A New Landscape Classification Approach for Quantifying Spatial Pattern of Bac Kan Province, Vietnam

Landscape theory and its application have played an important role in natural resources exploitation and environmental protection. Various classification approaches had been employed worldwide in landscape ecology studies. This paper had developed a new hierarchical landscape classification framework for quantifying spatial pattern of Bac Kan province. A landscape formation equation was applied with three natural factors (geology, topography, and soil) and cultural factor (land use). A multi-level segmentation technique with multiresolution segmentation algorithm was chosen to segment landscape units (patches) and to categorize landscape types at different levels. The results revealed that the landscape classification of Bac Kan province has 4 hierarchical levels. Level 4, which provided full details of spatial pattern based on geologic period, elevation, soil depth, and land use, had 315 landscape types. At this level, there are 8,427 landscape units mapped with a minimum and maximum areas of 0.02 km2 and 116.63 km2, respectively. A new Bac Kan landscape map at a scale of 1:100,000 along with 16 different attributes for each landscape unit was also produced. In conclusion, the framework of research methodology presented in this paper can be used as a guideline for landscape classification at provincial and national levels

Spatio-Temporal Urban Heat Island Phenomena Assessment using Landsat Imagery: A Case Study of Bangkok Metropolitan and its Vicinity, Thailand

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

Fundamental of Remote Sensing and Digital image process

หนึ่งอาจารย์หนึ่งผลงาน ประจำปี 255

Remote Sensing and Geospatial Models to Simulate Land Use and Land Cover and Estimate Water Supply and Demand for Water Balancing in Phuket Island, Thailand

Currently, Phuket Island is facing water scarcity because water demand for consumption was approximately 51 million m3/year, whereas water supply was only about 46 million m3/year. Thus, the study of water supply, demand and balancing are important for effective water resources management. This study aims to simulate the LULC data using the CLUE-S model, estimate water supply using the SWAT model, and calculate water demand using a water footprint basis for water balancing on the Island. In addition, tourist water demand was separately estimated under normal and new normal conditions (COVID-19 pandemic) to fit with the actual situation at national and international levels. Water balance results with the consideration of ecological water requirements suggest that a water deficit occurs every year under the dry year scenario in normal and new normal conditions. In addition, the monthly water balance indicates that a water deficit occurs in the summer season every year, both without and with the consideration of ecological water requirements. Consequently, it can be concluded that remote sensing data with advanced geospatial models can provide essential information about water supply, demand, and balance for water resources management, particularly water scarcity, in Phuket Island in the future. Additionally, this study’s conceptual framework and research workflows can assist government agencies in examining water deficits in other areas

Soil Salinity Prediction and Its Severity Mapping Using a Suitable Interpolation Method on Data Collected by Electromagnetic Induction Method

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 severity classification and overlay analysis with relevant data. The result of LRA showed a strong positive relationship between ECe and ECa. The correlation coefficient (R) values of a horizontal measuring mode (HH) and a vertical measuring mode (VV) were 0.873 to 0.861, respectively. Four selected interpolation methods—Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Ordinary CoKriging (OCK) with soil moisture content, and Regression Kriging (RK) without covariable factor—provided slightly different patterns of soil salinity prediction with HH and VV modes. The mean values of the ECe prediction from the four methods at the district level varied from 2156.02 to 2293.25 mS/m for HH mode and from 2377.38 to 2401.41 mS/m for VV mode. Based on the accuracy assessment with the rank-sum technique, the OCK is a suitable interpolation method for soil salinity prediction for HH mode. At the same time, the IDW is suitable for soil salinity prediction for the VV mode. The dominant soil salinity severity classes of the two measuring modes using suitable spatial interpolation methods were strongly and very strongly saline. Consequently, the developed research methodology can be applied to conduct soil salinity surveys to reduce costs and save time in other areas by government agencies in Thailand. Nevertheless, to apply the EMI method for soil salinity survey, the users should understand the principle of EMI and how to calibrate and operate the EM device properly for accurate ECa measurement

Optimizing Land Use and Land Cover Allocation for Flood Mitigation Using Land Use Change and Hydrological Models with Goal Programming, Chaiyaphum, Thailand

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 economic and ecosystem service value evaluation and change. According to the results of the optimization and mapping of suitable LULC allocation to minimize surface runoff for flood mitigation in dry, normal, and wet years using goal programming and the CLUE-S model, the suitable LULC allocation for flood mitigation in 2049 under a normal year could provide the highest future economic value and gain. In the meantime, the suitable LULC allocation for flood mitigation in 2049 under a drought year could provide the highest ecosystem service value and gain. Nevertheless, considering future economic and ecosystem service values and changes with surface runoff reduction, the most suitable LULC allocation for flood mitigation is a normal year. Consequently, it can be concluded that the derived results of this study can be used as primary information for flood mitigation project implementation. Additionally, the presented conceptual framework and research workflows can be used as a guideline for government agencies to examine other flood-prone areas for flood mitigation in Thailand

Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China

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 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature

Suitable Land-Use and Land-Cover Allocation Scenarios to Minimize Sediment and Nutrient Loads into Kwan Phayao, Upper Ing Watershed, Thailand

Human activity and land-use changes have affected the water quality of Kwan Phayao, Upper Ing watershed, due to the associated high sediment load and eutrophication. This study aims to identify suitable LULC allocation scenarios for minimizing sediment and nutrient export into the lake. For this purpose, the LULC status and change were first assessed, based on classified LULC data in 2009 and 2019 from Landsat images, using the SVM algorithm. Later, the land requirements of three scenarios between 2020 and 2029 were estimated, based on their characteristics, and applied to predict LULC change using the CLUE-S model. Then, actual LULC data in 2019 and predicted LULC data under three scenarios between 2020 and 2029 were used to estimate sediment and nutrient export using the SDR and NDR models. Finally, the ecosystem service change index identified a suitable LULC allocation for minimizing sediment or/and nutrient export. According to the results, LULC status and change indicated perennial trees and orchards, para rubber, and rangeland increased, while forest land and paddy fields decreased. The land requirements of the three scenarios provided reasonable results, as expected, particularly Scenario II, which adopts linear programming to calculate the land requirements for maximizing ecosystem service values. For sediment and nutrient export estimation under the predicted LULC for the three scenarios, Scenario II led to the lowest yield of sediment and nutrient exports, and provided the lowest average ESCI value among the three scenarios. Thus, the LULC allocation under Scenario II was chosen as suitable for minimizing sediment or/and nutrient export into Kwan Phayao. These results can serve as crucial information to minimize sediment and nutrient loads for land-use planners, land managers, and decision makers

Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China

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 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature