Pub Date : 2023-10-31DOI: 10.14710/geoplanning.10.1.23-36
Kaushikkumar Prafulbhai Sheladiya, Chetan R. Patel
The main purpose of this study is to detect land use land cover change for 1990-2000, 2000-2010, and 2010-2020 using multispectral Landsat images as well as to simulate and predict urban growth of Surat city using Cellular Automata-based Markov Chain Model. Maximum likelihood supervise classification was used to generate LULC maps of the years 1990,2000,2010, and 2020 and the overall accuracy of these maps were 90%, 95%, 91.25%, and 96.25%, respectively. Two transition rules were commuted to predict the LULC of 2010 and 2020. For validation of these LULC maps, the Area Under Characteristics curve was used, and these maps' accuracy was 95.30% and 86.90%. This validation predicted LULC maps for the years 2035 and 2050. Transition rules of 2010-2035 showed that there will be a probability that 36.33% of vegetation area and 40.27% of the vacant land area will be transited into built-up by the year 2035, and it will be 49.20 % of the total area. Also, 57.77% of the vegetation area and 60.24% of the built-up area will be transformed into urban areas by the year 2050, almost 62.60 %. Analysis of LULC maps 2035 and 2050 exhibits that there will be abundant growth in all directions except the South Zone and Southwest Zone. Therefore, this study helps urban planners and decision-makers decide what to retain, where to plan for new development and type of development, what to connect, and what to protect in coming years.
{"title":"An Application of Cellular Automata (CA) and Markov Chain (MC) Model in Urban Growth Prediction: A case of Surat City, Gujarat, India","authors":"Kaushikkumar Prafulbhai Sheladiya, Chetan R. Patel","doi":"10.14710/geoplanning.10.1.23-36","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.23-36","url":null,"abstract":"The main purpose of this study is to detect land use land cover change for 1990-2000, 2000-2010, and 2010-2020 using multispectral Landsat images as well as to simulate and predict urban growth of Surat city using Cellular Automata-based Markov Chain Model. Maximum likelihood supervise classification was used to generate LULC maps of the years 1990,2000,2010, and 2020 and the overall accuracy of these maps were 90%, 95%, 91.25%, and 96.25%, respectively. Two transition rules were commuted to predict the LULC of 2010 and 2020. For validation of these LULC maps, the Area Under Characteristics curve was used, and these maps' accuracy was 95.30% and 86.90%. This validation predicted LULC maps for the years 2035 and 2050. Transition rules of 2010-2035 showed that there will be a probability that 36.33% of vegetation area and 40.27% of the vacant land area will be transited into built-up by the year 2035, and it will be 49.20 % of the total area. Also, 57.77% of the vegetation area and 60.24% of the built-up area will be transformed into urban areas by the year 2050, almost 62.60 %. Analysis of LULC maps 2035 and 2050 exhibits that there will be abundant growth in all directions except the South Zone and Southwest Zone. Therefore, this study helps urban planners and decision-makers decide what to retain, where to plan for new development and type of development, what to connect, and what to protect in coming years.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"61 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135979376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to assess the effect of green open space (GOS) on the microclimate and thermal comfort in three integrated campuses namely Universitas Gadjah Mada (UGM), Universitas Muhammadiyah Yogyakarta (UMY), and Universitas Pembangunan Nasional (UPN) Veteran. In order to achieve the research objective, three main steps were conducted. First, we mapped the GOS area and density of the three integrated campuses using a high-resolution satellite imagery. Second, three microclimate parameters such as air temperature, relative humidity, and wind speed were measured to each detected green spaces in the morning (08:00 am), at noon (01:00 pm), and afternoon (5:00 pm). Subsequently, the results of microclimate measurements were used to calculate the level of thermal comfort using Thermal Humidity Index (THI) method. Third, we carried out statistical analysis to investigate the correlation between the distribution and the density of GOS and the microclimate conditions. The results showed that a negative (-) correlation occurred between the pattern and density of GOS with temperature and wind speed indicating that clustered GOS significantly reduces the air temperature as well as the wind speed. On the contrary, the relative humidity has been increased. UPN campus has the highest temperature and wind speed and the lowest humidity among other campuses. According to the results of THI, a 100% of the UPN areas are uncomfortable, while at UGM and UMY 42,08% and 11,28% of their area are uncomfortable, respectively. This study found that the existence of GOS has an effect on microclimate depending on pattern and density.
