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Prof. Yuji MURAYAMA
Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Jap

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0 Geography
0 Spatial Analysis
0 Transportation
0 Urban Geography
0 GIS and Remote Sensing

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Geography
Spatial Analysis
Transportation
GIS and Remote Sensing
Urban Geography

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Short Biography

Yuji Murayama is Professor Emeritus of the University of Tsukuba, Japan. He has served as Vice-President of Asian Geographical Association (2019-present), President (2018-20), Chairperson (2016-18) and Director (2010-14) of Association of Japanese Geographers, Member of Science Council of Japan (2005-present), Director of Tokyo Geographical Society (2011-17), IGU Steering Committee Member of Transport Geography Commission (2008-16), Urban Commission (2000-08), and President of GIS Association of Japan (2006-08). Professor Dr. Murayama has acted as Editor-in-Chief of AJG Library: International Perspectives in Geography (2018-present), Associate Editor of Euro-Mediterranean Journal of Environmental Integration (2015-2020), Editor-in-Chief of Tsukuba Geoenvironmental Sciences (2015-19), Editor of Urban Studies Research (2011-17), Editor-in-Chief of Geographical Review of Japan, Ser. B (2006-08), and Editor-in-Chief of Theory and Applications of GIS (2004-06). He has also joined in the editorial board of academic journals including Annals of the National Association of Geographers, India (2020-present), Asian Geographer (2019-present), Remote Sensing (2018-present), Sustainability (2018-present), Computers, Environment and Urban Systems (2015-present), Progress in Earth and Planetary Science (2013-present), Positioning (2010-present), Transactions in GIS (2015-17), Journal of Transport Geography (2001-17), GeoJournal (2001-16), and Urban Geography (2002-12).

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Journal article
Published: 27 August 2021 in ISPRS International Journal of Geo-Information
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The history of modern maps in Japan began with Inoh’s map that was made by surveying the whole of Japan on foot 200 years ago. Inoh’s team investigated coastlines, major roads, and geographical features such as rivers, lakes, temples, forts, village names, etc. The survey was successively conducted ten times from 1800 to 1816. Inoh’s map is known as the first scientific map in Japan using a systematic method. However, the actual survey was conducted only for 75% of the coastlines in Japan and the remaining 25% was drawn by Inoh’s estimation (observation). This study investigated how the non-surveyed (estimated) coastlines were distributed in the map and why the actual survey was not conducted in these non-surveyed coastlines. Using GIS, we overlaid the geometrically corrected Inoh’s map (Digital Inoh’s Map Professional Edition) with the current map published by the Geospatial Information Authority (GSI) of Japan for examining the spatial difference. We found that the non-surveyed coastlines were in places where the practice of actual surveying was topographically difficult because of the limited surveying technology of those days. The analytical result shows that 38.6% of the non-surveyed coastlines were cliffs, 25.7% were rocky beaches, and 6.2% were wetlands and tidal lands (including rice fields and tidal flats).

ACS Style

Yuki Iwai; Yuji Murayama. Geospatial Analysis of the Non-Surveyed (Estimated) Coastlines in Inoh’s Map, 1821. ISPRS International Journal of Geo-Information 2021, 10, 580 .

AMA Style

Yuki Iwai, Yuji Murayama. Geospatial Analysis of the Non-Surveyed (Estimated) Coastlines in Inoh’s Map, 1821. ISPRS International Journal of Geo-Information. 2021; 10 (9):580.

Chicago/Turabian Style

Yuki Iwai; Yuji Murayama. 2021. "Geospatial Analysis of the Non-Surveyed (Estimated) Coastlines in Inoh’s Map, 1821." ISPRS International Journal of Geo-Information 10, no. 9: 580.

Journal article
Published: 15 April 2021 in Remote Sensing
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The rapid and dominant urbanization in Asian cities has fueled concerns regarding the local and global efforts toward urban sustainability. Specifically, South Asian cities have been a topical issue concerning ecological and environmental threats due to their unplanned and haphazard urban development. However, comparative urbanization studies in South Asian cities remain uncommon. Therefore, in this study, we sought to comparatively examine the land use and land cover (LULC) dynamics and to detect the urbanization patterns of four rapidly developing South Asian lowland cities: Mumbai (India), Colombo (Sri Lanka), Karachi (Pakistan), and Dhaka (Bangladesh). Sentinel-2 (10 m) data and various geospatial approaches, including urban–rural gradient and grid-based methods, statistics, and urban landscape metric techniques, were used to facilitate the analysis. The study revealed that Mumbai, Karachi, and Dhaka had larger built-up landscapes compared to Colombo. Mumbai had the highest percentage of green spaces, followed by Colombo. Dhaka and Karachi had relatively small percentages of green spaces. Colombo and Dhaka had more croplands, which consistently increased along the urban–rural gradient compared to Mumbai and Karachi. Karachi showed that the only major land use was built-up, while most of the areas were left as open lands. On the other hand, Colombo’s urban setup was more fragmented than the other three cities. Mumbai and Karachi had larger patches of urban footprints compared to Colombo and Dhaka. Thus, this study provides vital information on the past land utilization priorities in the four cities, and comparatively proffers guidance on certain critical areas of focus for local, regional, and global future sustainable urban planning.

ACS Style

Manjula Ranagalage; Takehiro Morimoto; Matamyo Simwanda; Yuji Murayama. Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data. Remote Sensing 2021, 13, 1531 .

AMA Style

Manjula Ranagalage, Takehiro Morimoto, Matamyo Simwanda, Yuji Murayama. Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data. Remote Sensing. 2021; 13 (8):1531.

