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Urban land use/cover mapping and change detection analysis using time series satellite images | ||
| نشریه کاربرد سنجش از دور و سیستم اطلاعات جغرافیایی در علوم محیطی | ||
| مقاله 6، دوره 2، شماره 5، اسفند 1401، صفحه 135-112 اصل مقاله (2.22 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22034/rsgi.2023.16823 | ||
| نویسندگان | ||
| ابوالفضل قنبری* 1؛ خلیل ولیزاده کامران2؛ علی محمد فاضل3 | ||
| 1هیات علمی/دانشگاه تبریز | ||
| 2گروه سنجش از دورو GIS دانشگاه تبریز | ||
| 3M.A Student in Remote Sensing and Geographic Information System, University of Tabriz | ||
| چکیده | ||
| Land use and land cover change have been among the most important perceptible changes taking place around us. Although perceptible, the magnitude, variety and the spatial variability of the changes taking place has made the quantification and assessment of land use and land cover changes a challenge to scientists. Furthermore, since most of the land use and land cover changes are directly influenced by human activities, they rarely follow standard ecological theories. The Remote Sensing and Geographic Information System has proved to be very important in assessing and analyzing land use and land cover changes. Satellite-based Remote Sensing, by virtue of its ability to provide synoptic information of land use and land cover at a particular time and location, has revolutionized the study of land use and land cover change. The temporal information on land use and land cover helps identify the areas of change in a region. The use of Geoinformatics has enabled us to assign spatial connotations to land use land cover changes, namely, population pressure, climate, terrain, etc which drive these changes. This has helped scientists to quantify these tools and to predict various scenarios. The purpose of this paper is to detect and evaluate land use and land cover changes (LULCC) of Khanaqin urban area over 20 years using remote sensing techniques and Landsat dataset for years 2000, 2010, and 2020. For this purpose supervised classification algorithm and maximum likelihood method has been used. Results show that Water lands, Built-up area, and Vegetation areas increased from 2000 to 2020 in the last 20 years while Barren lands, and Agricultural mixed lands had decreased. According to the analysis and results obtained, this research can be useful in the field of regional and environmental management in the city of Khanaqin and in the field of urban planning and management and research decisions in this region can be used | ||
تازه های تحقیق | ||
At present, satellite imagery is one of the most powerful tools for researchers to detect and detect changes due to its unique capabilities, which is used in many environmental sciences. Examining changes is one of the most important parts of analyzing satellite images, which today are used in a variety of ways to study changes before and after a particular time.Land use maps are one of the requirements of any national and regional development planning that enables managers and planners to design and implement the necessary measures by identifying the current situation and comparing capabilities and potentials to meet current and future needs. In fact, the results of such studies indicate the type of management applied in the region and also indicate its strengths and weaknesses during the study period, which can be a powerful management tool for optimal land management to achieve sustainable development and appropriate for managers and local officials. To take. Irregular land use changes in the future, regardless of the environmental situation, can also lead to environmental hazards. Therefore, the mentioned changes, especially the changes in residential areas, should be done in accordance with the conditions governing the environment and in compliance with the relevant principles. The urban communities of Iraq, and especially the remote and less developed cities of the country, have suffered great losses in economic, social, environmental, and managerial aspects of the spatial distribution of urban land uses. The rapid growth of Khanaqin city in recent decades along with the current growth pattern has led to economic, demographic, and urban development and so on. This issue is due to the significant growth of residential, industrial, and commercial construction in recent years, which has led to changes in land-use patterns in this city. In this study, urban land-use changes in the city of Khanaqin in Iraq have studied over a period of 20 years from 2000 to 2020 using remote sensing techniques and GIS. To classification of satellite images of the study area, 5 land use classes including barren lands, agricultural lands, built-up lands, mixed vegetation, and water lands have been considered for analysis. And using 350 training samples, the supervised classification algorithm of the maximum likelihood type has been implemented for this purpose. Results show that all classes except barren lands have been growing from 2000 to 2020, and therefore only barren lands have lost in total 6% of