Suwit Ongsomwang | SURANAREE UNIVERSITY OF TECHNOLOGY (original) (raw)
Papers by Suwit Ongsomwang
ISPRS international journal of geo-information, Jan 21, 2020
An understanding of historical and present land use and land cover (LULC) information and its cha... more An understanding of historical and present land use and land cover (LULC) information and its changes, such as urbanization and urban growth, is critical for city planners, land managers and resource managers in any rapidly changing landscape. To deal with this situation, the development of a new supervised classification method for multitemporal LULC mapping with long-term reliable information is necessary. The ultimate goal of this study was to develop a new classification method using harmonic analysis with a minimum spectral distance algorithm for multitemporal LULC mapping. Here, the Jiangning District of Nanjing City, Jiangsu Province, China was chosen as the study area. The research methodology consisted of two main components: (1) Landsat data selection and time-series spectral reflectance reconstruction and (2) multitemporal LULC classification using HA with a minimum spectral distance algorithm. The results revealed that the overall accuracy and
The study of land use and land cover simulation using the integration of geospatial models is ver... more The study of land use and land cover simulation using the integration of geospatial models is very important in various aspects, especially sustainable use with minimum environmental impact. The main objectives of the study were: 1) to assess historical and recent LULC and its changes; 2) to simulate 3 different LULC scenarios using the CLUES model; 3) to assess soil erosion, water yield, and economic value and their changes; and 4) to allocate the optimum land use for 3 different scenarios. The 4 main components of the research methodology implemented here included: 1) data collection and preparation; 2) LULC simulation of 3 different scenarios; 3) soil erosion, water yield, and economic value assessment and their changes; and 4) the optimum land use allocation of 3 different scenarios. From the results of the LULC assessment between 2003 to 2013, urban and built-up land, cassava, sugarcane, water body, and miscellaneous land had increased while maize, perennial tree/orchard, and forest land had decreased. The most common important driving factor for location preference of the LULC types was population density. The simulation of 3 LULC scenarios in 2023 by the CLUES model revealed that urban and built-up land, cassava, sugarcane, water body and miscellaneous land would increase while maize, perennial tree/orchard, and forest land would decrease under Scenario I (Historical land use evolution). At the same time, the increase in cassava and sugarcane under Scenario II (Energy crop extension) came from maize, forest land, and miscellaneous land while most of the increasing forest land under Scenario III (Forest conservation and prevention) was converted from maize, sugarcane, and miscellaneous land. The optimum land use allocation of the 3 scenarios indicated that most of the agricultural land and forest land of Scenario I was allocated into the moderate and high suitability classes, respectively. In the meantime, most of the cassava and sugarcane as energy crops of Scenario II were located in the low and moderate suitability classes and moderate and high suitability classes, respectively, while the forest land with restriction rules was located in the high suitability class. Under Scenario III, the forest land was allocated in the moderate and high suitability classes and the agricultural land was distributed throughout all the suitability classes. On the basis of these results, it is suggested that the integration of the LULC change model (CLUE-S model), soil erosion model (USLE model), hydrologic model (SWAT model and SCS-CN method), and economic value measures (PV model) can be efficiently used as a tool for optimum land use allocation by considering LULC change and its impact from different scenarios.
DDF (dry dipterocarp forest) is importantly deciduous forest type in Thailand since it consists o... more DDF (dry dipterocarp forest) is importantly deciduous forest type in Thailand since it consists of important tree species for timber products and non-timber products. So, people would like to come to use these products for daily uses in this forest type. The main aim of this study is to evaluate significant biophysical factors for DDF distribution using factor analysis and to model DDF distribution using ENFA (ecological niche factor analysis). In this study, 13 watersheds of Ping Basin in northern Thailand were selected as the study site based on availability of forest inventory data in 2007 from DNP (Department of National Parks, Wildlife and Plant Conservation). Basic biophysical data for data analysis included forest inventory data (179 DDF plots), 10 climatic data, three topographic data, and one soil data. For identification and evaluation of biophysical factors for DDF distribution using factor analysis, the first three factors, namely DDF-1, DDF-2 and DDF-3, had been extracted with 95.35% of total variance. These three components were used to predict DDF distribution based on HS (habitat suitability) with ENFA. In practice, the results were validated with AVI (absolute validation index) and CVI (contrast validation index) with validated forest inventory dataset. This evaluation shows that DDF-2 model is the best HS data consisting of four physical factors (mean annually temperature, mean monthly maximum temperature, mean monthly minimum temperature, and elevation), which is able to effectively used for habitat suitability for DDF distribution prediction. It was found that habitat suitability for DDF distribution can be classified into four classes including high suitable habitat, moderate suitable habitat, low suitable habitat, and unsuitable habitat. As a result, DDF distributions with high suitable habitat are highly related with DDF forest inventory plots of DNP. Thus, the obtained output can be further used for DDF rehabilitation according to climate and topographic factors.
