Land Use Data Research Articles

CHAIR-consortium: A collaboration for air pollution research across India

Ambient air pollution levels in India are among the highest in the world and contribute to climate change and poor health. Despite extreme levels of air pollution and increased frequency and intensity of heat waves in India, current Indian public policy to reduce emissions has been inadequate and lacked a coordinated and sustained effort. Planned coal power plants will additionally contribute to both more CO2 and air pollution emissions. Moreover, lack of monitoring in rural areas has contributed to a belief that air pollution is only an urban problem. To address this we have developed an exposure assessment methodology employing machine-learning methods and multiple data sources including monitoring data, satellite data, meteorology and land-use data to make reliable high resolution predictions of particulate matter <2.5 µm in diameter (PM2.5) and temperature in areas with sparse monitoring. We will develop a nation-wide exposure model for daily ambient PM2.5 and ambient temperature from 2008-2020 at a spatial resolution of 1 km x 1 km and locally at 200 m x 200 m in India. Our aim is to link our national estimates of PM2.5 and temperature to health data to quantify the associations between PM2.5 and ambient temperature, independently and jointly on major public health endpoints. Our specific intention is to make the exposure model an open resource to accelerate environmental epidemiology and build capacity around the many existing health studies in India to which the exposure model can be applied. We will develop an online interactive environmental database and a strategy for stakeholder communication to significantly facilitate decision-making and increase public awareness and engagement. Successful fulfillment of our aims in India will significantly contribute to sustainable development benefitting not only the very large Indian population but also the global community.

Changes in urban green spaces’ value perception: A meta-analytic benefit transfer function for European cities

We estimate a meta-regression of the willingness to pay (WTP) for green spaces in European urban and peri-urban areas obtained from contingent valuation (CV) studies to construct a benefit transfer (BT) function. Compared to previous studies that estimated meta-regression for urban green spaces, we introduce two main novelties. Firstly, we focus exclusively on Europe to reduce the heterogeneity due to unobservable factors that affect the estimates and their transferability. Secondly, we use urban socio-economic indicators and land-use data derived from terrestrial observations as proxies for the supply and demand of ecosystem services at the local level, allowing interactions between these variables and the specific characteristics of the site valued. We demonstrate that both approaches improve the accuracy of the estimates and, hence, the validity of the transferred values.

Urban density and spatial planning: The unforeseen impacts of Dutch devolution.

National spatial planning has strongly influenced urban development and open space preservation in the Netherlands since the 1950s and established the country's reputation as a planner's paradise. The gradual withdrawal from this active and stringent type of planning in favour of decentralisation and deregulation has received less attention and its impacts on urban development patterns remain poorly studied. This study investigates residential development since 2000 in relation to the changing planning context. We focused on residential densification and the redevelopment of greyfields and brownfields as desired outcomes of policies that aim to limit urban development in open landscapes. Using detailed spatial housing and land-use data we quantified the relative importance of different urban development processes over three subsequent six-year periods characterised by slowly decreasing national policy attention to steering residential development. Our results indicate that, while the national policy instruments got weaker, the share of residential development within existing urban areas increased. Our results lend further credence to the suggestion that the abandoned national spatial planning policy targeted at housing construction within urban development zones that were predominantly defined on greenfield near existing cities, limited urban redevelopment. Despite reduced government spending, densities increased within existing urban areas as general, local-level restrictive policies with respect to greenfield development remained in place and demand for urban housing remained unabated.

Current and Future Ecological Status Assessment: A New Holistic Approach for Watershed Management

