A Study on the Spatial Distribution Patterns of Urban Green Spaces Using Local Spatial Autocorrelation Statistics
1
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
The primary purpose of this study is to compare and analyze the performance of local spatial autocorrelation techniques in identifying spatial distribution patterns of green spaces. To achieve the objective, this researcher uses satellite image analysis and spatial autocorrelation techniques. The result of the study shows that the LISA cluster map with the spatial outlier cluster is superior to other analytical methods in identifying the spatial distribution pattern of urban green space. This study can contribute to the related fields in that it uses several different research methods than the existing ones. Despite this differentiation and usefulness, this study has limitations in using low-resolution satellite imagery and NDVI among vegetation indices in identifying spatial distribution patterns of green areas. These limitations may be overcome in future studies by using UAV images or by simultaneously using several vegetation indices.
Abstract
The primary purpose of this study is to compare and analyze the performance of local spatial autocorrelation techniques in identifying spatial distribution patterns of green spaces. To achieve the objective, this researcher uses satellite image analysis and spatial autocorrelation techniques. The result of the study shows that the LISA cluster map with the spatial outlier cluster is superior to other analytical methods in identifying the spatial distribution pattern of urban green space. This study can contribute to the related fields in that it uses several different research methods than the existing ones. Despite this differentiation and usefulness, this study has limitations in using low-resolution satellite imagery and NDVI among vegetation indices in identifying spatial distribution patterns of green areas. These limitations may be overcome in future studies by using UAV images or by simultaneously using several vegetation indices.
참고문헌 (67)
- Abelt K, "Green streets : urban green and birth outcomes", International journal of environmental research and public health, 14(7), pp.771~ (2017)
- Anguluri R, "Role of green space in urban planning : Outlook towards smart cities", Urban Forestry & Urban Greening, 25, pp.58~65 (2017)
- Anselin L, "Local indicators of spatial association-LISA", Geographical analysis, 27(2), pp.93~115 (1995)
- Anselin L, "A local indicator of multivariate spatial association : extending Geary’s C", Geographical Analysis, 51(2), pp.133~150 (2019)
- Anselin L, "GeoDa : an introduction to spatial data analysis", Geographical analysis, 38(1), pp.5~22 (2006)
- Avdan U, "Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data", Journal of Sensors (2016)
- Bao S, "Heterogeneity issues in local measurements of spatial association", Geographical Systems, 3, pp.1~14 (1996)
- Bao T, "Assessing the distribution of urban green spaces and its anisotropic cooling distance on urban heat island pattern in Baotou, China", ISPRS International Journal of Geo-Information, 5(2), pp.12~ (2016)
- Baruch-Mordo, "Spatiotemporal distribution of black bear‐human conflicts in Colorado. USA", The Journal of Wildlife Management, 72(8), pp.1853~1862 (2008)
- Bhatti SS, "Built-up area extraction using Landsat 8 OLI imagery", GIScience sensing, 51(4), pp.445~467 (2014)
- Bivand R, "Spatial econometrics functions in R : Classes and methods", Journal of geographical systems, 4(4), pp.405~421 (2002)
- Bivand R, "Implementing spatial data analysis software tools in R", Geographical Analysis, 38(1), pp.23~40 (2006)
- Bivand R, "Applying measures of spatial autocorrelation : computation and simulation", Geographical Analysis, 41(4), pp.375~384 (2009)
- Carlson TN, "On the relation between NDVI. fractional vegetation cover. and leaf area index", Remote sensing of Environment, 62(3), pp.241~252 (1997)
- Cima EG, "Analysis of spatial autocorrelation of grain production and agricultural storage in Parana", Engenharia Agrícola, 38(3), pp.395~402 (2018)