本研究旨在评估Gadjah Mada大学(UGM)、Universitas Muhammadiyah Yogyakarta大学(UMY)和Universitas Pembangunan Nasional (UPN) Veteran三个综合校区的绿色开放空间(GOS)对小气候和热舒适的影响。为了实现研究目标，主要进行了三个步骤。首先，我们利用高分辨率卫星图像绘制了三个综合校区的GOS面积和密度。其次，分别在上午(08:00 am)、中午(01:00 pm)和下午(5:00 pm)对每个被检测绿地的气温、相对湿度和风速等3个小气候参数进行测量。随后，利用微气候测量结果，采用热湿度指数(THI)法计算热舒适水平。第三，对GOS分布和密度与小气候条件的相关性进行了统计分析。结果表明:GOS的分布和密度与气温和风速呈负(-)相关，表明聚集的GOS显著降低了气温和风速;相反，相对湿度增加了。UPN校园是其他校园中温度和风速最高，湿度最低的。根据THI的结果，100%的UPN地区不舒服，而在UGM和UMY分别有42,08%和11.28%的地区不舒服。研究发现，GOS的存在对小气候的影响有不同的模式和密度。
{"title":"The Effects of Green Open Spaces on Microclimate and Thermal Comfort in Three Integrated Campus in Yogyakarta, Indonesia","authors":"Nurwidya Ambarwati, Lies Rahayu Wijayanti Faida, Hero Marhaento","doi":"10.14710/geoplanning.10.1.37-44","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.37-44","url":null,"abstract":"This study aims to assess the effect of green open space (GOS) on the microclimate and thermal comfort in three integrated campuses namely Universitas Gadjah Mada (UGM), Universitas Muhammadiyah Yogyakarta (UMY), and Universitas Pembangunan Nasional (UPN) Veteran. In order to achieve the research objective, three main steps were conducted. First, we mapped the GOS area and density of the three integrated campuses using a high-resolution satellite imagery. Second, three microclimate parameters such as air temperature, relative humidity, and wind speed were measured to each detected green spaces in the morning (08:00 am), at noon (01:00 pm), and afternoon (5:00 pm). Subsequently, the results of microclimate measurements were used to calculate the level of thermal comfort using Thermal Humidity Index (THI) method. Third, we carried out statistical analysis to investigate the correlation between the distribution and the density of GOS and the microclimate conditions. The results showed that a negative (-) correlation occurred between the pattern and density of GOS with temperature and wind speed indicating that clustered GOS significantly reduces the air temperature as well as the wind speed. On the contrary, the relative humidity has been increased. UPN campus has the highest temperature and wind speed and the lowest humidity among other campuses. According to the results of THI, a 100% of the UPN areas are uncomfortable, while at UGM and UMY 42,08% and 11,28% of their area are uncomfortable, respectively. This study found that the existence of GOS has an effect on microclimate depending on pattern and density.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"27 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135979530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.14710/geoplanning.10.1.45-54
Ricky Anak Kemarau, Oliver Valentine Eboy, Zaini Sakawi, Stanley Anak Suab, Nik Norliati Fitri Md Nor
In recent decades, extensive deforestation in tropical regions has dynamically reshaped forests and land cover. Driven by demands for intensified agriculture, rural settlement expansion, and urban growth, this transformation underscores the need for vigilant monitoring of vegetation and forest cover to comprehend global and local environmental shifts. This study focuses on the intricate interplay between deforestation and its impact on land surface temperature (LST) within Sabah's Kundasang highland. Analyzing years 1990, 2009, and 2021, the study employs Landsat 5 and Landsat 8 satellite data spanning three decades to decipher forest cover dynamics. Utilizing remote sensing techniques, it unveils the evolving relationship between deforestation, forest cover, and LST fluctuations, validated using Moderate Resolution Imaging Spectroradiometer (MODIS) insights from 1990 to 2021. Motivated by the scarcity of research on tropical deforestation's LST impact, the study's core aim is to establish a robust link between forest loss extent and ensuing thermal changes. The findings highlight a tangible influence of reduced vegetation on rising surface temperatures, necessitating a precise understanding of deforested areas and their thermal responses. Revealing a striking scenario, around 76% of Kundasang highland's forest cover transformed into agriculture and urban zones over 27 years. The study further uncovers a clear inverse relationship between LST and forest area in square kilometers, as well as the Normalized Difference Vegetation Index (NDVI). These findings provide valuable guidance for forest management, identifying vulnerable areas, while also empowering local governance to shape sustainable land management strategies.
