scholarly journals Land Cover Change Impact on Coastal Tourism Development near Pacitan Southern Ringroad

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Riswandha Risang Aji ◽  
Visilya Faniza
Keyword(s):  
Economic Development ◽  
Land Cover ◽  
Land Cover Change ◽  
Descriptive Analysis ◽  
Coastal Areas ◽  
Coastal Tourism ◽  
Economic Sectors ◽  
Beach Tourism ◽  
Landsat 7 ◽  
Social Economic Development

Tourism is one of the economic sectors that can make a difference to the regional economy. Pacitan Regency is one of the regions which has tourism sector as its income. Pacitan regency also has Southern Ringroad that opens access to some coastal areas. Coastal areas have some tourism potentials, especially beach tourism. The aim of this research is to describe land cover change and its impacts on three beaches as coastal tourism areas due to the development of the southern ringroad. This research uses descriptive analysis to describe land cover change using remote sensing analysis and social-economic development in the coastal tourism area. Satellite images from Landsat 7 are analyzed to describe the land cover change. The result of this research shows that there is the land cover change which leads to social and economic development. Social development in the area is concluded not vulnerable and economic development is improved.

scholarly journals Land Cover Change Investigation in the Southern Syrian Coastal Basins During the Past 30-Years Using Landsat Remote Sensing Data

2018 ◽  
Vol 11 (1-2) ◽  
pp. 45-51 ◽  
Author(s):  
Muhannad Hammad ◽  
László Mucsi ◽  
Boudewijn van Leeuwen
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Coastal Basins ◽  
Major Increase ◽  
Temporal And Spatial ◽  
Land Cover Maps ◽  
Conflict Period

Abstract Land cover change and deforestation are important global ecosystem hazards. As for Syria, the current conflict and the subsequent absence of the forest preservation are main reasons for land cover change. This study aims to investigate the temporal and spatial aspects and trends of the land cover alterations in the southern Syrian coastal basins. In this study, land cover maps were made from surface reflectance images of Landsat-5(TM), Landsat-7(ETM+) and Landsat-8(OLI) during May (period of maximum vegetation cover) in 1987, 2002 and 2017. The images were classified into four different thematic classes using the maximum likelihood supervised classification method. The classification results were validated using 160 validation points in 2017, where overall accuracy was 83.75%. Spatial analysis was applied to investigate the land cover change during the period of 30 years for each basin and the whole study area. The results show 262.40 km2 reduction of forest and natural vegetation area during (1987-2017) period, and 72.5% of this reduction occurred during (2002-2017) period due to over-cutting of forest trees as a source of heating by local people, especially during the conflict period. This reduction was particularly high in the Alabrash and Hseen basins with 76.13 and 79.49 km2 respectively, and was accompanied by major increase of agriculture lands area which is attributed to dam construction in these basins which allowed people to cultivate rural lands for subsistence or to enhance their economic situation. The results of this study must draw the relevant authorities’ attention to preserve the remaining forest area.

Natural disasters and land-use/land-cover change in the southwest coastal areas of Bangladesh

2014 ◽  
Vol 15 (2) ◽  
pp. 241-250 ◽  
Author(s):  
Md Modasser Hossain Khan ◽  
Ian Bryceson ◽  
Korine N. Kolivras ◽  
Fazlay Faruque ◽  
M. Mokhlesur Rahman ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Natural Disasters ◽  
Land Cover Change ◽  
Coastal Areas ◽  
Land Use Land Cover

scholarly journals Analyzing Land Cover Change Using Remote Sensing and GIS: A Case Study of Gilgit River Basin, North Pakistan

2019 ◽  
Vol 10 (1) ◽  
pp. 100-105
Author(s):  
Karamat Ali ◽  
Roshan M. Bajracharya ◽  
Nawa Raj Chapagain ◽  
Nani Raut ◽  
Bishal Kumar Sitaula ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Thematic Mapper ◽  
Water Bodies ◽  
Land Cover Changes ◽  
Erdas Imagine ◽  
Landsat 7 ◽  
North Pakistan ◽  
Assessment And Monitoring ◽  
Effective Assessment