their area during this due to the growth of other lands, especially urban and agricultural lands. Also, during this period, the amount of residential and commercial constructions has been growing and in total, over a period of 20 years, about 141% of the urban land area has been added to them. Vegetation lands of the study area are also faced growth in these 20 years and the rate in the first period with 61%, compared to the second period with 6% was much higher. But the water lands had Growth in 20 years, in the first period increased by 148 percent and in the second period compared to the first period decreased by 12 percent. Agricultural lands also had a 25% growth in the second period, with a 46% decrease in area in the first period. According to the analysis and results obtained, this research can be useful in the field of regional and environmental management in the city of Khanaqin and in the field of urban planning and management and research decisions in this region can be used. Also, due to the lack of relevant research in this area, the results of this study can be useful and effective in future studies for analyzing interactive between land-use types and land-use trends, and land cover in this area. | ||
| کلیدواژهها | ||
| Land use؛ Land cover؛ Change detection؛ Remote sensing؛ Khanaqin | ||
| اصل مقاله | ||
|
Land use and land cover change have been among the most important perceptible changes taking place around us. Although perceptible, the magnitude, variety and the spatial variability of the changes taking place has made the quantification and assessment of land use and land cover changes a challenge to scientists. Furthermore, since most of the land use and land cover changes are directly influenced by human activities, they rarely follow standard ecological theories. The Remote Sensing and Geographic Information System has proved to be very important in assessing and analyzing land use and land cover changes. Satellite-based Remote Sensing, by virtue of its ability to provide synoptic information of land use and land cover at a particular time and location, has revolutionized the study of land use and land cover change. The temporal information on land use and land cover helps identify the areas of change in a region. The use of Geoinformatics has enabled us to assign spatial connotations to land use land cover changes, namely, population pressure, climate, terrain, etc which drive these changes. This has helped scientists to quantify these tools and to predict various scenarios. The purpose of this paper is to detect and evaluate land use and land cover changes (LULCC) of Khanaqin urban area over 20 years using remote sensing techniques and Landsat dataset for years 2000, 2010, and 2020. For this purpose supervised classification algorithm and maximum likelihood method has been used. Results show that Water lands, Built-up area, and Vegetation areas increased from 2000 to 2020 in the last 20 years while Barren lands, and Agricultural mixed lands had decreased. According to the analysis and results obtained, this research can be useful in the field of regional and environmental management in the city of Khanaqin and in the field of urban planning and management and research decisions in this region can be used. | ||
| مراجع | ||
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A Giraldo,M.Giraldo, M., S Chaudhari,L., O Schulz,L.(2012). Land-use and land-cover assessment for the study of lifestyle change in a rural Mexican community: The Maycoba Project. Giraldo et al. International Journal of Health Geographics. Abd El-Kawy, O. R., Rød, J. K., Ismail, H. A., & Suliman, A. S. (2011). Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Applied geography, 31(2), 483-494. Alawamy, J. S., Balasundram, S. K., & Boon Sung, C. T. (2020). Detecting and analyzing land use and land cover changes in the region of Al-Jabal Al-Akhdar, Libya using time-series landsat data from 1985 to 2017. Sustainability, 12(11), 4490. Al-doski, J., Mansor, S. B., & Shafri, H. Z. M. (2013). Change detection process and techniques. Civil and Environmental Research, 3(10). Alqurashi, A. F., Kumar, L., & Sinha, P. (2016). Urban land cover change modelling using timeseries satellite images: A case study of urban growth in five cities of Saudi Arabia. Remote Sensing, 8(10), 838. Chang,Y.Chang, Y., Hou,K.Hou, K., Li,X., Zhang,Y., Chen,P.