Chicago/Turabian Style

Manjula Ranagalage; Takehiro Morimoto; Matamyo Simwanda; Yuji Murayama. 2021. "Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data." Remote Sensing 13, no. 8: 1531.

Journal article
Published: 15 April 2021 in Remote Sensing
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The rapid urbanization worldwide has brought various environmental problems. The urban heat island (UHI) phenomenon is one of the most concerning issues because of its strong relation with daily lives. Water bodies are generally considered a vital resource to relieve the UHI. In this context, it is critical to develop a method for measuring the cooling effect and scale of water bodies in urban areas. In this study, West Lake and Xuanwu Lake, two famous natural inner-city lakes, are selected as the measuring targets. The scatter plot and multiple linear regression model were employed to detect the relationship between the distance to the lake and land surface temperature based on Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Sentinel-2 data. The results show that West Lake and Xuanwu Lake massively reduced the land surface temperature within a few hundred meters (471 m for West Lake and 336 m for Xuanwu Lake) and have potential cooling effects within thousands of meters (2900 m for West Lake and 3700 m for Xuanwu Lake). The results provide insights for urban planners to manage tradeoffs between the large lake design in urban areas and the cooling effect demands.

ACS Style

Yaoyao Zheng; Yao Li; Hao Hou; Yuji Murayama; Ruci Wang; Tangao Hu. Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing. Remote Sensing 2021, 13, 1526 .

AMA Style

Yaoyao Zheng, Yao Li, Hao Hou, Yuji Murayama, Ruci Wang, Tangao Hu. Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing. Remote Sensing. 2021; 13 (8):1526.

Chicago/Turabian Style

Yaoyao Zheng; Yao Li; Hao Hou; Yuji Murayama; Ruci Wang; Tangao Hu. 2021. "Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing." Remote Sensing 13, no. 8: 1526.

Journal article
Published: 05 April 2021 in Remote Sensing
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An urban heat island (UHI) is a significant anthropogenic modification of urban land surfaces, and its geospatial pattern can increase the intensity of the heatwave effects. The complex mechanisms and interactivity of the land surface temperature in urban areas are still being examined. The urban–rural gradient analysis serves as a unique natural opportunity to identify and mitigate ecological worsening. Using Landsat Thematic Mapper (TM), Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data in 2000, 2010, and 2019, we examined the spatial difference in daytime and nighttime LST trends along the urban–rural gradient in Greater Cairo, Egypt. Google Earth Engine (GEE) and machine learning techniques were employed to conduct the spatio-temporal analysis. The analysis results revealed that impervious surfaces (ISs) increased significantly from 564.14 km2 in 2000 to 869.35 km2 in 2019 in Greater Cairo. The size, aggregation, and complexity of patches of ISs, green space (GS), and bare land (BL) showed a strong correlation with the mean LST. The average urban–rural difference in mean LST was −3.59 °C in the daytime and 2.33 °C in the nighttime. In the daytime, Greater Cairo displayed the cool island effect, but in the nighttime, it showed the urban heat island effect. We estimated that dynamic human activities based on the urban structure are causing the spatial difference in the LST distribution between the day and night. The urban–rural gradient analysis indicated that this phenomenon became stronger from 2000 to 2019. Considering the drastic changes in the spatial patterns and the density of IS, GS, and BL, urban planners are urged to take immediate steps to mitigate increasing surface UHI; otherwise, urban dwellers might suffer from the severe effects of heatwaves.

ACS Style

Darshana Athukorala; Yuji Murayama. Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient. Remote Sensing 2021, 13, 1396 .

AMA Style

Darshana Athukorala, Yuji Murayama. Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient. Remote Sensing. 2021; 13 (7):1396.

Chicago/Turabian Style

Darshana Athukorala; Yuji Murayama. 2021. "Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient." Remote Sensing 13, no. 7: 1396.

Editorial
Published: 26 March 2021 in Sustainability
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The international statistics show that the global urban population will increase by up to 68% by 2050

ACS Style

Yuji Murayama; Matamyo Simwanda; Manjula Ranagalage. Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries. Sustainability 2021, 13, 3681 .

AMA Style

Yuji Murayama, Matamyo Simwanda, Manjula Ranagalage. Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries. Sustainability. 2021; 13 (7):3681.

Chicago/Turabian Style

Yuji Murayama; Matamyo Simwanda; Manjula Ranagalage. 2021. "Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries." Sustainability 13, no. 7: 3681.

Journal article
Published: 03 March 2021 in Remote Sensing
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Forecasting scenarios of future intra-urban land-use (intra-urban-LU) expansion can help to curb the historically unplanned urbanization in cities in sub-Saharan Africa (SSA) and promote urban sustainability. In this study, we applied the neural network–Markov model to simulate scenarios of future intra-urban-LU expansion in Lusaka city, Zambia. Data derived from remote sensing (RS) and geographic information system (GIS) techniques including urban-LU maps (from 2000, 2005, 2010, and 2015) and selected driver variables, were used to calibrate and validate the model. We then simulated urban-LU expansion for three scenarios (business as usual/status quo, environmental conservation and protection, and strategic urban planning) to explore alternatives for attaining urban sustainability by 2030. The results revealed that Lusaka had experienced rapid urban expansion dominated by informal settlements. Scenario analysis results suggest that a business-as-usual setup is perilous, as it signals an escalating problem of unplanned settlements. The environmental conservation and protection scenario is insufficient, as most of the green spaces and forests have been depleted. The strategic urban planning scenario has the potential for attaining urban sustainability, as it predicts sufficient control of unplanned settlement expansion and protection of green spaces and forests. The study proffers guidance for strategic policy directions and creating a planning vision.

ACS Style

Matamyo Simwanda; Yuji Murayama; Darius Phiri; Vincent Nyirenda; Manjula Ranagalage. Simulating Scenarios of Future Intra-Urban Land-Use Expansion Based on the Neural Network–Markov Model: A Case Study of Lusaka, Zambia. Remote Sensing 2021, 13, 942 .

AMA Style

Matamyo Simwanda, Yuji Murayama, Darius Phiri, Vincent Nyirenda, Manjula Ranagalage. Simulating Scenarios of Future Intra-Urban Land-Use Expansion Based on the Neural Network–Markov Model: A Case Study of Lusaka, Zambia. Remote Sensing. 2021; 13 (5):942.

Chicago/Turabian Style

Matamyo Simwanda; Yuji Murayama; Darius Phiri; Vincent Nyirenda; Manjula Ranagalage. 2021. "Simulating Scenarios of Future Intra-Urban Land-Use Expansion Based on the Neural Network–Markov Model: A Case Study of Lusaka, Zambia." Remote Sensing 13, no. 5: 942.

Journal article
Published: 08 February 2021 in Remote Sensing
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As one of the most populated metropolitan areas in the world, the Tokyo Metropolitan Area (TMA) has experienced severe climatic modifications and pressure due to densified human activities and urban expansion. The surface urban heat island (SUHI) phenomenon particularly constitutes a significant threat to human comfort and geo-environmental health in TMA. This study aimed to profile the spatial interconnections between land surface temperature (LST) and land cover/use in TMA from 2001 to 2015 using multi-source spatial data. To this end, the thermal gradients between the urban and non-urban fabric areas in TMA were examined by joint analysis of land cover/use and LST. The spatiotemporal aggregation patterns, variations, and movement trajectories of SUHI intensity in TMA were identified and delineated. The spatial relationship between SUHI and the potential driving forces in TMA was clarified using geographically weighted regression (GWR) analysis. The results show that the thermal environment of TMA exhibited a polynucleated spatial structure with multiple thermal island cores. Overall, the magnitude and extent of SUHI in TMA increased and expanded from 2001 to 2015. During that time, SUHIs clustered in the compact residential quarters and redevelopment/renovation areas rather than downtown. The GWR models showed better performance than ordinary least squares (OLS) models, with Adj R2 > 0.9, indicating that the magnitude of SUHI significantly depended on its neighboring geographical setting, including land cover composition and configuration, population size, and terrain. We suggest that UHI mitigation in Tokyo should be focused on alleviating the magnitude of persistent thermal cores and controlling unstable SUHI occurrence based on partitioned or location-specific landscape design. This study’s findings have immense implications for SUHI mitigation in metropolitan areas situated in bay regions.

ACS Style

Fei Liu; Hao Hou; Yuji Murayama. Spatial Interconnections of Land Surface Temperatures with Land Cover/Use: A Case Study of Tokyo. Remote Sensing 2021, 13, 610 .

AMA Style

Fei Liu, Hao Hou, Yuji Murayama. Spatial Interconnections of Land Surface Temperatures with Land Cover/Use: A Case Study of Tokyo. Remote Sensing. 2021; 13 (4):610.

Chicago/Turabian Style

Fei Liu; Hao Hou; Yuji Murayama. 2021. "Spatial Interconnections of Land Surface Temperatures with Land Cover/Use: A Case Study of Tokyo." Remote Sensing 13, no. 4: 610.

Journal article
Published: 18 January 2021 in Remote Sensing
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Urban wetland ecosystems (UWEs) play important social and ecological roles but are often adversely affected by urban landscape transformations. Spatio-temporal analyses to gain insights into the trajectories of landscape changes in these ecosystems are needed for better landscape planning towards sustainable UWEs. In this study, we examined the impacts of urbanization on the Muthurajawela Marsh and Negombo Lagoon (MMNL), an important UWE in Sri Lanka that provides valuable ecosystem services. We used remote sensing data to detect changes in the land use/cover (LUC) of the MMNL over a two-decade period (1997–2017) and spatial metrics to characterize changes in landscape composition and configuration. The results revealed that the spatial and socio-economic elements of rapid urbanization of the MMNL had been the main driver of transformation of its natural environment over the past 20 years. This is indicated by a substantial expansion of settlements (+68%) and a considerable decrease of marshland and mangrove cover (−41% and −21%, respectively). A statistical analysis revealed a significant relationship between the change in population density and the loss of wetland due to settlement expansion at the Grama Niladhari division level (n = 99) (where wetland includes marshland, mangrove, and water) (1997–2007: R2 = 0.435, p = 0.000; 2007–2017: R2 = 0.343, p = 0.000). The findings also revealed that most of the observed LUC changes occurred in areas close to roads and growth nodes (viz. Negombo, Ja-Ela, Wattala, and Katana), which resulted in both landscape fragmentation and infill urban expansion. We conclude that, in order to ensure the sustainability of the MMNL, there is an urgent need for forward-looking landscape and urban planning to promote environmentally conscious urban development in the area which is a highly valuable UWE.

ACS Style

Darshana Athukorala; Ronald C. Estoque; Yuji Murayama; Bunkei Matsushita. Impacts of Urbanization on the Muthurajawela Marsh and Negombo Lagoon, Sri Lanka: Implications for Landscape Planning Towards a Sustainable Urban Wetland Ecosystem. Remote Sensing 2021, 13, 316 .