Mountainous areas of northern Pakistan are rich in biodiversity, glaciers and key watershed of Indus Riversystem which provide ecosystem services for their inhabitants. These regions have experienced extensive deforestationand are presently vulnerable by rapid land cover changes, therefore an effective assessment and monitoring is essentialto capture such changes. The aim of this study is to analyze the observed changes in land cover over a period of thirtynine years, divided into three stages (1976-1999, 1999-2008 and 2008-2015). Four images from Landsat 2Multispectral Scanner System (MSS), Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper andLandsat 8 Operation Land Imager data were obtained to detect land cover change. This study used supervisedclassification-maximum likelihood algorithm in ERDAS imagine to identify land cover changes perceived in GilgitRiver Basin, Pakistan. The result showed that the range land, glaciers, water bodies, built-up/agricultural cover are themajor categories that have been altered by the natural and anthropogenic actions. In 1976, built up/agriculture, rangeland, water bodies and glacier cover was 1.13%, 45.3%, 0.66% and 13.2%, respectively. Whereas in 2015, builtup/agriculture, range land, water bodies and glacier cover was 3.25%, 12.7%, 0.91% and 8.2%, respectively. Thesesland cover shifts posed acute threat to watershed resources. Therefore, a comprehensive watershed resourcemanagement is essential or otherwise, these resources will deplete rapidly and no longer be capable of playing their rolein socioeconomic and sustainable environmental development of the area

scholarly journals COMPATIBILITY STUDY AND SUPPORTING CAPACITY OF TOURISM AT PERERENAN BEACH BADUNG, BALI

ASTONJADRO ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 130
Author(s):  
Ni Putu Yunita Laura Vianthi ◽  
Widiastuti Widiastuti
Keyword(s):  
Carrying Capacity ◽  
Descriptive Analysis ◽  
Compatibility Study ◽  
Analysis Method ◽  
Supporting Capacity ◽  
Coastal Tourism ◽  
Mass Tourism ◽  
Beach Recreation ◽  
Beach Tourism ◽  
Travel Satisfaction

<p>The challenge of Pererenan Beach Development is to determine the efficiency of resource utilization, so that it does not exceed its carrying capacity. The carrying capacity of Pererenan Beach tourism is carried out by analyzing the suitability of coastal tourism. Then calculate the capacity to measure the number of tourists that can be accommodated without damaging the ecosystem. This study aims to determine the suitability and carrying capacity of coastal tourism. The method used is quantitative and descriptive analysis method. The results showed that the carrying capacity of the area on Pererenan Beach was classified under the carrying capacity and had a very suitable relative criterion (S1) with a percentage value of 96% suitable for use as beach recreation tourism. The Covid-19 pandemic provides a lesson that the concept of carrying capacity is important to avoid mass tourism and reduce the number of tourists according to their capacity so that visitors get comfort and travel satisfaction.</p>

scholarly journals Land Cover Change and Coastal Sustainability in the Coastal Area of Kendari Bay, Southeast Sulawesi, Indonesia

2021 ◽  
Vol 921 (1) ◽  
pp. 012008
Author(s):  
Ariyani ◽  
M Achmad ◽  
E Morgan
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Use Planning ◽  
Supervised Classification ◽  
Accuracy Assessment ◽  
Coastal Areas ◽  
Maximum Likelihood Algorithm ◽  
Rapid Changes ◽  
Land Cover Map ◽  
Method Accuracy

Abstract Coastal areas provide invaluable resources which have important environment, economic and social value. These resources encourages growing population and development which induced rapid changes in coastal areas. This study aims to analyse the changes in land cover of the coastal areas of Kendari Bay to provide recent perspectives of how land cover has changed using Landsat TM and Landsat OLI images for the period of 1998, 2008 and 2018. The classified land cover classes are categorized as waterbodies, built-up, bareland, forest, wetland, vegetation and mangrove. The land cover map of each period was acquired from supervised classification using maximum likelihood algorithm in ArcGIS, then the land cover change was analysed through post-classification change detection of GIS-based method. . Accuracy assessment of classified images shows the overall accuracy is estimated as 88.71%, 85.81% and 91.61%, and overall Kappa coeffient statistical values of 0.87, 0.83 and 0.90 for the year 1998, 2008 and 2018 respectively. This study found that there was significant land cover change in the coastal areas of Kendari Bay. It was dominated by the expansion of built-up areas and bareland by 55% and 469.77% respectively, which was gained from the conversion of vegetation and wetland. Meanwhile, considerable reduction were shown in mangrove, wetland, forest and vegetation which have declined by 48.65%, 43.39%, 38.72% and 27.20%. Analysing land cover change is an effective way to understand the dynamics of land cover in coastal areas, and can be used for future land use planning and policies.