The Paiva River catchment, located in Portugal, integrates the Natura 2000 network of European Union nature protection areas. Resorting to topography, climate and land-use data, a semi-distributed hydrological model (Hydrological Simulation Program–FORTRAN) was run in order to simulate the hydrological cycle of the river and its tributaries. The model was calibrated over a 25-year period and validated within a 31-year period. Its performance was verified by comparing the recorded and simulated daily flows. The values of the Nash–Sutcliffe coefficient of efficiency of 0.95 and 0.76, and coefficient of determination of 0.95 and 0.82, were achieved for calibration and validation, respectively, thus showing a quite satisfactory model performance. Subsequently, the climate change impacts on temperature and precipitation, as well as their extremes, and on the flowrates were also assessed for a future period (2041–2070) under two anthropogenic forcing scenarios (representative concentration pathways 4.5 and 8.5). A procedure for selecting the most relevant metrics for assessing the ecological condition of the Paiva River was developed based upon a set of 52 invertebrate families sampled. Correspondence analyses were carried out for biological datasets (traits/metrics) with physicochemical and land use/land cover matrices separately. Out of all variables, water quality and flow and agriculture land use explained most of the variance observed. The integrated analysis undertaken in the present study is an important advance when compared to previous studies and it provides key information to stakeholders and decision-makers, particularly when planning suitable adaptation measures to cope with changing climates in the forthcoming decades.

Cluster and characteristic analysis of Shanghai metro stations based on metro card and land-use data

ABSTRACT Metro is an important form of public transport in Shanghai. Based on the metro card data, we conduct the cluster analysis of Shanghai metro stations according to the pattern of passenger flow changing with time. Then the characteristics of travel time and surrounding land use are investigated for different types of stations to explore the relationship between urban land-use characteristics and travel activities reflected by passenger flow at metro stations. It is found that the passenger flow pattern of metro stations is closely related to the location conditions of stations and its surrounding land-use patterns. Based on various characteristics, 285 metro stations are classified into four types, including residential-oriented stations, employment-oriented stations, employment-residence-oriented stations, and integrated functional-oriented stations, reflecting the interaction between spontaneous travel behavior and urban land-use characteristics and providing a reference for optimizing the urban functional structure and the spatial allocation of facilities.

Flood Risk Index for Land-Use Changes: Case Study of Pakpanang River Basin

Flood Risk Index (FRI) is the multi-criteria linked with the factors of vulnerability; exposure, susceptibility, and resilience. In order to establish local FRI, crucial local information have to be accumulated. However, under the limitation of land-use data, particular techniques were applied in this study. CA Markov model was used to analyze the past missing land-use data and, also forecast the future land-use of Pakpanang river basin under conditions of plan and without plan. The ratio changes of forest, agriculture, wetland and water, and urban areas were considered. Then, the result of LULC spatial-temporal changes was then applied to Hec-HMS and Hec-Ras , with Arc GIS extension of Hec-GeoHMS and Hec-GeoRas software, in order to evaluate the flood hydrographs and flood severity in three municipalities corresponding to 100-year return period rainfall. Afterward, the FRI of Pakpanang, Chianyai, and Hua-sai, which ranges from 0 to 1, were evaluated by using the modified FRI equations. It was found that sensitivity analysis in the area of forest on flood depth and inundation areas is incoherent. Nevertheless, without land-use planning, the changes in these three cities cause higher flood risk, where Chianyai is the riskiest as the FRIE is 0.58. Further consideration of FRIE and FRIP proportion that reveals the FRI deviation indicates that to reduce flood risk, Chianyai would need the most resources and highest effort comparison to Pakpanang and Hua-sai.

Long-term trends in anthropogenic land use in Siberia and the Russian Far East: a case study synthesis from Landsat

As globally important forested areas situated in a context of dramatic socio-economic changes, Siberia and the Russian Far East (RFE) are important regions to monitor for anthropogenic land-use trends. Therefore, we compiled decadal Landsat-derived land-cover and land-use data for eight dominantly rural case study sites in these regions and focused on trends associated with settlements, agriculture, logging, and roads 1975–2010. Several key spatial–temporal trends emerged from the integrated landscape-scale analyses. First, road building increased in all case study sites over the 35-year period, despite widespread socio-economic decline post-1990. Second, increase in settlements area was negligible over all sites. Third, increased road building, largely of minor roads, was especially high in more rugged and remote RFE case study sites not associated with greater agriculture extent or settlement densities. High demands for wood export coupled with the expansion of commercial timber harvest leases starting in the mid-1990s are likely among leading reasons for an increase in roads. Fourth, although fire was the dominant disturbance over all sites and dates combined, logging exerted a strong land-use pattern, serving as a reminder that considering local anthropogenic landscapes is important, especially in Siberia and the RFE, which represent almost 10% of the Earth’s terrestrial land surface. The paper concludes by identifying remaining research needs regarding anthropogenic land use in the region: more frequent moderate spatial resolution imagery and greater access to more finely resolved statistical and other spatial data will enable further research.Social media abstractLandsat reveals long-term anthropogenic land-use trends in Siberia and Russian Far East

Study of the spatial connection between urbanization and the ecosystem-A case study of Central Yunnan (China).

