosquito population. The mosquito samples were collected before and after Hurricane Harvey, which landed in the Houston area on August 27, 2017. For area 802, genotyping data from weeks 14, 23, and 48 in 2016 were used for pre-hurricane analysis in DIYabc, while genotyping data from weeks 12, 20, and 42 in 2017 were used for post-hurricane analysis. In addition to DIYabc, we used NeEstimator version 2.1 (Do et al., 2014) to estimate the Ne of Cx. quinquefasciatus from eight sampling time points in 2016 and 2017 at area 802 to further explore the impact of Hurricane Harvey on the Ne of mosquito population in Harris County. The Ne at each time point was estimated with the Linkage Disequilibrium (LD) method. The mating system was defined as random mating.

This statistic provides projected figures for the Gross Metropolitan Product (GMP) of the United States in 2021, by metropolitan area. Only the 100 leading metropolitan areas are shown here. In 2022, the GMP of the New York-Newark-Jersey City metro area is projected to be around of about **** trillion U.S. dollars. Los Angeles metropolitan areaA metropolitan area in the U.S. is characterized by a relatively high population density and close economic ties through the area, albeit, without the legal incorporation that is found within cities. The Gross Metropolitan Product is measured by the Bureau of Economic Analysis under the U.S. Department of Commerce and includes only metropolitan areas. The GMP of the Los Angeles-Long Beach-Anaheim metropolitan area located in California is projected to be among the highest in the United States in 2021, amounting to *** trillion U.S. dollars. The Houston-The Woodlands-Sugar Land, Texas metro area is estimated to be approximately *** billion U.S. dollars in the same year. The Los Angeles metro area had one of the largest populations in the country, totaling ****** million people in 2021. The Greater Los Angeles region has one of the largest economies in the world and is the U.S. headquarters of many international car manufacturers including Honda, Mazda, and Hyundai. Its entertainment industry has generated plenty of tourism and includes world famous beaches, shopping, motion picture studios, and amusement parks. The Hollywood district is known as the “movie capital of the U.S.” and has its historical roots in the country’s film industry. Its port, the Port of Los Angeles and the Port of Long Beach are aggregately one of the world’s busiest ports. The Port of Los Angelesgenerated some ****** million U.S. dollars in revenue in 2019.