{"title":"Impact Deforestation on Land Surface Temperature: A Case Study Highland Kundasang, Sabah","authors":"Ricky Anak Kemarau, Oliver Valentine Eboy, Zaini Sakawi, Stanley Anak Suab, Nik Norliati Fitri Md Nor","doi":"10.14710/geoplanning.10.1.45-54","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.45-54","url":null,"abstract":"In recent decades, extensive deforestation in tropical regions has dynamically reshaped forests and land cover. Driven by demands for intensified agriculture, rural settlement expansion, and urban growth, this transformation underscores the need for vigilant monitoring of vegetation and forest cover to comprehend global and local environmental shifts. This study focuses on the intricate interplay between deforestation and its impact on land surface temperature (LST) within Sabah's Kundasang highland. Analyzing years 1990, 2009, and 2021, the study employs Landsat 5 and Landsat 8 satellite data spanning three decades to decipher forest cover dynamics. Utilizing remote sensing techniques, it unveils the evolving relationship between deforestation, forest cover, and LST fluctuations, validated using Moderate Resolution Imaging Spectroradiometer (MODIS) insights from 1990 to 2021. Motivated by the scarcity of research on tropical deforestation's LST impact, the study's core aim is to establish a robust link between forest loss extent and ensuing thermal changes. The findings highlight a tangible influence of reduced vegetation on rising surface temperatures, necessitating a precise understanding of deforested areas and their thermal responses. Revealing a striking scenario, around 76% of Kundasang highland's forest cover transformed into agriculture and urban zones over 27 years. The study further uncovers a clear inverse relationship between LST and forest area in square kilometers, as well as the Normalized Difference Vegetation Index (NDVI). These findings provide valuable guidance for forest management, identifying vulnerable areas, while also empowering local governance to shape sustainable land management strategies.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"32 11-12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136133609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.14710/geoplanning.10.1.55-72
Heri Mulyanti, Istadi Istadi, Rahmat Gernowo
Drought known as ‘silent killer’—unpredictable slow-moving hazard which cause severe damage to people and environment. Since agriculture is the first and foremost sector affected by drought, the risk of crop failure can be minimized by reducing vulnerability. Climate patterns can be considered as systematic conditions which are capable of assigning sensitivity regions to drought. Here, the study employs Oldeman’s Agro Climatic data as physical vulnerability indicator to assess and monitor the vulnerability of agriculture system to drought in East Java. The study used long-term monthly rainfall observation data to generate climatic map accompanied with socio-economic indicators to assess vulnerability of region to drought. Spatial distribution of vulnerability was mapped using Geographic Information Systems (GIS) combined with Analytic Hierarchy Process (AHP). The results show there are five categories of vulnerability to drought: very high, high, moderate, low, and very low based on standardized index. Madura Island, particularly Bangkalan, Sampang, and Sumenep considered as most vulnerable region to drought. In addition, most regions in the north plain of East Java, including Tuban, Lamongan, and Gresik categorized as highly vulnerable to drought. Factors affecting vulnerability are mostly related to drier climate which affect acreage and availability of irrigation. The socio-economic factors likewise smallholder farmers and poverty contribute to rising vulnerability level. South part of East Java, particularly Tulungagung and Blitar Regency was least vulnerable because of appropriate climate which induced to acreage of irrigated land. The study emphasizes the utilizing of Oldeman climate pattern as primary indicator in determining vulnerable regions. Smallholder farmers and poverty causing vulnerability in agriculture emerged as priority for further study. The results can provide new insights into drought management for most vulnerable regions by considering local climatic characteristics.