This study provides new perspectives on urban development and conservation by exploring the spatial interaction between ecosystem services and urbanization. Limited studies have discussed the interaction between ecosystem services and urbanization; therefore, in this research, the spatial relationship between ecosystem services and urbanization is explored by taking the urban agglomeration in Central Yunnan as an example, and land-use data and economic and social data from 2009 and 2018 are used to determine the interactive impact of urbanization on the urban ecosystem. It is shown that (1) the spatial distribution of the urbanization level of the urban agglomeration in Central Yunnan has significant regional differences, showing a decreasing trend from the urbanized area to the surrounding areas. (2) Another factor with obvious regional differences is the spatial distribution of ecosystem services, which is similar to urbanization in spatial distribution. This difference is mainly caused by the impact of the urbanization level and the change in land use. (3) The spatial distribution and local agglomeration of urbanization and the ecosystem service value of urban agglomeration in Central Yunnan are very similar, and there is a significant negative correlation between the urbanization level and ecosystem service value. The research results have guiding significance for future urban and ecological development in Central Yunnan city.

Biogeophysical and biogeochemical impacts of land-use change simulated by MIROC-ES2L

Land-use change is one of the focal processes in Earth system models because it has strong impacts on terrestrial biogeophysical and biogeochemical conditions. However, modeling land-use impacts is still challenging because of model complexity and uncertainty. This study examined the results of simulations of land-use change impacts by the Model for Interdisciplinary Research on Climate, Earth System version 2 for long-term simulations (MIROC-ES2L) conducted under the Land-Use Model Intercomparison Project protocol. In a historical experiment, the model reproduced biogeophysical impacts such as decreasing trends in land-surface net radiation and evapotranspiration by about 1970. Among biogeochemical impacts, the model captured the global decrease of vegetation and soil carbon stocks caused by extensive deforestation. By releasing ecosystem carbon stock to the atmosphere, land-use change shortened the mean residence time of terrestrial carbon and accelerated its turnover rate, especially in low latitudes. Future projections based on Shared Socioeconomic Pathways indicated substantial alteration of land conditions caused primarily by climatic change and secondarily by land-use change. Sensitivity experiments conducted by exchanging land-use data between different future projection baseline experiments showed that, at the global scale, the anticipated extent of land-use conversion would likely play a modest role in the future terrestrial radiation, water, and carbon budgets. Regional investigations revealed that future land use would exert a considerable influence on runoff and vegetation carbon stock. Further model refinement is required to improve its capability to analyze its complicated terrestrial linkages or nexus (e.g., food, bioenergy, and carbon sequestration) to climate-change impacts.

Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators

BackgroundThe rapid and often uncontrolled rural–urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa’s population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam.MethodsOpenly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2–10 years (PfPR2–10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2–10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population.ResultsThe results suggest that the spatial distribution of PfPR2–10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2–10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values.ConclusionsThe outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts.

Adults\u2019 leisure-time physical activity and the neighborhood built environment: a contextual perspective