Applied Sciences
Salt mining and shrimp farming have been practiced in the Non Thai district and the surrounding a... more Salt mining and shrimp farming have been practiced in the Non Thai district and the surrounding areas for more than 30 years, creating saline soil problems. To solve the soil salinity problem, soil salinity prediction and mapping utilizing the electromagnetic induction method (EMI) and spatial interpolation methods were examined in the Non Thai district, Nakhon Ratchasima province, Thailand. The research objectives were (1) to predict soil salinity using spatial interpolation methods and (2) to identify a suitable spatial interpolation method for soil salinity severity mapping. The research methodology consisted of five steps: apparent electrical conductivity (ECa) measurement using an electromagnetic induction (EMI) method; in situ soil sample collection and electrical conductivity of the saturated soil paste extract (ECe) measurement; soil electrical conductivity estimation using linear regression analysis (LRA); soil salinity prediction and accuracy assessment; and soil salinity ...
Applications of LST data to advanced research on UHI phenomena and its intensity are still relati... more Applications of LST data to advanced research on UHI phenomena and its intensity are still relatively low in Thailand. The main objectives of this study are (1) to extract and predict LST data associated with urban and non-urban areas from Landsat imageries and (2) to quantify the intensity of UHI phenomena and its changes over BMV between 2006 and 2026. The research methodology was conducted systematically to extract and predict the LST associated with the urban and non-urban areas in order to assess the intensity of UHI phenomena. The results show that WAI as UHI intensity is extremely critical between 2006 and 2022 and becomes critically severe during 2024 and 2026. The result also show that URI as a degree of UHI development has increased from 2010 to 2016, however, it will suddenly decrease in 2018 and continuously increase between 2020 and 2026. In addition, TGCI analysis indicates that a decreasing temperature trend is dominant in the existing urban areas while an increasing temperature trend shows remarkably in urban expansion areas. These findings confirm the impacts of urbanization and urban development state on UHI intensity. In conclusion, the approaches and results of this study can be applied to master the urban planning properly, especially the mitigation of UHI phenomena in the future.
Atmosphere
Spatiotemporal particulate matter (PM) concentration prediction using MODIS AOD with significant ... more Spatiotemporal particulate matter (PM) concentration prediction using MODIS AOD with significant PM factors in rural and urban landscapes in Thailand is necessary for public health and has been complicated by the limitations of PM monitoring stations. The research objectives were (1) to identify significant factors affecting PM10 concentrations in rural landscapes and PM2.5 in urban landscapes; (2) to predict spatiotemporal PM10 and PM2.5 concentrations using geographically weighted regression (GWR) and mixed-effect model (MEM), and (3) to evaluate a suitable spatiotemporal model for PM10 and PM2.5 concentration prediction and validation. The research methodology consisted of four stages: data collection and preparation, the identification of significant spatiotemporal factors affecting PM concentrations, the prediction of spatiotemporal PM concentrations, and a suitable spatiotemporal model for PM concentration prediction and validation. As a result, the predicted PM10 concentratio...
