Yaowaret Jantakat - Academia.edu (original) (raw)

Papers by Yaowaret Jantakat

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019

Presently, urban agriculture (UA) is an important part of the urban ecosystem and a key factor th... more Presently, urban agriculture (UA) is an important part of the urban ecosystem and a key factor that can help in the urban environmental management. Therefore, this paper studies a spatial-temporal analysis of UA areas and types in Municipality of Nakhonratchasima City (MNC), Thailand. This UA types referred land use classification system of Land Development Department (LDD). Google Earth images acquired in the years of 2007, 2011, 2015 and 2018 were used to examine UA change with segmentation-based classification method in QGIS to classify Google Earth images into thematic maps. Moreover, this study showed different spatiotemporal change patterns, composition and rates in the study area and indicates the importance of analyzing UA change. Therefore, the results of this classification consisted of eleven classesabandoned paddy field, rice paddy, abandoned field crop, mixed field crop, cassava, betel palm, mixed orchard, coconut, rose apple, truck crop, and fish farm. Truck crop had the greatest cover in study area while floricultural covered the minimal space over periods of study. The UA change analysis over time for entire study areas provides an overall picture of change trends. Furthermore, the UA change at census sector scale gives new insights on how human-induced activities (e.g., built-up areas and roads) affect UA change patterns and rates. This research indicates the necessity to implement change detection for better understanding the UA change patterns and rates. 1. INTRODUCTION 1.1 Urban Agriculture Urban agriculture (UA) is now one important type of urban land use/cover planning or an agricultural activities in urban areas. UA provides food, economic, social and environment (Goodman and Minner, 2019; Dieleman, 2017) that types of UA includes a diversity of agriculture in both hidden and obvious patterns that is depend on that urban area's location. Meaning of UA, generally, is briefly defined as the growing of urban food areas (

International Journal of Building, Urban, Interior and Landscape Technology (BUILT)

Green areas are so critical in urban communities for making environments healthier and mo... more Green areas are so critical in urban communities for making environments healthier and more livable. The objectives of this study were to assess sustainable green areas and to study their ecological niches in an urban education institute. Rajamangala University of Technology Isan (RMUTI) at Nakhonratchasima City Municipality (NCM) was selected as the study area. The spatial assessment of sustainable green areas used guidelines of the policy action plan for sustainable urban green area management by the Office of Natural Resources and Environmental Policy and Planning (ONEP) and then sustainable green areas were analyzed by the Ecological Niche Model (ENM) in Biomapper to check the distribution and durability of the existing trees to the current environment.The study found that sustainable green area in RMUTI at NCM is about 54.23% with 1,176 trees, which is in accordance with the policy action plan of ONEP that has suggested at least 30% of the land parcel being the sustaina...

Many cities has set goal of green city with tree increasing. The objective of this study is to as... more Many cities has set goal of green city with tree increasing. The objective of this study is to assess green city-based tree cover change in Nakhonratchasima City Municipality (NCM). In analysis, Google Earth (GE) imagery during 2012-2020 was used for visual interpretation but the result of Urban Tree Canopy (UTC) cover interpretation on GE image in year 2020 only was evaluated accuracy in field and was used to be the base map for supporting GE photo-interpretation in the past (2012-2019). The result of annually UTC cover layers would be taken to estimate air pollutants ((CO, NO 2 , O 3 , PM10, PM 2.5 and SO 2) via i-Tree Canopy on web. As results, the accuracy assessment of UTC cover map in year 2020 is 96.5517%. Tree cover change during the varying periods were found that there were ranged from dramatic reduction in percent tree cover of 17.2873% in year 2013 (because of built-up areas' increasing in that time) and slight reducing 0.0561% in year 2015 to an increase in percent tree cover of 0.3122% in year 2016 and 0.0488% in year 2017 while percent tree cover has been gradually decreased between 2018 and 2020. At the same time, NCM's UTC cover included the highest total removal value of CO (17.0 x 10-7 % per year) in year 2017; of NO 2 (74.0 x 10-7 % per year) in year 2013, 2014 and 2017; of O 3 (711.0 x 10-7 % per year) in year 2015; of PM10 (240.0 x 10-7 % per year) in year 2013 and 2014; of PM 2.5 (38.0 x 10-7 % per year) in year 2017; of SO 2 (48.0 x 10-7 % per year) in year 2013 and 2014. This assessment of such pollutant removal should not only be considered by tree cover but also the concerned factors (i.e., pollution concentrate, length of in-leaf season, amount of precipitation, and other meteorological variables). The mentioned results above, they will be used for spatial information for planning green city in area of NCM and guiding other green cities. Consequently, this study suggests for next work as: (1) study relationship between tree cover and land use/land cover and (2) study other related factors for UTC cover change.