BackgroundContext-free outcome measures, such as overall leisure-time physical activity (LTPA), are habitually applied to study the neighborhood built environment correlates of physical activity. This cross sectional study identifies and empirically tests potential methodological limitations related to the use of context-free measures and discusses how these may help in the interpretation of inconsistent associations between participation in moderate-to-vigorous LTPA and objectively measured neighborhood-level built environment attributes.MethodsWe employ a public participation geographic information system (PPGIS), an advanced participatory mapping method, to study the spatial distribution of moderate-to-vigorous LTPA among adult urban Finnish residents (n 1322). Secondary sources of GIS land-use and sport facility data were used to disaggregate respondent-mapped LTPA by the behavioral context, such as indoor and outdoor sport facilities, green spaces, and other public open spaces. Associations between the use of the identified LTPA settings and a range of objectively measured neighborhood built environment attributes were studied with multilevel logistic regression models.ResultsDisaggregated by behavioral context, we observed varied and partly opposite built environment correlates for LTPA. The use of indoor and outdoor sport facilities showed no significant associations with their neighborhood availability, but were significantly associated with personal-level attributes. By contrast, participation in LTPA in green and built public open space shared significant associations with access to and availability of neighborhood green space that persisted after controlling for personal-level covariates. Moreover, neighborhood distances up to 1600 m poorly captured participation in moderate-to-vigorous LTPA, as, on average, 40% of visits were located further from home. However, we found the immediate home environment to be an important LTPA setting for the least active participants.ConclusionsThis study demonstrates that LTPA can be a highly heterogeneous measure regarding both the spatial distribution and the environmental correlates of behavioral contexts. The results show that context-free LTPA outcome measures yield inconsistent associations with built environment exposure variables, challenging the applicability of such measures in designing neighborhood-level built environment interventions.

Industrial land expansion in rural China threatens environmental securities

China’s rural industrialization has been a major driver for its rapid economic growth during the recent decades, but its myriad environmental risks are yet to be fully understood. Based on a comprehensive national land-use data set, our study shows that the area of China’s rural industrial land (RIL) quadrupled during 1990–2015, reaching 39338 km2 in 2015, comparable to urbanization in magnitude but with a much greater degree of landscape fragmentation which implies stronger ecological and environmental impacts. About 91% of the protected areas in the central China were within 50 km from rural industrial land, thus exposed to industrial disturbances. Accelerated rural industrial land expansion, particularly in regions under high geo-hazard risks, led to dramatically increased environmental risks, threatening the safety and health of both rural industrial workers and residents. Moreover, negative effects from rural industrial land expansion could partially offset the crop production growth in recent decades. The underprivileged rural population in the west bears a disproportionally large share of the increased environmental risks. China urgently needs to design and implement sustainable policies to restrict and reshape its rural industrialization. This study aims to inspire policy makers and researchers to rethink the current model of industrial expansion and improve rural industrial land planning, which is important for achieving the sustainable development goals of China.

Urban-rural spatial transformation process and influences from the perspective of land use: A case study of the Pearl River Delta Region

The process of rapid urbanization results in the flow and agglomeration of regional production factors, which leads to the transformation of the urban-rural territorial system and changes the spatial patterns of urban and rural areas. On the basis of the dynamic changes about urban and rural construction land, this research focuses on the processes, influencing factors, and driving mechanisms motivating the urban-rural transformation in the Pearl River Delta Region. Vector data of urban construction land use in 1990, 2000, 2005, and 2017, natural elements, socioeconomic data, geostatistical analysis method, and logistic regression model were all utilized to identify the characteristics of the processes and influencing factors. The driving mechanisms of spatial evolution in urban-rural transformation from regional growth, market development, and government controls were also explained according to analytics. The results reveal the following: (1) The spatial agglomeration of urban-rural transformation was highlighted, and a stable “A” regional spatial structure was formed around Guangzhou, Foshan, Zhuhai, Shenzhen, and Dongguan. (2) The urban-rural transformation changed from a high-intensity expansion mode in the core region to a low-intensity expansion mode in the core periphery region. (3) The urban-rural transformation in the east coast of the Pearl River Delta was better than that in the west coast, and the transformation pace of the Pearl River estuary was faster than that of the periphery region. (4) The urban-rural transformation was affected by natural conditions and socioeconomic development, of which traffic location was the most significant factor. (5) The urban-rural spatial variation originated from the combined effects of regional growth forces, market driving forces, and government control forces.