The integration of RS/GIS with Universal Soil Loss Equation (USLE) for soil erosion assessment ha... more The integration of RS/GIS with Universal Soil Loss Equation (USLE) for soil erosion assessment has been carried out in Upper Lam Phra Phloeng watershed in Nakhon Ratchasima. The study basically aimed to spatially model soil loss to be used for soil conservation purposes. Herewith, two Landsat-5 TM imageries in 2000 and 2008 were classified by using hybrid techniques for land use and land cover classes for vegetation cover and field support practice factors of USLE. Also, other USLE factors which included rainfall-runoff erosivity, slope length and steepness and erodibility were extracted based on mean annual rainfall, DEM, soil and geological data. The land use and land cover in 2000 and 2008 were extracted with their change. Soil loss maps in 2000 and 2008 were produced based on USLE indicated the amount of soil loss in 2000 was more than 2008. Furthermore, severity of soil loss was reclassified into 5 classes: very low, low, moderate, severe and very severe. The result obtained 19...
Pan-sharpening is a well-known technique used to fuse the high spatial resolution panchromatic im... more Pan-sharpening is a well-known technique used to fuse the high spatial resolution panchromatic image and the low spatial resolution multispectral image to produce a high spatial resolution multispectral image. This paper will present the quantitative evaluation of THEOS image pan-sharpening methods by means of a Quality Indices (QI). The pan-sharpening methods which consist of Brovey transformation (BT), Multiplicative transformation (MT), Principle Component Analysis (PCA), Intensity-Hue-Saturation (IHS), High Pass Filter (HPF), and Wavelet transformation were here investigated. The QI include Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative shift of Means (RM), Relative Average Spectral Error (RASE), and Relative dimensionless global error in synthesis (ERGAS) were used to evaluate the pan-sharpening methods. According to the experimental results, it is possible to evaluate the pan-sharpening methods by means of the quantitative measurement and the HPF method ...
The study of land use and land cover simulation using the integration of geospatial models is ver... more The study of land use and land cover simulation using the integration of geospatial models is very important in various aspects, especially sustainable use with minimum environmental impact. The main objectives of the study were: 1) to assess historical and recent LULC and its changes; 2) to simulate 3 different LULC scenarios using the CLUE-S model; 3) to assess soil erosion, water yield, and economic value and their changes; and 4) to allocate the optimum land use for 3 different scenarios. The 4 main components of the research methodology implemented here included: 1) data collection and preparation; 2) LULC simulation of 3 different scenarios; 3) soil erosion, water yield, and economic value assessment and their changes; and 4) the optimum land use allocation of 3 different scenarios. From the results of the LULC assessment between 2003 to 2013, urban and built-up land, cassava, sugarcane, water body, and miscellaneous land had increased while maize, perennial tree/orchard, and ...
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...
... Instead, the difficulty in discriminating mangroves when using near-infrared spectral informa... more ... Instead, the difficulty in discriminating mangroves when using near-infrared spectral information was probably caused by a characteristic of plants in general: they have little absorption on the electromagnetic wave of this region (Kumar et al., 2001). ...
This research aims to investigate forest landscape pattern changes in the Sakaerat Biosphere Rese... more This research aims to investigate forest landscape pattern changes in the Sakaerat Biosphere Reserve (SBR), and to classify and assess changes of multi-temporal forest landscape types, and analyze patterns using landscape metrics from 1980-2010. Landscape classification and assessment of 6 landscape types showed the natural forest landscape was the major landscape type and occupied an area of 46.23% to 44.40%. Landscape changes had occurred mostly in disturbed forest, decreasing from 10.22% to 3.99%, while forest plantations and urban and built-up landscapes increased from 1.61% to 3.71% and 1.36% to 2.98%, respectively. More importantly, the number of patches, mean proximity, and interspersion juxtaposition indices assisted in determining the forest landscape pattern changes. The trends of change in the indices’ values of forest landscape types were subsequently used in relation to gains and losses in the context of forest landscape ecology to set up the priority levels of recommen...
The aim of this study was to test the performance of hyperspectral data in discriminating mangrov... more The aim of this study was to test the performance of hyperspectral data in discriminating mangroves at the species level. First, spectral responses between 350 nm and 2500 nm of 16 Thai tropical mangrove species were recorded from the leaves, using a field spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested to see whether they significantly differed at every spectral location. Finally, the spectral separability between each pair of mangrove species was quantified using the J-M distance measure. The results demonstrated that the mangrove species were spectrally separable, and we therefore anticipate the use of hyperspectral sensors for mangrove species classification.