The aim of the study is to evaluate suitable algorithm and datasets for land use and land cover (... more The aim of the study is to evaluate suitable algorithm and datasets for land use and land cover (LULC) classification in Chok Chai district of Nakhon Ratchasima province in Thailand. This study prepared 10 datasets (1 multispectral data and 9 texture measures data) that were used for LULC classification using supervised classification with Maximum Likelihood Classifier (MLC) and Artificial Neural Networks (ANN). Herein, all datasets were classified into 10 classes that consisted of (1) urban and built-up area, (2) paddy field, (3) cassava, (4) sugarcane, (5) eucalyptus, (6) orchard, (7) forest land, (8) water body, (9) scrub, and (10) abandon land. In addition, accuracy assessment of LULC classification in each dataset was performed with Overall Accuracy (OA) and Kappa hat coefficient of agreement ( ). As a result, MLC is suitable algorithm for combined datasets of multispectral data and texture measures because accuracy of all combined datasets was higher than ANN. Herewith multisp...

The IAFOR International Conference on Education – Hawaii 2020 Official Conference Proceedings, 2020

– The IAFOR International Conference on Sustainability, Energy & the Environment – Hawaii 2020 Official Conference Proceedings, 2020

International Journal of Building, Urban, Interior and Landscape Technology (BUILT), 2020

Many cities has set goal of green city with tree increasing. The objective of this study is to as... more Many cities has set goal of green city with tree increasing. The objective of this study is to assess green city-based tree cover change in Nakhonratchasima City Municipality (NCM). In analysis, Google Earth (GE) imagery during 2012-2020 was used for visual interpretation but the result of Urban Tree Canopy (UTC) cover interpretation on GE image in year 2020 only was evaluated accuracy in field and was used to be the base map for supporting GE photo-interpretation in the past (2012-2019). The result of annually UTC cover layers would be taken to estimate air pollutants ((CO, NO 2 , O 3 , PM10, PM 2.5 and SO 2) via i-Tree Canopy on web. As results, the accuracy assessment of UTC cover map in year 2020 is 96.5517%. Tree cover change during the varying periods were found that there were ranged from dramatic reduction in percent tree cover of 17.2873% in year 2013 (because of built-up areas' increasing in that time) and slight reducing 0.0561% in year 2015 to an increase in percent tree cover of 0.3122% in year 2016 and 0.0488% in year 2017 while percent tree cover has been gradually decreased between 2018 and 2020. At the same time, NCM's UTC cover included the highest total removal value of CO (17.0 x 10-7 % per year) in year 2017; of NO 2 (74.0 x 10-7 % per year) in year 2013, 2014 and 2017; of O 3 (711.0 x 10-7 % per year) in year 2015; of PM10 (240.0 x 10-7 % per year) in year 2013 and 2014; of PM 2.5 (38.0 x 10-7 % per year) in year 2017; of SO 2 (48.0 x 10-7 % per year) in year 2013 and 2014. This assessment of such pollutant removal should not only be considered by tree cover but also the concerned factors (i.e., pollution concentrate, length of in-leaf season, amount of precipitation, and other meteorological variables). The mentioned results above, they will be used for spatial information for planning green city in area of NCM and guiding other green cities. Consequently, this study suggests for next work as: (1) study relationship between tree cover and land use/land cover and (2) study other related factors for UTC cover change.

Ranked road sections in terms of risk together with ranked weights of factors considered to cause... more Ranked road sections in terms of risk together with ranked weights of factors considered to cause accident for each section are highly effectual information for road safety implementing planning. To achieve this goal, 36 road sections from 5 highways in Nakhon Ratchasima, Thailand with varying slopes, surface widths, and a number of connection routes, initially selected from 166 sections by using 3-year accident data, are ranked into order from the highest risk to the lowest risk using ordered weight averaging (OWA) decision rule. OWA is a multi-criteria evaluation procedure using combination operators. Apart from risk ranking of road sections, the result shows that slope is considered to be the highest rank among risk factors for 16 sections, while 15 and 5 sections are for the number of connection routes and surface width respectively. In addition, a number of ranking sections within each certain highway can be obtained i.e. 17, 12, 3, 2, and 2 sections for highway no. 205, 207, 2...

Ranked road sections in terms of risk together with ranked weights of factors considered to cause... more Ranked road sections in terms of risk together with ranked weights of factors considered to cause accident for each section are highly effectual information for road safety implementing planning. To achieve this goal, 36 road sections from 5 highways in Nakhon Ratchasima, Thailand with varying slopes, surface widths, and a number of connection routes, initially selected from 166 sections by using 3-year accident data, are ranked into order from the highest risk to the lowest risk using ordered weight averaging (OWA) decision rule. OWA is a multi-criteria evaluation procedure using combination operators. Apart from risk ranking of road sections, the result shows that slope is considered to be the highest rank among risk factors for 16 sections, while 15 and 5 sections are for the number of connection routes and surface width respectively. In addition, a number of ranking sections within each certain highway can be obtained i.e. 17, 12, 3, 2, and 2 sections for highway no. 205, 207, 2...

This paper aims to assess the effect of incorporating topographical data with geostatistical inte... more This paper aims to assess the effect of incorporating topographical data with geostatistical interpolation for monthly rainfall and temperature in Ping Basin, Thailand. The spatial interpolation techniques based on 11 semivariogram models of 4 main sub-types of cokriging with 3 topographical variables: elevation, longitude, and latitude have been applied in this study. The best interpolation models from cokriging technique on mean monthly rainfall and mean monthly temperature are selected by Akaike Information Criterion (AIC) based on partial sill, range and nugget that the best monthly models of kriging technique is operated in same mentioned selection. In addition, an assessment of the effective results of the cokriging interpolation models is performed by 2 approaches: i) comparing the errors of the best results from other interpolations excluding topographic data with the least MAE, MRE and RMSE value and ii) comparing the accuracy of results from Multiple Linear Regression (MLR...

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019

Presently, urban agriculture (UA) is an important part of the urban ecosystem and a key factor th... more Presently, urban agriculture (UA) is an important part of the urban ecosystem and a key factor that can help in the urban environmental management. Therefore, this paper studies a spatial-temporal analysis of UA areas and types in Municipality of Nakhonratchasima City (MNC), Thailand. This UA types referred land use classification system of Land Development Department (LDD). Google Earth images acquired in the years of 2007, 2011, 2015 and 2018 were used to examine UA change with segmentation-based classification method in QGIS to classify Google Earth images into thematic maps. Moreover, this study showed different spatiotemporal change patterns, composition and rates in the study area and indicates the importance of analyzing UA change. Therefore, the results of this classification consisted of eleven classesabandoned paddy field, rice paddy, abandoned field crop, mixed field crop, cassava, betel palm, mixed orchard, coconut, rose apple, truck crop, and fish farm. Truck crop had the greatest cover in study area while floricultural covered the minimal space over periods of study. The UA change analysis over time for entire study areas provides an overall picture of change trends. Furthermore, the UA change at census sector scale gives new insights on how human-induced activities (e.g., built-up areas and roads) affect UA change patterns and rates. This research indicates the necessity to implement change detection for better understanding the UA change patterns and rates. 1. INTRODUCTION 1.1 Urban Agriculture Urban agriculture (UA) is now one important type of urban land use/cover planning or an agricultural activities in urban areas. UA provides food, economic, social and environment (Goodman and Minner, 2019; Dieleman, 2017) that types of UA includes a diversity of agriculture in both hidden and obvious patterns that is depend on that urban area's location. Meaning of UA, generally, is briefly defined as the growing of urban food areas (

International Journal of Building, Urban, Interior and Landscape Technology (BUILT)

Green areas are so critical in urban communities for making environments healthier and mo... more Green areas are so critical in urban communities for making environments healthier and more livable. The objectives of this study were to assess sustainable green areas and to study their ecological niches in an urban education institute. Rajamangala University of Technology Isan (RMUTI) at Nakhonratchasima City Municipality (NCM) was selected as the study area. The spatial assessment of sustainable green areas used guidelines of the policy action plan for sustainable urban green area management by the Office of Natural Resources and Environmental Policy and Planning (ONEP) and then sustainable green areas were analyzed by the Ecological Niche Model (ENM) in Biomapper to check the distribution and durability of the existing trees to the current environment.The study found that sustainable green area in RMUTI at NCM is about 54.23% with 1,176 trees, which is in accordance with the policy action plan of ONEP that has suggested at least 30% of the land parcel being the sustaina...