AMA Style

Darshana Athukorala, Ronald C. Estoque, Yuji Murayama, Bunkei Matsushita. Impacts of Urbanization on the Muthurajawela Marsh and Negombo Lagoon, Sri Lanka: Implications for Landscape Planning Towards a Sustainable Urban Wetland Ecosystem. Remote Sensing. 2021; 13 (2):316.

Chicago/Turabian Style

Darshana Athukorala; Ronald C. Estoque; Yuji Murayama; Bunkei Matsushita. 2021. "Impacts of Urbanization on the Muthurajawela Marsh and Negombo Lagoon, Sri Lanka: Implications for Landscape Planning Towards a Sustainable Urban Wetland Ecosystem." Remote Sensing 13, no. 2: 316.

Journal article
Published: 25 September 2020 in Sustainability
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Rapid urbanization is one of the most crucial issues in the world of the 21st century. Notably, the urban heat island phenomenon is becoming more prominent in megacities and their hinterlands in temperate and subtropical climatic regions. In the daytime in summer, there exists a high possibility of accelerating the land surface temperature (LST) in desert cities, due to the alterations made by human beings in the natural environment. In this study, we investigate the spatial formation of LST in a tropical sub-Saharan city of Accra, a gateway to West Africa, using Landsat data in 2003 and 2017. Machine learning techniques and the different spatial and statistical methods such as tasseled cap transformation (TCT), urban-rural gradient, and multiresolution grid-based and landscape metrics were employed to examine procured land use/cover (LUC) and LST maps. LUC was classified into five categories: Built up, Green 1, Green 2, Bare land, and Water. The results of the analysis indicate that Built up, Green 2, and Bare land had caused the highest heating effect while Green 1 and Water had caused the considerable cooling effect during the daytime in Accra. The urban-rural difference in LST recorded 1.4 °C in 2003 and 0.28 °C in 2017. The mean size, mean shape, largest patch, and aggregation of Built up, Green 1, and Green 2 had a strong relationship with the mean LST. It is essential for urban planners to carefully examine the formation and effect of the urban heat island (UHI) for sustainable urban development and landscape policy toward mitigation and adaptation planning in Accra.

ACS Style

Darshana Athukorala; Yuji Murayama. Spatial Variation of Land Use/Cover Composition and Impact on Surface Urban Heat Island in a Tropical Sub-Saharan City of Accra, Ghana. Sustainability 2020, 12, 7953 .

AMA Style

Darshana Athukorala, Yuji Murayama. Spatial Variation of Land Use/Cover Composition and Impact on Surface Urban Heat Island in a Tropical Sub-Saharan City of Accra, Ghana. Sustainability. 2020; 12 (19):7953.

Chicago/Turabian Style

Darshana Athukorala; Yuji Murayama. 2020. "Spatial Variation of Land Use/Cover Composition and Impact on Surface Urban Heat Island in a Tropical Sub-Saharan City of Accra, Ghana." Sustainability 12, no. 19: 7953.

Journal article
Published: 23 September 2020 in Diversity
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Rodent assemblages have ecological importance in ecosystem functioning and protected area management. Our study examines the patterns of assemblages of rodents across four habitat types (i.e., Miombo woodland, Acacia woodland, grasslands and farmlands) in the savanna environment. Capture-mark-recapture (CMR) methods were applied for data collection across the Chembe Bird Sanctuary (CBS) landscape. The Non-metric Multi-Dimensional Scaling (NMDS) was used for exploratory data analysis, followed by Analysis of Variance (ANOVA) and Tukey–Kramer’s Honestly Significant Difference (HSD) post-hoc tests. The rodent assemblages in CBS significantly differed between the non-farmlands (i.e., Miombo woodland, Acacia woodland and grasslands) and farmlands. There were: (1) zero rodent diversity in farmlands, dominated completely by a pest species, M. natalensis; and (2) different rodent assemblages in three non-farmland habitat types. We suggest that rodent assemblages should be mediated by conservation planning and multi-stakeholder collaboration beyond the protected area boundaries to contribute to a working CBS landscape positively.

ACS Style

Vincent R. Nyirenda; Ngawo Namukonde; Matamyo Simwanda; Darius Phiri; Yuji Murayama; Manjula Ranagalage; Kaula Milimo. Rodent Assemblages in the Mosaic of Habitat Types in the Zambezian Bioregion. Diversity 2020, 12, 365 .

AMA Style

Vincent R. Nyirenda, Ngawo Namukonde, Matamyo Simwanda, Darius Phiri, Yuji Murayama, Manjula Ranagalage, Kaula Milimo. Rodent Assemblages in the Mosaic of Habitat Types in the Zambezian Bioregion. Diversity. 2020; 12 (10):365.

Chicago/Turabian Style

Vincent R. Nyirenda; Ngawo Namukonde; Matamyo Simwanda; Darius Phiri; Yuji Murayama; Manjula Ranagalage; Kaula Milimo. 2020. "Rodent Assemblages in the Mosaic of Habitat Types in the Zambezian Bioregion." Diversity 12, no. 10: 365.