Land
Floods represent one of the most severe natural disasters threatening the development of human so... more Floods represent one of the most severe natural disasters threatening the development of human society worldwide, including in Thailand. In recent decades, Chaiyaphum province has experienced a problem with flooding almost every year. In particular, the flood in 2010 caused property damage of 495 million Baht, more than 322,000 persons were affected, and approximately 1046.4 km2 of productive agricultural area was affected. Therefore, this study examined how to optimize land use and land cover allocation for flood mitigation using land use change and hydrological models with optimization methods. This research aimed to allocate land use and land cover (LULC) to minimize the surface for flood mitigation in Mueang Chaiyaphum district, Chaiyaphum province, Thailand. The research methodology consisted of six stages: data collection and preparation, LULC classification, LULC prediction, surface runoff estimation, the optimization of LULC allocation for flood mitigation and mapping, and e...
Soil properties are one of the most important categories of information for land management and e... more Soil properties are one of the most important categories of information for land management and environmental modeling. Unfortunately, soil properties in mountainous areas with slopes of more than 35% are rarely investigated in Thailand due to the complexity of their landscapes and the cost and time requirements. The main objective was to predict soil properties in mountainous areas relating to soil forming factors using partial least squares regression (PLSR). The combination of topographic position index values from two different scales and criteria sets was fi rstly used to classify landform for in situ soil survey. Then, analyzed soil properties of the topsoil and subsoil (sand, silt, clay, pH, organic matter, total N, available P, exchangeable K, cation exchange capacity (CEC) and base saturation) and soil forming factors (rainfall, normalized difference vegetation index, elevation, slope, aspect, plan curvature, profi le curvature, curvature, topographic wetness index and Al/S...
ISPRS International Journal of Geo-Information
Land surface temperature (LST) is an essential parameter in the climate system whose dynamics ind... more Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 ...
A variety of land use and its change plays a vital role in the water quality of lakes. Especially... more A variety of land use and its change plays a vital role in the water quality of lakes. Especially, urban and built-up and cultivated areas influence the water quality within the lake basin. To understand sediment and nutrient processes using sediment delivery ratio (SDR) and nutrient delivery ratio (NDR) models under the InVEST software suite, sediment export and nutrient export were examined in the Upper Ing watershed. The specific objective was to estimate sediment and nutrient exports and to compare their results. The research methodology consisted of three components: data collection and preparation, sediment export estimation and nutrient export estimation, and sediment and nutrient export comparison. The results discovered that average sediment export in Upper Ing Watershed in 2009 and 2015 were about 116 tons and 47 tons, respectively. This finding indicates the effect of rainfall erosivity sediment export in the watershed. Meanwhile, average nitrogen (N) export in 2009 and 2...
The aim of this study was to test the performance of hyperspectral data in discriminating mangrov... more The aim of this study was to test the performance of hyperspectral data in discriminating mangroves at the species level. First, spectral responses between 350 nm and 2500 nm of 16 Thai tropical mangrove species were recorded from the leaves, using a field spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested to see whether they significantly differed at every spectral location. Finally, the spectral separability between each pair of mangrove species was quantified using the J-M distance measure. The results demonstrated that the mangrove species were spectrally separable, and we therefore anticipate the use of hyperspectral sensors for mangrove species classification.
The flood, which represents one of the most severe natural disasters around the world, has caused... more The flood, which represents one of the most severe natural disasters around the world, has caused enormous losses to economies, societies, and ecological environments. To deal with this situation, land use and land cover (LULC) allocation using a Goal programming was here examined to reduce surface runoff for flood mitigation. The specific objectives of the case study were to estimate surface runoff using the SCS-CN method and to allocate optimized LULC to minimize surface runoff using Goal programming. The primary research methodology consisted of three components: data collection and preparation, surface runoff estimation, and LULC allocation for flood mitigation. The results revealed that the surface runoff volume in three different years (2008, 2011, and 2015) varied from 1,767 million m3 in 2015 to 4,726 million m3 in 2008. Accordingly, the pattern of surface runoff and rainfall from three different years was similar. The surface runoff had a high positive correlation with annu...