Land-use planning adaptation in response to SLR based on a vulnerability analysis

Low-lying coastal areas are threatened worldwide by global climate change effects, including sea-level rise (SLR) and frequent storm surges. Identifying vulnerable areas and proposing feasible adaptation strategies for future land-use development are particularly important. Using Bay County, Florida, as a case study, this study develops a technical methodology to develop future land-use adaptation strategies in response to SLR and storm surges. We propose a cellular automata (CA) land-use adaptation model that not only minimizes the impacts of SLR and flooding from storm surge events but also captures inherent spatial growth characteristics by integrating a vulnerability assessment with a land suitability analysis. To assess vulnerability, a series of physical, environmental, and socioeconomic indicators for exposure, sensitivity and adaptation have been developed. In the CA land-use adaptation model, transition rules are generated from an integer programming problem that aims to maximize land-use suitability and to minimize the vulnerability of newly developed land cells. The model is calibrated with actual land-use data from 2000 to 2010. The model validation indicates that the predicted land uses effectively capture direction of spatial growth, with a kappa coefficient of 87.9%. In comparison with the results of a standard land-use development model, in this CA adaptation model successfully projects future developments in low vulnerability areas. This model could effectively help in the development of future land-use adaptation strategies to address the impacts of flooding due to SLR and storm surges.

Spatio-Temporal Dynamics of Sediment yield across the Imo River Basin South- East Nigeria

Soil and water are the two main natural resources that sustain human existence on earth. Proper monitoring and maintenance of these resources are done on basin level. The IRB drains an area of 7,951.03 km2. The basin has a mean annual discharge of 120m3/sec and generates significant surface runoff and sediment. The study aim was to evaluate the sediment yield across IRB using the Soil and Water Assessment Tool (SWAT) model. SWAT is a watershed-based, semi-distributed hydrologic model for simulating hydrological processes at different spatial scales. The model utilized digital elevation model DEM to extract the river network, basin delineation, and sub-basin division. The sub-basins were further divided into hydrological response unit HRU at a threshold of 5% slope, 5% the land use and 5% soil. Harmonized soil data and two land-use data of 1995 and 2010 were used to simulate the sediment yield across IRB. The study result shows an increase in sediment yield of 0.73 t/ha from1995 to 2010. Sub-basin 10 has the highest sediment yield during the two periods; September and October are the months with the highest sediment yield.

A NOVEL SELF-TAUGHT LEARNING FRAMEWORK USING SPATIAL PYRAMID MATCHING FOR SCENE CLASSIFICATION

Abstract. Remote sensing earth observation images have a wide range of applications in areas like urban planning, agriculture, environment monitoring, etc. While the industrial world benefits from availability of high resolution earth observation images since recent years, interpreting such images has become more challenging than ever. Among many machine learning based methods that have worked out successfully in remote sensing scene classification, spatial pyramid matching using sparse coding (ScSPM) is a classical model that has achieved promising classification accuracy on many benchmark data sets. ScSPM is a three-stage algorithm, composed of dictionary learning, sparse representation and classification. It is generally believed that in the dictionary learning stage, although unsupervised, one should use the same data set as classification stage to get good results. However, recent studies in transfer learning suggest that it might be a better strategy to train the dictionary on a larger data set different from the one to classify.In our work, we propose an algorithm that combines ScSPM with self-taught learning, a transfer learning framework that trains a dictionary on an unlabeled data set and uses it for multiple classification tasks. In the experiments, we learn the dictionary on Caltech-101 data set, and classify two remote sensing scene image data sets: UC Merced LandUse data set and Changping data set. Experimental results show that the classification accuracy of proposed method is compatible to that of ScSPM. Our work thus provides a new way to reduce resource cost in learning a remote sensing scene image classifier.

Response of resources and environment carrying capacity under the evolution of land use structure in Chongqing Section of the Three Gorges Reservoir Area

In this study, a comprehensive model for suitable carrying capacity of resources and environment was proposed based on ecological footprint method. Using the spatiotemporal distribution data of land use in Chongqing Section of Three Gorges Reservoir Area from 2001 to 2016, the response changes of carrying capacity of resources and environment under the evolution of land use structure were investigated. The analytical results showed that the suitable carrying capacity of resources and environment in Chongqing decreased first and then increased. In the early stage of the Three Gorges Project, some districts and counties exhibited the phenomenon of suitable carrying capacity deficit, especially in the northeast of Chongqing. In the main urban area of Chongqing, the suitable carrying capacity was also mainly restricted by the ecological resources conditions, the deficit was getting worse with the increase of population density. In the later stage, by restoring ecology and improving the living and economic conditions, the phenomenon of deficit was gradually alleviated. These findings will provide some references for the protection of ecological environment and the development of social economy in Chongqing Section of the Three Gorges Reservoir Area.