Many cities has set goal of green city with tree increasing. The objective of this study is to as... more Many cities has set goal of green city with tree increasing. The objective of this study is to assess green city-based tree cover change in Nakhonratchasima City Municipality (NCM). In analysis, Google Earth (GE) imagery during 2012-2020 was used for visual interpretation but the result of Urban Tree Canopy (UTC) cover interpretation on GE image in year 2020 only was evaluated accuracy in field and was used to be the base map for supporting GE photo-interpretation in the past (2012-2019). The result of annually UTC cover layers would be taken to estimate air pollutants ((CO, NO 2 , O 3 , PM10, PM 2.5 and SO 2) via i-Tree Canopy on web. As results, the accuracy assessment of UTC cover map in year 2020 is 96.5517%. Tree cover change during the varying periods were found that there were ranged from dramatic reduction in percent tree cover of 17.2873% in year 2013 (because of built-up areas' increasing in that time) and slight reducing 0.0561% in year 2015 to an increase in percent tree cover of 0.3122% in year 2016 and 0.0488% in year 2017 while percent tree cover has been gradually decreased between 2018 and 2020. At the same time, NCM's UTC cover included the highest total removal value of CO (17.0 x 10-7 % per year) in year 2017; of NO 2 (74.0 x 10-7 % per year) in year 2013, 2014 and 2017; of O 3 (711.0 x 10-7 % per year) in year 2015; of PM10 (240.0 x 10-7 % per year) in year 2013 and 2014; of PM 2.5 (38.0 x 10-7 % per year) in year 2017; of SO 2 (48.0 x 10-7 % per year) in year 2013 and 2014. This assessment of such pollutant removal should not only be considered by tree cover but also the concerned factors (i.e., pollution concentrate, length of in-leaf season, amount of precipitation, and other meteorological variables). The mentioned results above, they will be used for spatial information for planning green city in area of NCM and guiding other green cities. Consequently, this study suggests for next work as: (1) study relationship between tree cover and land use/land cover and (2) study other related factors for UTC cover change.

The aim of the study is to evaluate suitable algorithm and datasets for land use and land cover (... more The aim of the study is to evaluate suitable algorithm and datasets for land use and land cover (LULC) classification in Chok Chai district of Nakhon Ratchasima province in Thailand. This study prepared 10 datasets (1 multispectral data and 9 texture measures data) that were used for LULC classification using supervised classification with Maximum Likelihood Classifier (MLC) and Artificial Neural Networks (ANN). Herein, all datasets were classified into 10 classes that consisted of (1) urban and built-up area, (2) paddy field, (3) cassava, (4) sugarcane, (5) eucalyptus, (6) orchard, (7) forest land, (8) water body, (9) scrub, and (10) abandon land. In addition, accuracy assessment of LULC classification in each dataset was performed with Overall Accuracy (OA) and Kappa hat coefficient of agreement ( ). As a result, MLC is suitable algorithm for combined datasets of multispectral data and texture measures because accuracy of all combined datasets was higher than ANN. Herewith multisp...

The IAFOR International Conference on Education – Hawaii 2020 Official Conference Proceedings, 2020

– The IAFOR International Conference on Sustainability, Energy & the Environment – Hawaii 2020 Official Conference Proceedings, 2020

International Journal of Building, Urban, Interior and Landscape Technology (BUILT), 2020