ISPRS international journal of geo-information, Jan 21, 2020
An understanding of historical and present land use and land cover (LULC) information and its cha... more An understanding of historical and present land use and land cover (LULC) information and its changes, such as urbanization and urban growth, is critical for city planners, land managers and resource managers in any rapidly changing landscape. To deal with this situation, the development of a new supervised classification method for multitemporal LULC mapping with long-term reliable information is necessary. The ultimate goal of this study was to develop a new classification method using harmonic analysis with a minimum spectral distance algorithm for multitemporal LULC mapping. Here, the Jiangning District of Nanjing City, Jiangsu Province, China was chosen as the study area. The research methodology consisted of two main components: (1) Landsat data selection and time-series spectral reflectance reconstruction and (2) multitemporal LULC classification using HA with a minimum spectral distance algorithm. The results revealed that the overall accuracy and
The study of land use and land cover simulation using the integration of geospatial models is ver... more The study of land use and land cover simulation using the integration of geospatial models is very important in various aspects, especially sustainable use with minimum environmental impact. The main objectives of the study were: 1) to assess historical and recent LULC and its changes; 2) to simulate 3 different LULC scenarios using the CLUES model; 3) to assess soil erosion, water yield, and economic value and their changes; and 4) to allocate the optimum land use for 3 different scenarios. The 4 main components of the research methodology implemented here included: 1) data collection and preparation; 2) LULC simulation of 3 different scenarios; 3) soil erosion, water yield, and economic value assessment and their changes; and 4) the optimum land use allocation of 3 different scenarios. From the results of the LULC assessment between 2003 to 2013, urban and built-up land, cassava, sugarcane, water body, and miscellaneous land had increased while maize, perennial tree/orchard, and forest land had decreased. The most common important driving factor for location preference of the LULC types was population density. The simulation of 3 LULC scenarios in 2023 by the CLUES model revealed that urban and built-up land, cassava, sugarcane, water body and miscellaneous land would increase while maize, perennial tree/orchard, and forest land would decrease under Scenario I (Historical land use evolution). At the same time, the increase in cassava and sugarcane under Scenario II (Energy crop extension) came from maize, forest land, and miscellaneous land while most of the increasing forest land under Scenario III (Forest conservation and prevention) was converted from maize, sugarcane, and miscellaneous land. The optimum land use allocation of the 3 scenarios indicated that most of the agricultural land and forest land of Scenario I was allocated into the moderate and high suitability classes, respectively. In the meantime, most of the cassava and sugarcane as energy crops of Scenario II were located in the low and moderate suitability classes and moderate and high suitability classes, respectively, while the forest land with restriction rules was located in the high suitability class. Under Scenario III, the forest land was allocated in the moderate and high suitability classes and the agricultural land was distributed throughout all the suitability classes. On the basis of these results, it is suggested that the integration of the LULC change model (CLUE-S model), soil erosion model (USLE model), hydrologic model (SWAT model and SCS-CN method), and economic value measures (PV model) can be efficiently used as a tool for optimum land use allocation by considering LULC change and its impact from different scenarios.
DDF (dry dipterocarp forest) is importantly deciduous forest type in Thailand since it consists o... more DDF (dry dipterocarp forest) is importantly deciduous forest type in Thailand since it consists of important tree species for timber products and non-timber products. So, people would like to come to use these products for daily uses in this forest type. The main aim of this study is to evaluate significant biophysical factors for DDF distribution using factor analysis and to model DDF distribution using ENFA (ecological niche factor analysis). In this study, 13 watersheds of Ping Basin in northern Thailand were selected as the study site based on availability of forest inventory data in 2007 from DNP (Department of National Parks, Wildlife and Plant Conservation). Basic biophysical data for data analysis included forest inventory data (179 DDF plots), 10 climatic data, three topographic data, and one soil data. For identification and evaluation of biophysical factors for DDF distribution using factor analysis, the first three factors, namely DDF-1, DDF-2 and DDF-3, had been extracted with 95.35% of total variance. These three components were used to predict DDF distribution based on HS (habitat suitability) with ENFA. In practice, the results were validated with AVI (absolute validation index) and CVI (contrast validation index) with validated forest inventory dataset. This evaluation shows that DDF-2 model is the best HS data consisting of four physical factors (mean annually temperature, mean monthly maximum temperature, mean monthly minimum temperature, and elevation), which is able to effectively used for habitat suitability for DDF distribution prediction. It was found that habitat suitability for DDF distribution can be classified into four classes including high suitable habitat, moderate suitable habitat, low suitable habitat, and unsuitable habitat. As a result, DDF distributions with high suitable habitat are highly related with DDF forest inventory plots of DNP. Thus, the obtained output can be further used for DDF rehabilitation according to climate and topographic factors.