{"title":"Assessing Vulnerability of Agriculture to Drought in East Java, Indonesia: Application of GIS and AHP","authors":"Heri Mulyanti, Istadi Istadi, Rahmat Gernowo","doi":"10.14710/geoplanning.10.1.55-72","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.55-72","url":null,"abstract":"Drought known as ‘silent killer’—unpredictable slow-moving hazard which cause severe damage to people and environment. Since agriculture is the first and foremost sector affected by drought, the risk of crop failure can be minimized by reducing vulnerability. Climate patterns can be considered as systematic conditions which are capable of assigning sensitivity regions to drought. Here, the study employs Oldeman’s Agro Climatic data as physical vulnerability indicator to assess and monitor the vulnerability of agriculture system to drought in East Java. The study used long-term monthly rainfall observation data to generate climatic map accompanied with socio-economic indicators to assess vulnerability of region to drought. Spatial distribution of vulnerability was mapped using Geographic Information Systems (GIS) combined with Analytic Hierarchy Process (AHP). The results show there are five categories of vulnerability to drought: very high, high, moderate, low, and very low based on standardized index. Madura Island, particularly Bangkalan, Sampang, and Sumenep considered as most vulnerable region to drought. In addition, most regions in the north plain of East Java, including Tuban, Lamongan, and Gresik categorized as highly vulnerable to drought. Factors affecting vulnerability are mostly related to drier climate which affect acreage and availability of irrigation. The socio-economic factors likewise smallholder farmers and poverty contribute to rising vulnerability level. South part of East Java, particularly Tulungagung and Blitar Regency was least vulnerable because of appropriate climate which induced to acreage of irrigated land. The study emphasizes the utilizing of Oldeman climate pattern as primary indicator in determining vulnerable regions. Smallholder farmers and poverty causing vulnerability in agriculture emerged as priority for further study. The results can provide new insights into drought management for most vulnerable regions by considering local climatic characteristics.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.14710/geoplanning.10.1.73-82
Mulyadi Alwi, Bachtiar W. Mutaqin, Muh Aris Marfai
Indonesia is considered one of the biggest archipelagic countries in the world. According to some literature, Indonesia has more than 17,000 islands, most of which are classified as small islands. Some of these islands have become important areas for tourism, for instance, small islands in Karimunjawa. However, some of these islands experienced shoreline changes caused by erosion and accretion. Hence, this research aims to map the spatial distribution of shoreline change using the Digital Shoreline Analysis System (DSAS) add-in on ArcGIS. The primary dataset utilized as input consists of Sentinel 2A imagery captured over 2017 and 2022. The results showed that around 89 segments, or 51.47% of the total shoreline segments, tend to experience accretion, while the remaining 79 segments, or 45.93%, experience erosion. This finding suggests that most shoreline segments tend to accrete or seaward movement in the research area. The results of this study exhibit notable disparities when compared to the occurrences observed in Pandeglang (Banten), Kuwaru (Yogyakarta), Buleleng (Bali), and East Java Province, where coastal erosion prevails over accretion. The managers of the islands try to reduce the threat of erosion by constructing dykes and breakwaters. However, these buildings are ineffective due to the relatively simple structures and building materials. Therefore, further studies are needed to determine the type and specification of mitigation buildings that are suitable for implementation in that location.