Journal article
Published: 06 August 2020 in Sustainable Cities and Society
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Land surface temperature (LST) is receiving increasing attention as a measure of urban health and sustainable development. With rapid urbanization and industrialization, the urban heat island phenomenon, which causes excessive energy consumption and climatic and environmental deterioration, has become prevalent in many cities. It is well known that optimizing land use/cover (LUC) distribution can reduce the urban heat island phenomenon. Therefore, monitoring land use and land cover changes and analyzing their effects on LST is crucial for healthy urban development. In this study, an attempt is made to examine LST and LUC changes in Sapporo, Japan. Using Landsat data, we attempted to analyze the LST in each LUC category from 1985 to 2015. The results show that: (1) LUC types and spatial distribution have great influences on LST, (2) expanding development has been the most significant factor affecting urban heat island phenomenon over the past 30 years, and (3) green space and water areas have helped cool the city. This study revealed a strong relationship between LUC distribution and LST, opening research avenues for future LUC simulation. Our analysis not only contributes to urban health and sustainable development but also provides significant insights into the promotion of city competence.

ACS Style

Ruci Wang; Yuji Murayama. Geo-simulation of land use/cover scenarios and impacts on land surface temperature in Sapporo, Japan. Sustainable Cities and Society 2020, 63, 102432 .

AMA Style

Ruci Wang, Yuji Murayama. Geo-simulation of land use/cover scenarios and impacts on land surface temperature in Sapporo, Japan. Sustainable Cities and Society. 2020; 63 ():102432.

Chicago/Turabian Style

Ruci Wang; Yuji Murayama. 2020. "Geo-simulation of land use/cover scenarios and impacts on land surface temperature in Sapporo, Japan." Sustainable Cities and Society 63, no. : 102432.

Journal article
Published: 01 August 2020 in Forests
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Forest-cover change has become an important topic in global biodiversity conservation in recent decades because of the high rates of forest loss in different parts of the world, especially in the tropical region. While human interventions are the major cause, natural disasters also contribute to forest cover changes. During the past decades, several studies have been conducted to address different aspects of forest cover changes (e.g., drivers of deforestation, degradation, interventions) in different parts of the world. In Sri Lanka, increasing rates of forest loss have been recorded during the last 100 years on a regional basis, especially in the dry zone. However, Sri Lanka needs detailed studies that employ contemporary data and robust analytical tools to understand the patterns of forest cover changes and their drivers. The dry zone of Sri Lanka encompasses 59% of the total land area of the country, ergo, the most extensive forest cover. Our study analyzed forest cover dynamics and its drivers between 1992 and 2019. Our specific objectives included (i) producing a forest cover map for 2019, (ii) analyzing the spatiotemporal patterns of forest cover changes from 1992 to 2019, and (iii) determining the main driving forces. Landsat 8 images were used to develop forest-cover maps for 2019, and the rest of the forest cover maps (1992, 1999, and 2010) were obtained from the Forest Department of Sri Lanka. In this study, we found that the dry zone had undergone rapid forest loss (246,958.4 ha) during the past 27 years, which accounts for 8.0% of the net forest cover changes. From 2010 to 2019, the rates of forest loss were high, and this can be associated with the rapid infrastructure development of the country. The findings of this study can be used as a proxy to reform current forest policies and enhance the forest sustainability of the study area.

ACS Style

Manjula Ranagalage; M. H. J. P. Gunarathna; Thilina D. Surasinghe; Dmslb Dissanayake; Matamyo Simwanda; Yuji Murayama; Takehiro Morimoto; Darius Phiri; Vincent R. Nyirenda; K. T. Premakantha; Anura Sathurusinghe. Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka. Forests 2020, 11, 836 .

AMA Style

Manjula Ranagalage, M. H. J. P. Gunarathna, Thilina D. Surasinghe, Dmslb Dissanayake, Matamyo Simwanda, Yuji Murayama, Takehiro Morimoto, Darius Phiri, Vincent R. Nyirenda, K. T. Premakantha, Anura Sathurusinghe. Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka. Forests. 2020; 11 (8):836.

Chicago/Turabian Style

Manjula Ranagalage; M. H. J. P. Gunarathna; Thilina D. Surasinghe; Dmslb Dissanayake; Matamyo Simwanda; Yuji Murayama; Takehiro Morimoto; Darius Phiri; Vincent R. Nyirenda; K. T. Premakantha; Anura Sathurusinghe. 2020. "Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka." Forests 11, no. 8: 836.

Review
Published: 16 July 2020 in Remote Sensing
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The advancement in satellite remote sensing technology has revolutionised the approaches to monitoring the Earth’s surface. The development of the Copernicus Programme by the European Space Agency (ESA) and the European Union (EU) has contributed to the effective monitoring of the Earth’s surface by producing the Sentinel-2 multispectral products. Sentinel-2 satellites are the second constellation of the ESA Sentinel missions and carry onboard multispectral scanners. The primary objective of the Sentinel-2 mission is to provide high resolution satellite data for land cover/use monitoring, climate change and disaster monitoring, as well as complementing the other satellite missions such as Landsat. Since the launch of Sentinel-2 multispectral instruments in 2015, there have been many studies on land cover/use classification which use Sentinel-2 images. However, no review studies have been dedicated to the application of ESA Sentinel-2 land cover/use monitoring. Therefore, this review focuses on two aspects: (1) assessing the contribution of ESA Sentinel-2 to land cover/use classification, and (2) exploring the performance of Sentinel-2 data in different applications (e.g., forest, urban area and natural hazard monitoring). The present review shows that Sentinel-2 has a positive impact on land cover/use monitoring, specifically in monitoring of crop, forests, urban areas, and water resources. The contemporary high adoption and application of Sentinel-2 can be attributed to the higher spatial resolution (10 m) than other medium spatial resolution images, the high temporal resolution of 5 days and the availability of the red-edge bands with multiple applications. The ability to integrate Sentinel-2 data with other remotely sensed data, as part of data analysis, improves the overall accuracy (OA) when working with Sentinel-2 images. The free access policy drives the increasing use of Sentinel-2 data, especially in developing countries where financial resources for the acquisition of remotely sensed data are limited. The literature also shows that the use of Sentinel-2 data produces high accuracies (>80%) with machine-learning classifiers such as support vector machine (SVM) and Random forest (RF). However, other classifiers such as maximum likelihood analysis are also common. Although Sentinel-2 offers many opportunities for land cover/use classification, there are challenges which include mismatching with Landsat OLI-8 data, a lack of thermal bands, and the differences in spatial resolution among the bands of Sentinel-2. Sentinel-2 data show promise and have the potential to contribute significantly towards land cover/use monitoring.

ACS Style

Darius Phiri; Matamyo Simwanda; Serajis Salekin; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing 2020, 12, 2291 .

AMA Style

Darius Phiri, Matamyo Simwanda, Serajis Salekin, Vincent Nyirenda, Yuji Murayama, Manjula Ranagalage. Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing. 2020; 12 (14):2291.

Chicago/Turabian Style

Darius Phiri; Matamyo Simwanda; Serajis Salekin; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. 2020. "Sentinel-2 Data for Land Cover/Use Mapping: A Review." Remote Sensing 12, no. 14: 2291.

Journal article
Published: 19 May 2020 in ISPRS International Journal of Geo-Information
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Decision tree (DT) algorithms are important non-parametric tools used for land cover classification. While different DTs have been applied to Landsat land cover classification, their individual classification accuracies and performance have not been compared, especially on their effectiveness to produce accurate thresholds for developing rulesets for object-based land cover classification. Here, the focus was on comparing the performance of five DT algorithms: Tree, C5.0, Rpart, Ipred, and Party. These DT algorithms were used to classify ten land cover classes using Landsat 8 images on the Copperbelt Province of Zambia. Classification was done using object-based image analysis (OBIA) through the development of rulesets with thresholds defined by the DTs. The performance of the DT algorithms was assessed based on: (1) DT accuracy through cross-validation; (2) land cover classification accuracy of thematic maps; and (3) other structure properties such as the sizes of the tree diagrams and variable selection abilities. The results indicate that only the rulesets developed from DT algorithms with simple structures and a minimum number of variables produced high land cover classification accuracies (overall accuracy > 88%). Thus, algorithms such as Tree and Rpart produced higher classification results as compared to C5.0 and Party DT algorithms, which involve many variables in classification. This high accuracy has been attributed to the ability to minimize overfitting and the capacity to handle noise in the data during training by the Tree and Rpart DTs. The study produced new insights on the formal selection of DT algorithms for OBIA ruleset development. Therefore, the Tree and Rpart algorithms could be used for developing rulesets because they produce high land cover classification accuracies and have simple structures. As an avenue of future studies, the performance of DT algorithms can be compared with contemporary machine-learning classifiers (e.g., Random Forest and Support Vector Machine).

ACS Style

Darius Phiri; Matamyo Simwanda; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. Decision Tree Algorithms for Developing Rulesets for Object-Based Land Cover Classification. ISPRS International Journal of Geo-Information 2020, 9, 329 .

AMA Style

Darius Phiri, Matamyo Simwanda, Vincent Nyirenda, Yuji Murayama, Manjula Ranagalage. Decision Tree Algorithms for Developing Rulesets for Object-Based Land Cover Classification. ISPRS International Journal of Geo-Information. 2020; 9 (5):329.

Chicago/Turabian Style

Darius Phiri; Matamyo Simwanda; Vincent Nyirenda; Yuji Murayama; Manjula Ranagalage. 2020. "Decision Tree Algorithms for Developing Rulesets for Object-Based Land Cover Classification." ISPRS International Journal of Geo-Information 9, no. 5: 329.

Journal article
Published: 25 April 2020 in Journal of Geography (Chigaku Zasshi)
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Geographical features in the early 19th century and transformation of landforms during the past 200 years in Japan are studied through an overlay analysis of the current GSI map issued by the Geospatial Information Authority of Japan and Inoh's map issued in 1821. Analyzed are: (i) survey activities of Inoh's team and terrain conditions, shapes of lakes and islands, and distribution of place names at the end of the Edo era using 214 sheets of Inoh's large-scale map (1:36,000), and (ii) retreat and advance of coastlines, and route changes of roads and rivers over the 200 years. Land development is investigated through reclamation and landfills from natural and socio-economic aspects by applying GIS datasets to a digitalized version of Inoh's map. The usefulness of geospatial analysis is demonstrated by employing GIS techniques to understand quantitatively changing land conditions in Japan.

ACS Style

Yuki Iwai; Yuji Murayama; Kota Inohara. Spatial Analysis of Inoh's Map Using GIS with the Focus on National Land Changes over 200 Years in Japan. Journal of Geography (Chigaku Zasshi) 2020, 129, 215 -226.

AMA Style

Yuki Iwai, Yuji Murayama, Kota Inohara. Spatial Analysis of Inoh's Map Using GIS with the Focus on National Land Changes over 200 Years in Japan. Journal of Geography (Chigaku Zasshi). 2020; 129 (2):215-226.

Chicago/Turabian Style

Yuki Iwai; Yuji Murayama; Kota Inohara. 2020. "Spatial Analysis of Inoh's Map Using GIS with the Focus on National Land Changes over 200 Years in Japan." Journal of Geography (Chigaku Zasshi) 129, no. 2: 215-226.