Many cities has set goal of green city with tree increasing. The objective of this study is to as... more Many cities has set goal of green city with tree increasing. The objective of this study is to assess green city-based tree cover change in Nakhonratchasima City Municipality (NCM). In analysis, Google Earth (GE) imagery during 2012-2020 was used for visual interpretation but the result of Urban Tree Canopy (UTC) cover interpretation on GE image in year 2020 only was evaluated accuracy in field and was used to be the base map for supporting GE photo-interpretation in the past (2012-2019). The result of annually UTC cover layers would be taken to estimate air pollutants ((CO, NO 2 , O 3 , PM10, PM 2.5 and SO 2) via i-Tree Canopy on web. As results, the accuracy assessment of UTC cover map in year 2020 is 96.5517%. Tree cover change during the varying periods were found that there were ranged from dramatic reduction in percent tree cover of 17.2873% in year 2013 (because of built-up areas' increasing in that time) and slight reducing 0.0561% in year 2015 to an increase in percent tree cover of 0.3122% in year 2016 and 0.0488% in year 2017 while percent tree cover has been gradually decreased between 2018 and 2020. At the same time, NCM's UTC cover included the highest total removal value of CO (17.0 x 10-7 % per year) in year 2017; of NO 2 (74.0 x 10-7 % per year) in year 2013, 2014 and 2017; of O 3 (711.0 x 10-7 % per year) in year 2015; of PM10 (240.0 x 10-7 % per year) in year 2013 and 2014; of PM 2.5 (38.0 x 10-7 % per year) in year 2017; of SO 2 (48.0 x 10-7 % per year) in year 2013 and 2014. This assessment of such pollutant removal should not only be considered by tree cover but also the concerned factors (i.e., pollution concentrate, length of in-leaf season, amount of precipitation, and other meteorological variables). The mentioned results above, they will be used for spatial information for planning green city in area of NCM and guiding other green cities. Consequently, this study suggests for next work as: (1) study relationship between tree cover and land use/land cover and (2) study other related factors for UTC cover change.

Ranked road sections in terms of risk together with ranked weights of factors considered to cause... more Ranked road sections in terms of risk together with ranked weights of factors considered to cause accident for each section are highly effectual information for road safety implementing planning. To achieve this goal, 36 road sections from 5 highways in Nakhon Ratchasima, Thailand with varying slopes, surface widths, and a number of connection routes, initially selected from 166 sections by using 3-year accident data, are ranked into order from the highest risk to the lowest risk using ordered weight averaging (OWA) decision rule. OWA is a multi-criteria evaluation procedure using combination operators. Apart from risk ranking of road sections, the result shows that slope is considered to be the highest rank among risk factors for 16 sections, while 15 and 5 sections are for the number of connection routes and surface width respectively. In addition, a number of ranking sections within each certain highway can be obtained i.e. 17, 12, 3, 2, and 2 sections for highway no. 205, 207, 2...

Ranked road sections in terms of risk together with ranked weights of factors considered to cause... more Ranked road sections in terms of risk together with ranked weights of factors considered to cause accident for each section are highly effectual information for road safety implementing planning. To achieve this goal, 36 road sections from 5 highways in Nakhon Ratchasima, Thailand with varying slopes, surface widths, and a number of connection routes, initially selected from 166 sections by using 3-year accident data, are ranked into order from the highest risk to the lowest risk using ordered weight averaging (OWA) decision rule. OWA is a multi-criteria evaluation procedure using combination operators. Apart from risk ranking of road sections, the result shows that slope is considered to be the highest rank among risk factors for 16 sections, while 15 and 5 sections are for the number of connection routes and surface width respectively. In addition, a number of ranking sections within each certain highway can be obtained i.e. 17, 12, 3, 2, and 2 sections for highway no. 205, 207, 2...

This paper aims to assess the effect of incorporating topographical data with geostatistical inte... more This paper aims to assess the effect of incorporating topographical data with geostatistical interpolation for monthly rainfall and temperature in Ping Basin, Thailand. The spatial interpolation techniques based on 11 semivariogram models of 4 main sub-types of cokriging with 3 topographical variables: elevation, longitude, and latitude have been applied in this study. The best interpolation models from cokriging technique on mean monthly rainfall and mean monthly temperature are selected by Akaike Information Criterion (AIC) based on partial sill, range and nugget that the best monthly models of kriging technique is operated in same mentioned selection. In addition, an assessment of the effective results of the cokriging interpolation models is performed by 2 approaches: i) comparing the errors of the best results from other interpolations excluding topographic data with the least MAE, MRE and RMSE value and ii) comparing the accuracy of results from Multiple Linear Regression (MLR...