{"title":"Shoreline Dynamics in the Very Small Islands of Karimunjawa – Indonesia: A Preliminary Study","authors":"Mulyadi Alwi, Bachtiar W. Mutaqin, Muh Aris Marfai","doi":"10.14710/geoplanning.10.1.73-82","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.73-82","url":null,"abstract":"Indonesia is considered one of the biggest archipelagic countries in the world. According to some literature, Indonesia has more than 17,000 islands, most of which are classified as small islands. Some of these islands have become important areas for tourism, for instance, small islands in Karimunjawa. However, some of these islands experienced shoreline changes caused by erosion and accretion. Hence, this research aims to map the spatial distribution of shoreline change using the Digital Shoreline Analysis System (DSAS) add-in on ArcGIS. The primary dataset utilized as input consists of Sentinel 2A imagery captured over 2017 and 2022. The results showed that around 89 segments, or 51.47% of the total shoreline segments, tend to experience accretion, while the remaining 79 segments, or 45.93%, experience erosion. This finding suggests that most shoreline segments tend to accrete or seaward movement in the research area. The results of this study exhibit notable disparities when compared to the occurrences observed in Pandeglang (Banten), Kuwaru (Yogyakarta), Buleleng (Bali), and East Java Province, where coastal erosion prevails over accretion. The managers of the islands try to reduce the threat of erosion by constructing dykes and breakwaters. However, these buildings are ineffective due to the relatively simple structures and building materials. Therefore, further studies are needed to determine the type and specification of mitigation buildings that are suitable for implementation in that location.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"44 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136319051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.14710/geoplanning.10.1.11-22
Abraham Babatounde Alamou, Ousséni Arouna, Joseph Oloukoi
Forest ecosystems of the Alibori basin are subject to multiple anthropogenic pressures witch therefore modify their land use and their land cover. This research aims at analyzing the spatio-temporal dynamics of land use and land cover in the Alibori basin in Northern Benin. The methodological approach used is based on the diachronic analysis of land cover from Landsat 2, 7, and 8 satellite images acquired respectively in 1980, 2000, and 2020, and the evaluation of land cover change parameters (conversion rate, level of deforestation, intensity and speed of change of land cover units). The results obtained reveal that the number of classes has increased from 8 to 9 with the appearance of plantations between 1980 and 2000. Between 1980 and 2020 the basin recorded a degradation of forest formations and an anthrogenization of savannah formations. The intensity and speed of loss of area are quite rapid in dense dry forests, open forests, and wooded savannahs between 1980 and 2020. The average rate of deforestation decreased from 1.27% annually between 1980 and 2000 to 1.26% annually between 2000 and 2020.
{"title":"Spatio-temporal dynamics of land use and land cover in the Alibori basin in Northern Benin Republic (West Africa)","authors":"Abraham Babatounde Alamou, Ousséni Arouna, Joseph Oloukoi","doi":"10.14710/geoplanning.10.1.11-22","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.11-22","url":null,"abstract":"Forest ecosystems of the Alibori basin are subject to multiple anthropogenic pressures witch therefore modify their land use and their land cover. This research aims at analyzing the spatio-temporal dynamics of land use and land cover in the Alibori basin in Northern Benin. The methodological approach used is based on the diachronic analysis of land cover from Landsat 2, 7, and 8 satellite images acquired respectively in 1980, 2000, and 2020, and the evaluation of land cover change parameters (conversion rate, level of deforestation, intensity and speed of change of land cover units). The results obtained reveal that the number of classes has increased from 8 to 9 with the appearance of plantations between 1980 and 2000. Between 1980 and 2020 the basin recorded a degradation of forest formations and an anthrogenization of savannah formations. The intensity and speed of loss of area are quite rapid in dense dry forests, open forests, and wooded savannahs between 1980 and 2020. The average rate of deforestation decreased from 1.27% annually between 1980 and 2000 to 1.26% annually between 2000 and 2020.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"9 2-3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136319052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-20DOI: 10.14710/geoplanning.10.1.1-10