Applied Sciences
Salt mining and shrimp farming have been practiced in the Non Thai district and the surrounding a... more Salt mining and shrimp farming have been practiced in the Non Thai district and the surrounding areas for more than 30 years, creating saline soil problems. To solve the soil salinity problem, soil salinity prediction and mapping utilizing the electromagnetic induction method (EMI) and spatial interpolation methods were examined in the Non Thai district, Nakhon Ratchasima province, Thailand. The research objectives were (1) to predict soil salinity using spatial interpolation methods and (2) to identify a suitable spatial interpolation method for soil salinity severity mapping. The research methodology consisted of five steps: apparent electrical conductivity (ECa) measurement using an electromagnetic induction (EMI) method; in situ soil sample collection and electrical conductivity of the saturated soil paste extract (ECe) measurement; soil electrical conductivity estimation using linear regression analysis (LRA); soil salinity prediction and accuracy assessment; and soil salinity ...
Applications of LST data to advanced research on UHI phenomena and its intensity are still relati... more Applications of LST data to advanced research on UHI phenomena and its intensity are still relatively low in Thailand. The main objectives of this study are (1) to extract and predict LST data associated with urban and non-urban areas from Landsat imageries and (2) to quantify the intensity of UHI phenomena and its changes over BMV between 2006 and 2026. The research methodology was conducted systematically to extract and predict the LST associated with the urban and non-urban areas in order to assess the intensity of UHI phenomena. The results show that WAI as UHI intensity is extremely critical between 2006 and 2022 and becomes critically severe during 2024 and 2026. The result also show that URI as a degree of UHI development has increased from 2010 to 2016, however, it will suddenly decrease in 2018 and continuously increase between 2020 and 2026. In addition, TGCI analysis indicates that a decreasing temperature trend is dominant in the existing urban areas while an increasing temperature trend shows remarkably in urban expansion areas. These findings confirm the impacts of urbanization and urban development state on UHI intensity. In conclusion, the approaches and results of this study can be applied to master the urban planning properly, especially the mitigation of UHI phenomena in the future.
Atmosphere
Spatiotemporal particulate matter (PM) concentration prediction using MODIS AOD with significant ... more Spatiotemporal particulate matter (PM) concentration prediction using MODIS AOD with significant PM factors in rural and urban landscapes in Thailand is necessary for public health and has been complicated by the limitations of PM monitoring stations. The research objectives were (1) to identify significant factors affecting PM10 concentrations in rural landscapes and PM2.5 in urban landscapes; (2) to predict spatiotemporal PM10 and PM2.5 concentrations using geographically weighted regression (GWR) and mixed-effect model (MEM), and (3) to evaluate a suitable spatiotemporal model for PM10 and PM2.5 concentration prediction and validation. The research methodology consisted of four stages: data collection and preparation, the identification of significant spatiotemporal factors affecting PM concentrations, the prediction of spatiotemporal PM concentrations, and a suitable spatiotemporal model for PM concentration prediction and validation. As a result, the predicted PM10 concentratio...
