GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Comparison of Twelve Machine Learning Regression Methods for Spatial Decomposition of Demographic Data Using Multisource Geospatial Data: An Experiment in Guangzhou City, China
    MDPI AG ; 2021
    In:  Applied Sciences Vol. 11, No. 20 ( 2021-10-11), p. 9424-
    Details
    In: Applied Sciences, MDPI AG, Vol. 11, No. 20 ( 2021-10-11), p. 9424-
    Abstract: The spatial decomposition of demographic data at a fine resolution is a classic and crucial problem in the field of geographical information science. The main objective of this study was to compare twelve well-known machine learning regression algorithms for the spatial decomposition of demographic data with multisource geospatial data. Grid search and cross-validation methods were used to ensure that the optimal model parameters were obtained. The results showed that all the global regression algorithms used in the study exhibited acceptable results, besides the ordinary least squares (OLS) algorithm. In addition, the regularization method and the subsetting method were both useful for alleviating overfitting in the OLS model, and the former was better than the latter. The more competitive performance of the nonlinear regression algorithms than the linear regression algorithms implies that the relationship between population density and influence factors is likely to be non-linear. Among the global regression algorithms used in the study, the best results were achieved by the k-nearest neighbors (KNN) regression algorithm. In addition, it was found that multi-sources geospatial data can improve the accuracy of spatial decomposition results significantly, and thus the proposed method in our study can be applied to the study of spatial decomposition in other areas.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app11209424
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704225-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Evolution and Simulation of Terrestrial Ecosystem Carbon Storage and Sustainability Assessment in Karst Areas: A Case Study of Guizhou Province
    MDPI AG ; 2022
    In:  International Journal of Environmental Research and Public Health Vol. 19, No. 23 ( 2022-12-04), p. 16219-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 23 ( 2022-12-04), p. 16219-
    Abstract: Against the background of “carbon neutrality” and sustainable development goals, it is of great significance to assess the carbon storage changes and sustainability of terrestrial ecosystems in order to maintain the coordinated sustainable development of regional ecological economies and the balance of terrestrial ecosystems. In this study, the terrestrial ecosystem carbon storage in Guizhou from 2010 to 2020 was assessed with the InVEST model. Using the PLUS model, the distribution of terrestrial ecosystem carbon storage by 2030 and 2050 was predicted. The current sustainable development level of the terrestrial ecosystem of Guizhou was evaluated after establishing an index system based on SDGs. The results showed the following: (1) From 2010 to 2020, the terrestrial ecosystem carbon storage decreased by 1106.68 × 104 Mg. The area and carbon storage of the forest and farmland ecosystems decreased while the area and carbon storage of the grassland and settlement ecosystems increased. (2) Compared with 2020, the terrestrial ecosystem carbon storage will be reduced by 4091.43 × 104 Mg by 2030. Compared with 2030, the terrestrial ecosystem carbon storage will continue to decrease by 3833.25 × 104 Mg by 2050. (3) In 2020, the average score of the sustainable development of the terrestrial ecosystem was 0.4300. Zunyi City had the highest sustainable development score of 0.6255, and Anshun had the lowest sustainable development score of 0.3236. Overall, the sustainable development of the terrestrial ecosystem of Guizhou was found to be high in the north, low in the south, high in the east, and low in the west. The sustainable regional development of the terrestrial ecosystem of Guizhou was found to be unbalanced, and the carbon storage of the terrestrial ecosystem will keep decreasing in the future. In order to improve the sustainable development capacity of the terrestrial ecosystem, the government needs to take certain measures, such as returning farmland to forests and grasslands, curbing soil erosion, and actively supervising.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph192316219
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    Exploring the Multiscale Relationship between the Built Environment and the Metro-Oriented Dockless Bike-Sharing Usage
    MDPI AG ; 2022
    In:  International Journal of Environmental Research and Public Health Vol. 19, No. 4 ( 2022-02-17), p. 2323-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 4 ( 2022-02-17), p. 2323-
    Abstract: Dockless bike-sharing systems have become one of the important transport methods for urban residents as they can effectively expand the metro’s service area. We applied the ordinary least square (OLS) model, the geographically weighted regression (GWR) model and the multiscale geographically weighted regression (MGWR) model to capture the spatial relationship between the urban built environment and the usage of bike-sharing connected to the metro. A case study in Beijing, China, was conducted. The empirical result demonstrates that the MGWR model can explain the varieties of spatial relationship more precisely than the OLS model and the GWR model. The result also shows that, among the proposed built environment factors, the integrated usage of bike-sharing and metro is mainly affected by the distance to central business district (CBD), the Hotels-Residences points of interest (POI) density, and the road density. It is noteworthy that the effect of population density on dockless bike-sharing usage is only significant at weekends. In addition, the effects of the built environment variables on dockless bike-sharing usage also vary across space. A common feature is that most of the built environment factors have a more obvious impact on the metro-oriented dockless bike-sharing usage in the eastern part of the study area. This finding can provide support for governments and urban planners to efficiently develop a bike-sharing-friendly built environment that promotes the integration of bike-sharing and metro.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph19042323