- Dalposso GH, "Spatial autocorrelation of NDVI and GVI indices derived from Landsat", TM images for soybean crops in the western of the state of Paraná in 2004, Engenharia Agrícola, pp.2013 (2005), 33(3)[DOI]
- de México CE, "Spatial modeling of forest fires in Mexico : an integration of two sources", Bosque, 38(3), pp.563~574 (2017)
- Dwyer MC, "Using GIS to assess urban tree canopy benefits and surrounding greenspace distributions", Journal of Arboriculture, 25, pp.102~107 (1999)
- El-Gammal MIARR, "NDVI threshold classification for detecting vegetation cover in Damietta governorate. Egypt", Journal of American Science, 10(8), pp.108~113 (2014)
- Fu WJ, "Using Moran’s I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China", Biogeosciences, 11(8), pp.2401~2409 (2014)
- Gamon JA, "Relationships between NDVI. canopy structure and photosynthesis in three Californian vegetation types", Ecological Applications, 5(1), pp.28~41 (1995)
- Gandhi GM, "NDVI : vegetation change detection using remote sensing and GIS–a case study of Vellore District", Procedia Computer Science, 57, pp.1199~1210 (2015)
- Georgi JN, "The contribution of urban green spaces to the improvement of environment in cities : Case study of Chania. Greece", Building and environment, 45(6), pp.1401~1414 (2010)
- Getis A, "A history of the concept of spatial autocorrelation : A geographer’s perspective", Geographical Analysis, 40(3), pp.297~309 (2008)
- Haaland C, "Challenges and strategies for urban green-space planning in cities undergoing densification : A review", Urban forestry & urban greening, 14(4), pp.760~771 (2015)
- Han TTN, "Understanding Satellite Image-Based Green Space Distribution for Setting up Solutions on Effective Urban Environment Management", Multidisciplinary Digital Publishing Institute Proceedings, 2(10), pp.570~ (2018)
- Hoffimann E, "Socioeconomic inequalities in green space quality and accessibility—Evidence from a Southern European city", International journal of environmental research and public health, 14(8), pp.916~ (2017)
- Jacquez GM, "Spatial analysis in epidemiology:Nascent science or a failure of GIS?", Journal of Geographical Systems, 2(1), pp.91~97 (2000)
- Jennings V, "Advancing sustainability through urban green space:Cultural ecosystem services. equity. and social determinants of health", International Journal of environmental research and public health, 13(2), pp.196~ (2016)
- Keller W, "The origin of spatial interaction", Journal of Econometrics, 140(1), pp.304~332 (2007)
- Kong F, "Urban green space network development for biodiversity conservation: Identification based on graph theory and gravity modeling", Landscape and urban planning, 95(1-2), pp.16~27 (2010)
- Kosfeld R, "Identifying clusters within R&D intensive industries using local spatial methods", ~ (2012)
- Lee SI, "Developing a bivariate spatial association measure: an integration of Pearson’s r and Moran’s I", Journal of geographical systems, 3(4), pp.369~385 (2001)
- Le Gallo J, "Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe 1980–1995", Papers in regional science, 82(2), pp.175~201 (2003)
- Leung Y, "Statistical test for local patterns of spatial association", Environment and Planning A, 35(4), pp.725~744 (2003)
- Levine N, "Hot spot analysis of zones. N Levine. CrimeStat: Spatial Statistics Program for the Analysis of Crime Incident Locations. Version. 4 242960-242995", ~ (2013)
- Lwin K, "A GIS Approach to Estimation of Building Population for Microspatial Analysis", Transactions in GIS, 13(4), pp.401~414 (2009)
- Machiwal D, "Modeling short-term spatial and temporal variability of groundwater level using geostatistics and GIS", Natural resources research, 21(1), pp.117~136 (2012)
- Maimaitiyiming M, "Effects of green space spatial pattern on land surface temperature : Implications for sustainable urban planning and climate change adaptation", ISPRS Journal of Photogrammetry and Remote Sensing, 89, pp.59~66 (2014)