The integration of RS/GIS with Universal Soil Loss Equation (USLE) for soil erosion assessment ha... more The integration of RS/GIS with Universal Soil Loss Equation (USLE) for soil erosion assessment has been carried out in Upper Lam Phra Phloeng watershed in Nakhon Ratchasima. The study basically aimed to spatially model soil loss to be used for soil conservation purposes. Herewith, two Landsat-5 TM imageries in 2000 and 2008 were classified by using hybrid techniques for land use and land cover classes for vegetation cover and field support practice factors of USLE. Also, other USLE factors which included rainfall-runoff erosivity, slope length and steepness and erodibility were extracted based on mean annual rainfall, DEM, soil and geological data. The land use and land cover in 2000 and 2008 were extracted with their change. Soil loss maps in 2000 and 2008 were produced based on USLE indicated the amount of soil loss in 2000 was more than 2008. Furthermore, severity of soil loss was reclassified into 5 classes: very low, low, moderate, severe and very severe. The result obtained 19...
Pan-sharpening is a well-known technique used to fuse the high spatial resolution panchromatic im... more Pan-sharpening is a well-known technique used to fuse the high spatial resolution panchromatic image and the low spatial resolution multispectral image to produce a high spatial resolution multispectral image. This paper will present the quantitative evaluation of THEOS image pan-sharpening methods by means of a Quality Indices (QI). The pan-sharpening methods which consist of Brovey transformation (BT), Multiplicative transformation (MT), Principle Component Analysis (PCA), Intensity-Hue-Saturation (IHS), High Pass Filter (HPF), and Wavelet transformation were here investigated. The QI include Correlation Coefficient (CC), Root Mean Square Error (RMSE), Relative shift of Means (RM), Relative Average Spectral Error (RASE), and Relative dimensionless global error in synthesis (ERGAS) were used to evaluate the pan-sharpening methods. According to the experimental results, it is possible to evaluate the pan-sharpening methods by means of the quantitative measurement and the HPF method ...
The study of land use and land cover simulation using the integration of geospatial models is ver... more The study of land use and land cover simulation using the integration of geospatial models is very important in various aspects, especially sustainable use with minimum environmental impact. The main objectives of the study were: 1) to assess historical and recent LULC and its changes; 2) to simulate 3 different LULC scenarios using the CLUE-S model; 3) to assess soil erosion, water yield, and economic value and their changes; and 4) to allocate the optimum land use for 3 different scenarios. The 4 main components of the research methodology implemented here included: 1) data collection and preparation; 2) LULC simulation of 3 different scenarios; 3) soil erosion, water yield, and economic value assessment and their changes; and 4) the optimum land use allocation of 3 different scenarios. From the results of the LULC assessment between 2003 to 2013, urban and built-up land, cassava, sugarcane, water body, and miscellaneous land had increased while maize, perennial tree/orchard, and ...
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...
... Instead, the difficulty in discriminating mangroves when using near-infrared spectral informa... more ... Instead, the difficulty in discriminating mangroves when using near-infrared spectral information was probably caused by a characteristic of plants in general: they have little absorption on the electromagnetic wave of this region (Kumar et al., 2001). ...
This research aims to investigate forest landscape pattern changes in the Sakaerat Biosphere Rese... more This research aims to investigate forest landscape pattern changes in the Sakaerat Biosphere Reserve (SBR), and to classify and assess changes of multi-temporal forest landscape types, and analyze patterns using landscape metrics from 1980-2010. Landscape classification and assessment of 6 landscape types showed the natural forest landscape was the major landscape type and occupied an area of 46.23% to 44.40%. Landscape changes had occurred mostly in disturbed forest, decreasing from 10.22% to 3.99%, while forest plantations and urban and built-up landscapes increased from 1.61% to 3.71% and 1.36% to 2.98%, respectively. More importantly, the number of patches, mean proximity, and interspersion juxtaposition indices assisted in determining the forest landscape pattern changes. The trends of change in the indices’ values of forest landscape types were subsequently used in relation to gains and losses in the context of forest landscape ecology to set up the priority levels of recommen...
The aim of this study was to test the performance of hyperspectral data in discriminating mangrov... more The aim of this study was to test the performance of hyperspectral data in discriminating mangroves at the species level. First, spectral responses between 350 nm and 2500 nm of 16 Thai tropical mangrove species were recorded from the leaves, using a field spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested to see whether they significantly differed at every spectral location. Finally, the spectral separability between each pair of mangrove species was quantified using the J-M distance measure. The results demonstrated that the mangrove species were spectrally separable, and we therefore anticipate the use of hyperspectral sensors for mangrove species classification.