Journal article
Published: 06 April 2020 in Sustainability
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The blooming of urban expansion has led to the improvement of urban life, but some of the negative externalities have affected the life quality of urban dwellers, both directly and indirectly. As a result of this, research related to the quality of life has gained much attention among multidisciplinary researchers around the world. A number of attempts have been made by previous researchers to identify, assess, quantify, and map quality of life or well-being under various kinds of perspectives. The objectives of this research were to create a life quality index (LQI) and identify the spatial distribution pattern of LQI in Kandy City, Sri Lanka. Multiple factors were decomposed, a hierarchy was constructed by the multi-criteria decision making (MCDM) method, and 13 factors were selected under two main criteria—environmental and socioeconomic. Pairwise comparison matrices were created, and the weight of each factor was determined by the analytic hierarchy process (AHP). Finally, gradient analysis was employed to examine the spatial distribution pattern of LQI from the city center to the periphery. The results show that socioeconomic factors affect the quality of life more strongly than environmental factors, and the most significant factor is transportation. The highest life quality zones (26% of the total area) were distributed around the city center, while the lowest zones represented only 9% of the whole area. As shown in the gradient analysis, more than 50% of the land in the first five kilometers from the city center comes under the highest life quality zone. This research will provide guidance for the residents and respective administrative bodies to make Kandy City a livable city. It the constructed model can be applied to any geographical area by conducting necessary data calibration.

ACS Style

Dmslb Dissanayake; Takehiro Morimoto; Yuji Murayama; Manjula Ranagalage; Enc Perera. Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka. Sustainability 2020, 12, 2918 .

AMA Style

Dmslb Dissanayake, Takehiro Morimoto, Yuji Murayama, Manjula Ranagalage, Enc Perera. Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka. Sustainability. 2020; 12 (7):2918.

Chicago/Turabian Style

Dmslb Dissanayake; Takehiro Morimoto; Yuji Murayama; Manjula Ranagalage; Enc Perera. 2020. "Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka." Sustainability 12, no. 7: 2918.

Journal article
Published: 25 March 2020 in ISPRS International Journal of Geo-Information
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The use of parcel-pickup points (PPPs) is an effective approach for solving the last-mile problem. However, few studies provide specific guidance for the optimal organization of PPPs. Here, a geographic information system(GIS)-based hybrid model was developed combining the widely used analytic hierarchy process (AHP) multi-criteria analysis method with the Huff model that predicts the number of visiting customers to determine the optimal facility for collaboration and service as a PPP. Using this model, a decision-maker can select the highest-ranking facility or use the fluctuation ranking graph to determine a priority list of candidate facilities according to the appropriate PPP service distance. Our findings suggest that the optimal candidate facility should be located near high population density areas, a dense road network, and few geographic barriers. The facility should have a high attractiveness value, long business hours, and convenient access to public transportation, cover a large, high-population area, and should be a retail chain store. Based on these findings, the AHP method can improve the accuracy of obtaining the facility attractiveness value using the Huff model. Facility attractiveness has a strong effect on the resulting number of customers in the case of acceptably long distances to residential buildings.

ACS Style

Zilai Zheng; Takehiro Morimoto; Yuji Murayama. Optimal Location Analysis of Delivery Parcel-Pickup Points Using AHP and Network Huff Model: A Case Study of Shiweitang Sub-District in Guangzhou City, China. ISPRS International Journal of Geo-Information 2020, 9, 193 .

AMA Style

Zilai Zheng, Takehiro Morimoto, Yuji Murayama. Optimal Location Analysis of Delivery Parcel-Pickup Points Using AHP and Network Huff Model: A Case Study of Shiweitang Sub-District in Guangzhou City, China. ISPRS International Journal of Geo-Information. 2020; 9 (4):193.

Chicago/Turabian Style

Zilai Zheng; Takehiro Morimoto; Yuji Murayama. 2020. "Optimal Location Analysis of Delivery Parcel-Pickup Points Using AHP and Network Huff Model: A Case Study of Shiweitang Sub-District in Guangzhou City, China." ISPRS International Journal of Geo-Information 9, no. 4: 193.

Journal article
Published: 31 January 2020 in Remote Sensing
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Rapid urbanization is one of the most concerning issues in the 21st century because of its significant impacts on various fields, including agriculture, forestry, ecology, and climate. The urban heat island (UHI) phenomenon, highly related to the rapid urbanization, has attracted considerable attention from both academic scholars and governmental policymakers because of its direct influence on citizens’ daily life. Land surface temperature (LST) is a widely used indicator to assess the intensity of UHI significantly affected by the local land use/cover (LULC). In this study, we used the Landsat time-series data to derive the LULC composition and LST distribution maps of Nanjing in 2000, 2014, and 2018. A correlation analysis was carried out to check the relationship between LST and the density of each class of LULC. We found out that cropland and forest in Nanjing are helping to cool the city with different degrees of cooling effects depending on the location and LULC composition. Then, a Cellar Automata (CA)-Markov model was applied to predict the LULC conditions of Nanjing in 2030 and 2050. Based on the simulated LULC maps and the relationship between LST and LULC, we delineated high- and moderate-LST related risk areas in the city of Nanjing. Our findings are valuable for the local government to reorganize the future development zones in a way to control the urban climate environment and to keep a healthy social life within the city.

ACS Style

Ruci Wang; Hao Hou; Yuji Murayama; Ahmed Derdouri. Spatiotemporal Analysis of Land Use/Cover Patterns and Their Relationship with Land Surface Temperature in Nanjing, China. Remote Sensing 2020, 12, 440 .