Dynamic modes and ecological effects of salt field utilization in the Weifang coastal area, China: Implications for territorial spatial planning

Harmonious coexistence between human and nature has been an important prerequisite for territorial spatial planning to construct ecological civilizations. The effective way is essential to quantify dynamic modes of land-use changes and their ecological effects. Taking the coastal area of Weifang, eastern regions in China as a case study area, this paper quantified the spatiotemporal characteristics and ecosystem service value of salt field utilization using the theories and methods of geoscience analysis by using satellite imagery and land-use change survey data. The results showed that the area of salt field utilization first increased and then decreased with an upward trend in spatial separation. In the early study stage, the saline-alkali land was mainly developed into a salt field, following with the salt field into construction land, and the salt field into water. Changes in the utilization of salt fields reduced the value of ecosystem services by 3 million yuan RMB during the study period. Ecological value-added areas and ecological impaired areas were mainly located in economically developed areas such as Dajiawa Subdistrict, Yangzi Subdistrict and Yangkou Town. These results show that changes in the utilization of salt fields have different effects on ecosystem service values in different regions. It is necessary for Weifang to comprehensively control the utilization of salt fields, and to provide a reference for the preparation of territorial spatial planning.

Occurrence of Emerging Pollutants in Skudai River in Johor Bahru Region of Malaysia

Increase in landuse development and human activities have significant influence on the occurrence of emerging pollutants (EPs) in water bodies such as rivers. As rivers are the main source of water supply in Malaysia, a study was conducted to determine the occurrence of EPs in one of the drinking water sources, namely Skudai River. Samples were collected five times at eight sampling points from the upstream up to the water intake of the river. Sample pre-treatment was performed by solid-phase extraction (SPE), whereas the analyses of the EPs were performed by Liquid Chromatography-Mass Spectrometry (LCMS-MS QTOF). Results showed that about 50 compounds were detected and fall into categorise as pharmaceuticals, Personal Care Products (PCPs), and Endocrine Disrupting Chemical (EDC). The most prevalent (75-100%) compounds detected were of these categories, whereas the least (less than 40%) were mainly pharmaceuticals. The concentration of styrene, a health-hazards EPs ranged from 45.11 to 203.48 µg/L with increasing trend towards downstream of the river. Based on the landuse data of Skudai River Basin, the study concluded that human activity, landuse, and environmental factors could possibly contribute to the presence of the EPs in the river.

A 100 m population grid in the CONUS by disaggregating census data with open-source Microsoft building footprints

ABSTRACT In the Big Data era, Earth observation is becoming a complex process integrating physical and social sectors. This study presents an approach to generating a 100 m population grid in the Contiguous United States (CONUS) by disaggregating the US census records using 125 million of building footprints released by Microsoft in 2018. Land-use data from the OpenStreetMap (OSM), a crowdsourcing platform, was applied to trim original footprints by removing the non-residential buildings. After trimming, several metrics of building measurements such as building size and building count in a census tract were used as weighting scenarios, with which a dasymetric model was applied to disaggregate the American Community Survey (ACS) 5-year estimates (2013–2017) into a 100 m population grid product. The results confirm that the OSM trimming process removes non-residential buildings and thus provides a better representation of population distribution within complicated urban fabrics. The building size in the census tract is found in the optimal weighting scenario. The product is 2.5Gb in size containing 800 million populated grids and is currently hosted by ESRI (http://arcg.is/19S4qK) for visualization. The data can be accessed via https://doi.org/10.7910/DVN/DLGP7Y. With the accelerated acquisition of high-resolution spatial data, the product could be easily updated for spatial and temporal continuity.