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    Kaolin in the net-like horizon of laterite in Hubei, south China
    Mineralogical Society ; 2009
    In:  Clay Minerals Vol. 44, No. 1 ( 2009-03), p. 51-66
    Details
    In: Clay Minerals, Mineralogical Society, Vol. 44, No. 1 ( 2009-03), p. 51-66
    Abstract: The clay mineralogy and chemical composition of the white veins, red matrix and both Fe- and Mn-bearing nodules occurring in a laterite profile in Hubei, south China were investigated using X-ray diffraction, scanning electron microscopy equipped with an energy-dispersive spectrometer, and high-resolution transmission electron microscopy. The results show that the mineral components of the red matrix are mainly quartz, kaolinite, halloysite, goethite and minor illite, whereas the white net-like veins contain mostly quartz, kaolinite, halloysite, and illite. In the net-like horizon, the chemical index of alteration (CIA, the ratio of Al 2 O 3 /(Al 2 O 3 +CaO+K 2 O+Na 2 O)) and the TiO 2 /Al 2 O 3 ratio are 89.8% and 0.021 for the white vein and 90.7% and 0.025 for the red matrix, respectively. Both white-vein and red-matrix components have similar TiO 2 /Al 2 O 3 ratios, and are similar to the ratio 0.027 of the unaltered bedrock. The similarity in TiO 2 /Al 2 O 3 values indicates that all three portions of the laterite soil share the same origin. Also, although the white-vein and red-matrix components differ in Fe 2 O 3 abundance, the similar CIA values do imply similar degrees of alteration. The Fe-bearing and Mn-bearing nodules were produced by the local accumulation of Fe 2 O 3 and MnO, respectively. Halloysite in the weathering profile occurs in two different morphologies, tubular and platy crystals. Tubular halloysite occurs both in the red matrix and the Fe-bearing nodule whereas platy halloysite occurs only in the white vein and Mn-bearing nodule assemblages. Crystallization of small tubular halloysite from Si and Al concretions in the red matrix is observed, indicating that the morphology of these crystals in the weathering environment is mainly controlled by Fe 3+ cations, whereas platy halloysite may be derived from the hydration of kaolinite.
    Type of Medium: Online Resource
    ISSN: 0009-8558 , 1471-8030
    URL: Article
    DOI: 10.1180/claymin.2009.044.1.51
    RVK:
    TE 1000
    Language: English
    Publisher: Mineralogical Society
    Publication Date: 2009
    detail.hit.zdb_id: 2036186-5
    detail.hit.zdb_id: 961059-5
    SSG: 13
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 5
    Online Resource
    Online Resource
    Urban Population Distribution Mapping with Multisource Geospatial Data Based on Zonal Strategy
    MDPI AG ; 2020
    In:  ISPRS International Journal of Geo-Information Vol. 9, No. 11 ( 2020-10-30), p. 654-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 9, No. 11 ( 2020-10-30), p. 654-
    Abstract: Mapping population distribution at fine resolutions with high accuracy is crucial to urban planning and management. This paper takes Guangzhou city as the study area, illustrates the gridded population distribution map by using machine learning methods based on zoning strategy with multisource geospatial data such as night light remote sensing data, point of interest data, land use data, and so on. The street-level accuracy evaluation results show that the proposed approach achieved good overall accuracy, with determinant coefficient (R2) being 0.713 and root mean square error (RMSE) being 5512.9. Meanwhile, the goodness of fit for single linear regression (LR) model and random forest (RF) regression model are 0.0039 and 0.605, respectively. For dense area, the accuracy of the random forest model is better than the linear regression model, while for sparse area, the accuracy of the linear regression model is better than the random forest model. The results indicated that the proposed method has great potential in fine-scale population mapping. Therefore, it is advised that the zonal modeling strategy should be the primary choice for solving regional differences in the population distribution mapping research.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi9110654
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2655790-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 6
    Online Resource
    Online Resource
    Revealing Taxi Interaction Network of Urban Functional Area Units in Shenzhen, China
    MDPI AG ; 2022
    In:  ISPRS International Journal of Geo-Information Vol. 11, No. 7 ( 2022-07-07), p. 377-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 11, No. 7 ( 2022-07-07), p. 377-
    Abstract: Characterizing the taxi travel network is of fundamental importance to our understanding of urban mobility, and could provide intellectual support for urban planning, traffic congestion, and even the spread of diseases. However, the research on the interaction network between urban functional area (UFA) units are limited and worthy of notice. Therefore, this study has applied the taxi big data to construct a travel flow network for the exploration of spatial interaction relationships between different UFA units in Shenzhen, China. Our results suggested that taxi travel behavior was more active in UFA units dominated by functions, including residential, commercial, scenic, and greenspace during weekends, while more active in UFA units dominated by industrial function during weekdays. In terms of daily average volume, the characteristics of spatial interaction between the various UFA types during weekdays and weekends were similar. During the morning peak period, the sink areas were mainly distributed in Futian District and Nanshan District, while during the evening peak period, the sink areas were mainly distributed in the southern part of Yantian District, the southwestern part of Longgang District, and the eastern part of Luohu District. The average daily taxi mobility network during weekdays showed a spatial pattern of “dense in the west and north, sparse in the south and east”, exhibiting significant spatial unevenness. Compared with weekdays, the daily taxi mobility network during weekends was more dispersed and the differences in node sizes decreased, indicating that taxi travel destinations were more diverse. The pattern of communities was more consistent with the administrative division during weekdays, indicating that taxi trips are predominantly within the districts. Compared with weekdays, the community pattern of network during weekends was clearly different and more in line with the characteristics of a small world network. The findings can provide a better understanding of urban mobility characteristics in Shenzhen, and provide a reference for urban transportation planning and management.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi11070377
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2655790-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 7
    Online Resource
    Online Resource
    How Does the Urban Built Environment Affect Online Car-Hailing Ridership Intensity among Different Scales?
    MDPI AG ; 2022
    In:  International Journal of Environmental Research and Public Health Vol. 19, No. 9 ( 2022-04-27), p. 5325-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 9 ( 2022-04-27), p. 5325-
    Abstract: Understanding the effect of the urban built environment on online car-hailing ridership is crucial to urban planning. However, how the effects change with the analysis scales are still noteworthy. Therefore, a multiscale exploratory study was conducted in Chengdu, China, by using the stepwise regression selection and three spatial regression models. The main findings are summarized as follows. First, as the grid size increases, the number of built environment factors that have significant effects on trip intensity decrease continuously. Second, the effects of population density and road density are always positive from the 500 m grid to the 3000 m grid. As the analysis scale increases, the effect of proximity to public transportation shifts from inhibitory to facilitation, while the positive effect of land-use mix becomes stronger. Land-use type has both positive and negative effects and shows different characteristics at different scales. Third, the effects of built environment factors on online car-hailing trip intensity show different spatial variability characteristics at different scales. The effect of population density gradually decreases from north to south. The effect of road network density shows circling and wave patterns, with the former at relatively fine scales and the latter at relatively coarse scales. The spatial variation in the effect of land-use mix can only be observed more significantly at a relatively coarse scale. The effect of bus stop density is only obvious at the relatively fine and medium scales and shows a wave-like pattern and a circle-like pattern. The effect of various land-use types shows different spatial patterns at different scales, including wave-like pattern, circle-like pattern, and multi-core-like pattern. The spatial variation in the effects of various land-use factors gradually decrease with the increase in the analysis scale.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph19095325
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 8
    Online Resource
    Online Resource
    Marginal Effects and Spatial Variations of the Impact of the Built Environment on Taxis’ Pollutant Emissions in Chengdu, China
    MDPI AG ; 2022
    In:  International Journal of Environmental Research and Public Health Vol. 19, No. 24 ( 2022-12-16), p. 16962-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 24 ( 2022-12-16), p. 16962-
    Abstract: Understanding the impact of the urban built environment on taxis’ emissions is crucial for sustainable transportation. However, the marginal effects and spatial heterogeneity of this impact is worth noting. To this end, we calculated the taxis’ emissions on weekdays and weekends in Chengdu, China, and investigated the impact of the built environment on taxis’ emissions by applying multi-source data and several spatial regression models. The results showed that the taxis’ daily emissions on weekdays were higher than the emissions on weekends. The time heterogeneity of hourly taxis’ emissions was not significant, while the spatial heterogeneity of taxis’ emissions was significant. Except the HHI, the selected built environment variables both had a significant positive effect on taxis’ emissions on the global scale. There was a marginal effect of some built environment variables on taxis’ emissions, such as the density of bus stops and population density. The former exhibited an inhibitory effect on taxis’ emissions only when it was greater than 9 stops/km2, while the latter showed an inhibitory effect only in the range between 16,000 people/km2 and 22,000 people/km2. There were some spatial variations in the effects of built environment factors on taxis’ emissions, with HHI, road density, and accommodation service facilities density showing the most significant variation. The marginal effect and spatial variation of the impact needs to be considered when developing strategies to reduce taxis’ pollutant emissions.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph192416962
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2175195-X
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...