Yenda Padmini, M Sreenivasa Rao, Raja Rao Gara
Land use and land cover change (LULCC) has become a significant global concern due to its wide-ranging environmental, social and economic impacts. This literature review aims to provide a comprehensive overview of the key ideas, drivers, consequences and approaches to studying LULCC. By synthesizing various research articles, this review offers insights into the causes and impacts of LULCC, as well as the methods used to analyze and monitor these changes. The review also highlights the importance of understanding LULCC dynamics for sustainable land management and policy making. Between 2017 and 2022, the LULC categories underwent several changes. Data acquisition process for satellite imagery combining Sentinel-2 digital remote sensing data digital remote sensing data through the Copernicus Open Access Hub. The spectral resolution is 10, 20, and 30 meters respectively, while the spatial resolution is 10 meters which was used for the LULC analysis of the study area. This analysis underscores the importance of LULCC monitoring to inform sustainable land management practices and conservation efforts. The trends identified provide a basis for further investigation into the underlying drivers of these changes and their potential impacts on ecosystems, water resources and human well-being. Continued monitoring and proactive measures are essential to mitigate adverse impacts and promote sustainable land use in the future.
{"title":"Temporal Analysis of Land Use and Land Cover Changes in Vizianagaram District, Andhra Pradesh, India using Remote Sensing and GIS Techniques","authors":"Yenda Padmini, M Sreenivasa Rao, Raja Rao Gara","doi":"10.14710/geoplanning.10.1.1-10","DOIUrl":"https://doi.org/10.14710/geoplanning.10.1.1-10","url":null,"abstract":"Land use and land cover change (LULCC) has become a significant global concern due to its wide-ranging environmental, social and economic impacts. This literature review aims to provide a comprehensive overview of the key ideas, drivers, consequences and approaches to studying LULCC. By synthesizing various research articles, this review offers insights into the causes and impacts of LULCC, as well as the methods used to analyze and monitor these changes. The review also highlights the importance of understanding LULCC dynamics for sustainable land management and policy making. Between 2017 and 2022, the LULC categories underwent several changes. Data acquisition process for satellite imagery combining Sentinel-2 digital remote sensing data digital remote sensing data through the Copernicus Open Access Hub. The spectral resolution is 10, 20, and 30 meters respectively, while the spatial resolution is 10 meters which was used for the LULC analysis of the study area. This analysis underscores the importance of LULCC monitoring to inform sustainable land management practices and conservation efforts. The trends identified provide a basis for further investigation into the underlying drivers of these changes and their potential impacts on ecosystems, water resources and human well-being. Continued monitoring and proactive measures are essential to mitigate adverse impacts and promote sustainable land use in the future.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135936542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-08DOI: 10.14710/geoplanning.9.2.121-132
Muhammad Rafi Andhika Pratama, M. D. Manessa, S. Supriatna, Farida Ayu, Muhammad Haidar
A healthy coral reef ecosystem can be beneficial for the survival of fish habitats and aquatic ecosystems. This study aims to analyze the influence of human activities on the spatial distribution of coral reefs in the coastal waters of Samatellu Lompo Island, Pangkajene Islands Regency, South Sulawesi in 2000, 2014, 2018, and 2021. The spatial distribution of coral reefs was obtained through a field survey using the underwater transect photo method. Then, satellite images were processed by using the Lyzenga algorithm for water column correction, and aquatic objects were classified by using unsupervised classification. Human activities that affect coral reef destruction were obtained through interviews and it was strengthened with related literature studies. The results showed that the coral reefs in the coastal waters of Samatellu Lompo decreased from 2000-2021. In 2000, the live coral area was 13.53 ha, whereas in 2021 it was 8,031 ha. Destructive fishing activities such as using bombs and poison in catching fish are the main factors of coral reef destruction. In addition, destructive fishing activities commonly occur in the western and northern waters of Samatellu Lompo that causing the live coral into dead coral or rubble.