(2018). Review of Land Use and Land Cover Change research progress.OPprogress. OP Conf. Series: Earth and Environmental Science 113. Erasu, D. (2017). Remote sensing-based urban land use/land cover change detection and monitoring. Journal of Remote Sensing & GIS, 6(2), 5. Feizizadeh, B., Mohammadzade Alajujeh, K., Lakes, T., Blaschke, T., & Omarzadeh, D. (2021). A comparison of the integrated fuzzy object-based deep learning approach and three machine learning techniques for land use/cover change monitoring and environmental impacts assessment. GIScience & Remote Sensing, 58(8), 1543-1570. Grigorescu, I., Kucsicsa, G., Popovici, E. A., Mitrică, B., Mocanu, I., & Dumitraşcu, M. (2021). Modelling land use/cover change to assess future urban sprawl in Romania. Geocarto International, 36(7), 721-739. Hao, S., Zhu, F., & Cui, Y. (2021). Land use and land cover change detection and spatial distribution on the Tibetan Plateau. Scientific Reports, 11(1), 1-13. Hashim, B. M., Sultan, M. A., Attyia, M. N., Al Maliki, A. A., & Al-Ansari, N. (2019). Change detection and impact of climate changes to Iraqi southern marshes using Landsat 2 Mss, Landsat 8 Oli and sentinel 2 Msi data and Gis applications. Applied Sciences, 9(10). Hassan, Z., Shabbir, R., Ahmad, S. S., Malik, A. H., Aziz, N., Butt, A., & Erum, S. (2016). Dynamics of land use and land cover change (LULCC) using geospatial techniques: a case study of Islamabad Pakistan. SpringerPlus, 5(1), 1-11. Hemati, M., Hasanlou, M., Mahdianpari, M., & Mohammadimanesh, F. (2021). A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth. Remote Sensing, 13(15), 2869. Hu,Y.Hu, Y., Batunacun., Zhen,L.Zhen, L., Zhuang,D.(2019). Assessment of Land-Use and Land-Cover Change in Guangxi, China. Scientific Reports, 9:2189. Kafi, K. M., Shafri, H. Z. M., & Shariff, A. B. M. (2014, June). An analysis of LULC change detection using remotely sensed data; A Case study of Bauchi City. In IOP conference series: Earth and environmental science (Vol. 20, No. 1, p. 012056). IOP Publishing. Leta,K,M., Demissie,T,A., Tranckner ,J. (2021). Modeling and Prediction of Land Use Land Cover Change Dynamics Based on Land Change Modeler (LCM) in Nashe Watershed, Upper Blue Nile Basin, Ethiopia. Sustainability, 13, 3740 Li, B., & Zhou, Q. (2009). Accuracy assessment on multitemporal landcover change detection using a trajectory error matrix. International Journal of Remote Sensing, 30(5), 1283-1296. Mustafa, Y. T., Ali, R. T., & Saleh, R. M. (2012). Monitoring and evaluating land cover change in the Duhok city, Kurdistan regionRegion-Iraq, by using remote sensing and GIS. International Journal of Engineering Inventions, 1(11), 28-33. Näschen, K., Diekkrüger, B., Evers, M., Höllermann, B., Steinbach, S., & Thonfeld, F. (2019). The impact of land use/land cover change (LULCC) on water resources in a tropical catchment in Tanzania under different climate change scenarios. Sustainability, 11(24), 7083. Nistor, C., Vîrghileanu, M., Cârlan, I., Mihai, B. A., Toma, L., & Olariu, B. (2021). Remote Sensing-Based Analysis of Urban Landscape Change in the City of Bucharest, Romania. Remote Sensing, 13(12), 2323. Norovsuren, B., Tseveen, B., Batomunkuev, V., Renchin, T., Natsagdorj, E., Yangiv, A., & Mart, Z. (2019, November). Land cover classification using maximum likelihood method (2000 and 2019) at Khandgait valley in Mongolia. In IOP Conference Series: Earth and Environmental Science (Vol. 381, No. 1, p. 012054). IOP Publishing. Othman, A. A., Al-Saady, Y. I., Al-Khafaji, A. K., & Gloaguen, R. (2014). Environmental change detection in the central part of Iraq using remote sensing data and GIS. Arabian Journal of Geosciences, 7(3), 1017-1028. Pickering, J., Tyukavina, A., Khan, A., Potapov, P., Adusei, B., Hansen, M. C., & Lima, A. (2021). Using Multi-Resolution Satellite Data to Quantify Land Dynamics: Applications of PlanetScope Imagery for Cropland and Tree-Cover Loss Area Estimation. Remote Sensing, 13(11), 2191. Roy,PRoy, P.S, Roy,A.Roy, A.(2010). Land Use and Land Cover Change: A Remote Sensing & GIS Perspective. Journal of the Indian Institute of Science VOL 90:4 Oct–Dec 2010 journal.library.iisc.ernet.in Shivakumar, B. R., & Rajashekararadhya, S. V. (2018). Investigation on land cover mapping capability of maximum likelihood classifier: a case study on North Canara, India. Procedia computer science, 143, 579-586. Stephens, D., & Diesing, M. (2014). A comparison of supervised classification methods for the prediction of substrate type using multibeam acoustic and legacy grain-size data. PloS one, 9(4), e93950.
کاربرد سنجش از دور و GIS در علوم محیطی، شماره 5، سال دوم، زمستان 1401، صص Application of remote sensing and GIS in environmental sciences, Vol 2, No. 5, Winter 2023, pp. 112-133 24 Tesfaw, A. T., Pfaff, A., Kroner, R. E. G., Qin, S., Medeiros, R., & Mascia, M. B. (2018). Landuse and land-cover change shape the sustainability and impacts of protected areas. Proceedings of the National Academy of Sciences, 115(9), 2084-2089. Tewabe, D., & Fentahun, T. (2020). Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia. Cogent Environmental Science, 6(1), 1778998. Traore,T.Traore, T., Lee,MLee, M,S., Rasul,A., Balew,A.(2021). Assessment of land use/land cover changes and their impacts on land surface temperature in Bangui (the capital of Central African Republic). Environmental Challenges 4. Uddin, S., Khan, A., Hossain, M. E., & Moni, M. A. (2019). Comparing different supervised machine learning algorithms for disease prediction. BMC medical informatics and decision making, 19(1), 1-16. Viana, C. M., Oliveira, S., Oliveira, S. C., & Rocha, J. (2019). Land use/land cover change detection and urban sprawl analysis. In Spatial modeling in GIS and R for earth and environmental sciences (pp. 621-651). Elsevier. | ||
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