scholarly journals Assessing Land Use and Land Cover Change in the Volta Grande Do Xingu (Pará – Brazil) Between 2000 and 2017

2021 ◽  
Author(s):  
Alynne Almeida Affonso ◽  
Silvia Sayuri Mandai ◽  
Tatiana Pineda Portella ◽  
Carlos Henrique Grohmann ◽  
José Alberto Quintanilha
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Minimum Distance ◽  
Hydroelectric Power Plant ◽  
Ground Truth ◽  
Hydroelectric Power ◽  
Landsat 7 ◽  
Ground Truth Image ◽  
Belo Monte

Abstract This study aims to assess the land use and land cover change through the use of three pixel-based methods of image classification (Mahalanobis, Maximum Likelihood, and Minimum Distance) in the region of Volta Grande do Xingu (Brazilian Amazon), under influence of the Belo Monte hydroelectric power plant. Different pixel-based classification methods were performed on Landsat 7 and 8 multispectral products from the years 2000 and 2017, using a 2008 map as the ground truth image. The accuracies of the classifications were compared, and land use change analyses were performed in the different scenarios. The main impacts regarding land use and land cover change were from forest to agro pasture, from non-river to river upstream the Xingu river, and from river to non-river in the south of the Volta Grande do Xingu, resulting in rocks exposure.

Quantification of Land use/Land cover change in Qorveh-Dehgolan Basin, Kurdistan Province, Iran Using Remote Sensing and GIS

2018 ◽  
Vol 41 (2) ◽  
pp. 103-112
Author(s):  
Payam Sajadi ◽  
◽  
Saumitra Mukherjee ◽  
Kamran Chapi ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Maximum Likelihood ◽  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification ◽  
Bare Soil ◽  
Remote Sensing And Gis ◽  
Land Use Land Cover ◽  
Landsat 7

This research aimed to analyze the land use/ land cover (LULC) change in Qorveh-Dehgolan Basin (Kurdistan, Iran) from 2000 to 2017 (four sets of data) using Landsat (7 and 8) images. Supervised classification using maximum likelihood generated four series of LULC maps by ENVI 5.3 software. Overall, six major classes including bare soil, water body, vegetation cover, agriculture land, grassland, and settlements were identified and mapped.The LULC style has changed over 17 years. It was determined that the waterbody class has continuously reduced about 173.66 km2 from 2000 to 2017 by 63%. The agriculture class has considerably increased from 2000 to 2017 about 129.43 km2 and finally, the area of settlement class increased about 54.06. km2. The overall accuracy was 81.50%, 85.0%, 92.00%, 92.00% for the years of 2000, 2006, 2013 and 2017 respectively.

scholarly journals ASSESSMENT OF LAND USE/LAND COVER CHANGE MAPPING IN BANGUI CITY USING REMOTE SENSING AND GIS TECHNIQUES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1651-1656
Author(s):  
M. Traore ◽  
C. P. Ndepete ◽  
R. L. Zaguy-Guerembo ◽  
A. B. Pour
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Bare Soil ◽  
Kappa Statistics ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Landsat 7 ◽  
Negative Effect ◽  
The City

Abstract. The security instability in the Central African Republic (CAR) forces the civilian population to flee the provinces to seek refuge in Bangui city, or in other countries. Human activity, which is very beneficial in the context of urbanization, is the main driving force of change in the city of Bangui, but also has a negative effect on the geoenvironment. Multispectral images data Landsat TM5, Landsat 7 ETM+ and Landsat-8 OLI of the years 1986, 2003 and 2020 was used to investigate Land use land cover (LULC) change of the city of Bangui. Maximum Likelihood (ML) classification algorithm was used to produce the map land use/land cover change detection in the study area. In Bangui city, four major classes have been identified, including vegetation, built-up, bare soil / rock and water. The analyses of the classified maps showed that Bangui city has been changed between 1986 and 2020, exceedingly area increased for built up (145.81%), vegetation (5.59%) and water (3.46%), it has however decreased for bare soil/ rock (40.60%). The overall accuracies and overall Kappa statistics achieved were 92.5%, 82.5% and 87.5%, and 0.90, 0.87 and 0.83 for 1986, 1999 and 2018 images, respectively.

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