AMA Style

Ruci Wang, Hao Hou, Yuji Murayama, Ahmed Derdouri. Spatiotemporal Analysis of Land Use/Cover Patterns and Their Relationship with Land Surface Temperature in Nanjing, China. Remote Sensing. 2020; 12 (3):440.

Chicago/Turabian Style

Ruci Wang; Hao Hou; Yuji Murayama; Ahmed Derdouri. 2020. "Spatiotemporal Analysis of Land Use/Cover Patterns and Their Relationship with Land Surface Temperature in Nanjing, China." Remote Sensing 12, no. 3: 440.

Journal article
Published: 17 January 2020 in Remote Sensing
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Satellite-derived land surface temperature (LST) reveals the variations and impacts on the terrestrial thermal environment on a broad spatial scale. The drastic growth of urbanization-induced impervious surfaces and the urban population has generated a remarkably increasing influence on the urban thermal environment in China. This research was aimed to investigate land surface temperature (LST) intensity response to urban land cover/use by examining the thermal impact on urban settings in ten Chinese megacities (i.e., Beijing, Dongguan, Guangzhou, Hangzhou, Harbin, Nanjing, Shenyang, Suzhou, Tianjin, and Wuhan). Surface urban heat island (SUHI) footprints were scrutinized and compared by magnitude and extent. The causal mechanism among land cover composition (LCC), population, and SUHI was also identified. Spatial patterns of the thermal environments were identical to those of land cover/use. In addition, most impervious surface materials (greater than 81%) were labeled as heat sources, on the other hand, water and vegetation were functioned as heat sinks. More than 85% of heat budgets in Beijing and Guangzhou were generated from impervious surfaces. SUHI for all megacities showed spatially gradient decays between urban and surrounding rural areas; further, temperature peaks are not always dominant in the urban core, despite extremely dense impervious surfaces. The composition ratio of land cover (LCC%) negatively correlates with SUHI intensity (SUHII), whereas the population positively associates with SUHII. For all targeted megacities, land cover composition and population account for more than 63.9% of SUHI formation using geographically weighted regression. The findings can help optimize land cover/use to relieve pressure from rapid urbanization, maintain urban ecological balance, and meet the demands of sustainable urban growth.

ACS Style

Fei Liu; Xinmin Zhang; Yuji Murayama; Takehiro Morimoto. Impacts of Land Cover/Use on the Urban Thermal Environment: A Comparative Study of 10 Megacities in China. Remote Sensing 2020, 12, 307 .

AMA Style

Fei Liu, Xinmin Zhang, Yuji Murayama, Takehiro Morimoto. Impacts of Land Cover/Use on the Urban Thermal Environment: A Comparative Study of 10 Megacities in China. Remote Sensing. 2020; 12 (2):307.

Chicago/Turabian Style

Fei Liu; Xinmin Zhang; Yuji Murayama; Takehiro Morimoto. 2020. "Impacts of Land Cover/Use on the Urban Thermal Environment: A Comparative Study of 10 Megacities in China." Remote Sensing 12, no. 2: 307.

Journal article
Published: 11 January 2020 in Land Use Policy
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Curbing the historically unplanned urban development in African cities crucially demands that the drivers of urban land use (urban-LU) changes are comprehended. However, this has become a complex decision problem for African urban planners and policy makers owing to the interconnections among urban-LU drivers and the complicated mixed development of planned and unplanned areas. Therefore, this study presents a new framework to model drivers of urban-LU changes in Lusaka, Zambia for the last 50 years using ground questionnaire surveys and the analytic network process (ANP). The study considers the growth of six urban-LUs, namely, unplanned high density residential (UHDR), unplanned low density residential (ULDR); planned medium-high density residential (PMHDR), planned low density residential (PLDR), commercial and industrial (CMI); and public institutions and service (PIS). The results revealed that socio-economic (55.11 %) and population (27.37 %) factors have been the major drivers of urban-LU changes while political factors (13.07 %) have also played a role. The role of biophysical factors (4.44 %) has been insignificant. The ANP model ranks UHDR (1st) and CMI (2nd) areas as the fastest-growing primarily driven by interactions amongst migration, economic opportunities, social services and land market. The growth of PMHDR, PIS and PLDR areas, ranked 3rd, 4th and 5th, respectively, has been largely driven by plans and policies and the political situation. The growth of ULDR areas is ranked (6th) as the lowest. The study discusses the urban planning and land use policy implications and suggests several strategies including strengthening of the local planning authority; improvement of the land tenure policies and delivery systems; establishment of satellite economic zones to decongest the city; investment in both green and blue infrastructure; and timely policy reviews.

ACS Style

Matamyo Simwanda; Yuji Murayama; Manjula Ranagalage. Modeling the drivers of urban land use changes in Lusaka, Zambia using multi-criteria evaluation: An analytic network process approach. Land Use Policy 2020, 92, 104441 .

AMA Style

Matamyo Simwanda, Yuji Murayama, Manjula Ranagalage. Modeling the drivers of urban land use changes in Lusaka, Zambia using multi-criteria evaluation: An analytic network process approach. Land Use Policy. 2020; 92 ():104441.

Chicago/Turabian Style

Matamyo Simwanda; Yuji Murayama; Manjula Ranagalage. 2020. "Modeling the drivers of urban land use changes in Lusaka, Zambia using multi-criteria evaluation: An analytic network process approach." Land Use Policy 92, no. : 104441.