{"title":"Spatial Distribution of Coral Reef Degradation with Human Activities in the Coastal Waters of Samatellu Lompo Island, South Sulawesi","authors":"Muhammad Rafi Andhika Pratama, M. D. Manessa, S. Supriatna, Farida Ayu, Muhammad Haidar","doi":"10.14710/geoplanning.9.2.121-132","DOIUrl":"https://doi.org/10.14710/geoplanning.9.2.121-132","url":null,"abstract":"A healthy coral reef ecosystem can be beneficial for the survival of fish habitats and aquatic ecosystems. This study aims to analyze the influence of human activities on the spatial distribution of coral reefs in the coastal waters of Samatellu Lompo Island, Pangkajene Islands Regency, South Sulawesi in 2000, 2014, 2018, and 2021. The spatial distribution of coral reefs was obtained through a field survey using the underwater transect photo method. Then, satellite images were processed by using the Lyzenga algorithm for water column correction, and aquatic objects were classified by using unsupervised classification. Human activities that affect coral reef destruction were obtained through interviews and it was strengthened with related literature studies. The results showed that the coral reefs in the coastal waters of Samatellu Lompo decreased from 2000-2021. In 2000, the live coral area was 13.53 ha, whereas in 2021 it was 8,031 ha. Destructive fishing activities such as using bombs and poison in catching fish are the main factors of coral reef destruction. In addition, destructive fishing activities commonly occur in the western and northern waters of Samatellu Lompo that causing the live coral into dead coral or rubble.","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45878691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-22DOI: 10.14710/geoplanning.9.2.89-102
Nadiya Tri Utami, B. Pigawati
Palembang city has experienced an increase in its population. Population growth results in an increase in activities which enlarge the built-up areas. The increase of built-up areas is one of the indicators of urban growth. The increase in built-up areas is inversely proportional to the vegetation area. Reduced vegetation area might cause an increase in land surface temperature. The aim of the study was to analyze the correlation between urban growth and changes in land surface temperature in Palembang City using descriptive quantitative method and spatial analysis on the data obtained from remote sensing images. The result shows that in 1998-2018, Palembang City has developed to the north (Sukarami District) and to the west (Ilir Barat I District). There has been an increase in the temperature, documented as 2.12°C. There is a correlation between urban growth and changes in land surface temperature in Palembang City
巨港市经历了人口的增长。人口增长导致活动增加，从而扩大了建成区。建成区面积的增加是城市增长的指标之一。建成区面积的增加与植被面积成反比。植被面积减少可能导致地表温度升高。利用遥感影像数据，采用描述性定量方法和空间分析方法，分析巨港市城市增长与地表温度变化的相关性。结果表明，1998-2018年，巨港市向北(Sukarami区)和向西(Ilir Barat I区)发展。气温有所上升，据记载为2.12°C。巨港市的城市增长与地表温度变化之间存在相关性
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Pub Date : 2022-11-15DOI: 10.14710/geoplanning.9.1.37-46
G. A. J. Kartini, N. D. Saputri
Terrestrial Laser Scanner is a tool capable of generating millions 3D points with mm accuracy, but upper structure is difficult to model. Unmanned Aerial Vehicle is an unmanned aircraft system technology that can provide structural data on buildings. Measurements with one technique can lead to unsatisfactory results, so an integration process is carried out to obtain a more accurate 3D model. The purpose of this research is to see the successful integration of TLS and UAV point cloud data for 3D modeling. The data used is secondary data from previous research. TLS and UAV data were processed with Agisoft Metashape and Cyclone in the same coordinate system. The integration process is carried out by aligning the same point cloud between the two data in CloudCompare with an RMSE of 25.60 mm. Validation is done by comparing the distance between the results of the 3D model with the actual conditions. The integrated 3D model can be implemented for the purposes of Bosscha Observatory 3D modeling.
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