- Majumdar DD, "Quantifying land surface temperature change from LISA clusters : An alternative approach to identifying urban land use transformation", Landscape and Urban Planning, 153, pp.51~65 (2016)
- McCauley LA, "GIS‐based estimates of former and current depressional wetlands in an agricultural landscape", Ecological Applications, 15(4), pp.1199~1208 (2005)
- McConnachie MM, "Public green space inequality in small towns in South Africa", Habitat International, 34(2), pp.244~248 (2010)
- M’Ikiugu MM, "Urban green space analysis and identification of its potential expansion areas", Procedia-Social and Behavioral Sciences, 35, pp.449~458 (2012)
- Myint SW, "Employing spatial metrics in urban land-use", land-cover mapping, 2007, pp.73(12), 1403~1415
- Noce S, "Hot spot maps of forest presence in the Mediterranean basin", iForest-Biogeosciences and Forestry, 9(5), pp.766~ (2016)
- Ord JK, "Local spatial autocorrelation statistics : distributional issues and an application", Geographical analysis, 27(4), pp.286~306 (1995)
- Orner I, "Investigating fine-scale residential segregation by means of local spatial statistics", Geography Research Forum, 22, pp.41~60 (2002)
- Peng L, "DISTRIBUTION OF MANGROVE SPECIES", Scientia Silvae Sinicae, 4 (1987)
- Pernas JB, "Modelling spatial patterns and temporal trends of wildfires in Galicia (NW Spain)", Forest Systems, 24(2), pp.1~ (2015)
- Pettorelli N, "Using the satellite-derived NDVI to assess ecological responses to environmental change", Trends in ecology & evolution, 20(9), pp.503~510 (2005)
- Rouse Jr J, "Monitoring vegetation systems in the Great Plains with ERTS", ~ (1974)
- Shackleton S, "Multiple benefits and values of trees in urban landscapes in two towns in northern South Africa", Landscape and Urban Planning, 136, pp.76~86 (2015)
- Sokal RR, "Local spatial autocorrelation in a biological model", Geographical Analysis, 30(4), pp.331~354 (1998)
- Tian Y, "Landscape ecological assessment of green space fragmentation in Hong Kong", Urban Forestry &Urban Greening, 10(2), pp.79~86 (2011)
- Tiefelsdorf M, "The saddlepoint approximation of Moran’s I’s and local Moran’s Ii’s reference distributions and their numerical evaluation", Geographical Analysis, 34(3), pp.187~206 (2002)
- Truong LT, "Using GIS to identify pedestrian-vehicle crash hot spots and unsafe bus stops", Journal of Public Transportation, 14(1), pp.6~ (2011)
- Tsai PJ, "Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006", BMC Public Health, 9(1), pp.464~ (2009)
- Tucker CJ, "An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data", International Journal of Remote Sensing, 26(20), pp.4485~4498 (2005)
- Waldhör T, "The spatial autocorrelation coefficient Moran’s I under Heteroscedasticity", Statistics in Medicine, 15(7-9), pp.887~892 (1996)
- Wang J, "Spatial patterns of urban green infrastructure for equity : A novel exploration", Journal of Cleaner Production, 238, pp.117858~ (2019)
- Wang WC, "An Application of the Spatial Autocorrelation Method on the Change of Real Estate Prices in Taitung City", ISPRS International Journal of Geo-Information, 8(6), pp.249~ (2019)
- Wen M, "Spatial disparities in the distribution of parks and green spaces in the USA", Annals of Behavioral Medicine, 45(suppl_1), pp.S18~S27 (2013)
- Wüstemann H, "Access to urban green space and environmental inequalities in Germany", Landscape and Urban Planning, 164, pp.124~131 (2017)
- Xu D, "Compare NDVI extracted from Landsat 8 imagery with that from Landsat 7imagery", American Journal of Remote Sensing, 2(2), pp.10~14 (2014)
- You J, "A GISbased traffic analysis zone design : implementation and evaluation", Transportation Planning and Technology, 21(1-2), pp.69~91 (1998)
- Zhang H, "Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River", IOP Conference Series : Earth and Environmental Science, 108(3), pp.032058~ (2018), IOP Publishing
- Zhou X, "Social benefits of urban green space: A conceptual framework of valuation and accessibility measurements" (2012), Management of Environmental Quality