Land
Floods represent one of the most severe natural disasters threatening the development of human so... more Floods represent one of the most severe natural disasters threatening the development of human society worldwide, including in Thailand. In recent decades, Chaiyaphum province has experienced a problem with flooding almost every year. In particular, the flood in 2010 caused property damage of 495 million Baht, more than 322,000 persons were affected, and approximately 1046.4 km2 of productive agricultural area was affected. Therefore, this study examined how to optimize land use and land cover allocation for flood mitigation using land use change and hydrological models with optimization methods. This research aimed to allocate land use and land cover (LULC) to minimize the surface for flood mitigation in Mueang Chaiyaphum district, Chaiyaphum province, Thailand. The research methodology consisted of six stages: data collection and preparation, LULC classification, LULC prediction, surface runoff estimation, the optimization of LULC allocation for flood mitigation and mapping, and e...
Soil properties are one of the most important categories of information for land management and e... more Soil properties are one of the most important categories of information for land management and environmental modeling. Unfortunately, soil properties in mountainous areas with slopes of more than 35% are rarely investigated in Thailand due to the complexity of their landscapes and the cost and time requirements. The main objective was to predict soil properties in mountainous areas relating to soil forming factors using partial least squares regression (PLSR). The combination of topographic position index values from two different scales and criteria sets was fi rstly used to classify landform for in situ soil survey. Then, analyzed soil properties of the topsoil and subsoil (sand, silt, clay, pH, organic matter, total N, available P, exchangeable K, cation exchange capacity (CEC) and base saturation) and soil forming factors (rainfall, normalized difference vegetation index, elevation, slope, aspect, plan curvature, profi le curvature, curvature, topographic wetness index and Al/S...
ISPRS International Journal of Geo-Information
Land surface temperature (LST) is an essential parameter in the climate system whose dynamics ind... more Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 ...
A variety of land use and its change plays a vital role in the water quality of lakes. Especially... more A variety of land use and its change plays a vital role in the water quality of lakes. Especially, urban and built-up and cultivated areas influence the water quality within the lake basin. To understand sediment and nutrient processes using sediment delivery ratio (SDR) and nutrient delivery ratio (NDR) models under the InVEST software suite, sediment export and nutrient export were examined in the Upper Ing watershed. The specific objective was to estimate sediment and nutrient exports and to compare their results. The research methodology consisted of three components: data collection and preparation, sediment export estimation and nutrient export estimation, and sediment and nutrient export comparison. The results discovered that average sediment export in Upper Ing Watershed in 2009 and 2015 were about 116 tons and 47 tons, respectively. This finding indicates the effect of rainfall erosivity sediment export in the watershed. Meanwhile, average nitrogen (N) export in 2009 and 2...
The aim of this study was to test the performance of hyperspectral data in discriminating mangrov... more The aim of this study was to test the performance of hyperspectral data in discriminating mangroves at the species level. First, spectral responses between 350 nm and 2500 nm of 16 Thai tropical mangrove species were recorded from the leaves, using a field spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested to see whether they significantly differed at every spectral location. Finally, the spectral separability between each pair of mangrove species was quantified using the J-M distance measure. The results demonstrated that the mangrove species were spectrally separable, and we therefore anticipate the use of hyperspectral sensors for mangrove species classification.
The flood, which represents one of the most severe natural disasters around the world, has caused... more The flood, which represents one of the most severe natural disasters around the world, has caused enormous losses to economies, societies, and ecological environments. To deal with this situation, land use and land cover (LULC) allocation using a Goal programming was here examined to reduce surface runoff for flood mitigation. The specific objectives of the case study were to estimate surface runoff using the SCS-CN method and to allocate optimized LULC to minimize surface runoff using Goal programming. The primary research methodology consisted of three components: data collection and preparation, surface runoff estimation, and LULC allocation for flood mitigation. The results revealed that the surface runoff volume in three different years (2008, 2011, and 2015) varied from 1,767 million m3 in 2015 to 4,726 million m3 in 2008. Accordingly, the pattern of surface runoff and rainfall from three different years was similar. The surface runoff had a high positive correlation with annu...