An Assessment of Spatio-temporal Land Use/Land Cover Dynamics Using Landsat Time Series Data (2008-2022) in Kuliyapitiya West Divisional Secretariat Division in Kurunagala District, Sri Lanka

W. Withanage, P. K. Mishra, B. C. Jayasinghe
{"title":"An Assessment of Spatio-temporal Land Use/Land Cover Dynamics Using Landsat Time Series Data (2008-2022) in Kuliyapitiya West Divisional Secretariat Division in Kurunagala District, Sri Lanka","authors":"W. Withanage, P. K. Mishra, B. C. Jayasinghe","doi":"10.4038/jgs.v4i1.52","DOIUrl":null,"url":null,"abstract":"The main aim of the study is to detect the changes of land use land cover (LULC) in Kuliyapitiya West Divisional Secretariat division during 2008-2022. Following the download of Landsat images in the study area, several procedures were taken to pre-process the images. This included performing radiometric and geometric corrections to eliminate undesired sensor data and atmospheric noise. The Maximum Likelihood Classification (MLC) was used as the main technique of image post-processing to derive land use maps for the target years. To evaluate the accuracy of outputs 525 ground control points were verified using the Google Earth Pro engine. The classification accuracy of the study was 86% for 2008, 79 % in 2015, and 80 % in 2022. The results showed that over the past 15 years, settlements and built-up areas increased from 20.84% to 28.14% and 0.33% to 2.71%, respectively, whereas coconut lands decreased from 58.3% to 48.6%. The settlement, which showed an increase of land area of 11.9 km2 throughout the period, was identified as the main land use gainer while coconut was the main land use that lost 15.9 km2 of its land area over the past fifteen years. The built-up area showed a 3.96 km2 overall gain during the period due to urbanization and the expansion of the industrial, educational, and service sectors in the study area. The other four land use classes have not undergone any significant changes throughout the relevant time. The study highlights the importance of combining accuracy evaluation and image classification algorithms to gain a more comprehensive understanding of the LULC changes. Hence, our findings could assist decision-makers in land use planning to efficiently guide the sustainable land management.","PeriodicalId":199553,"journal":{"name":"Journal of Geospatial Surveying","volume":"12 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geospatial Surveying","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4038/jgs.v4i1.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The main aim of the study is to detect the changes of land use land cover (LULC) in Kuliyapitiya West Divisional Secretariat division during 2008-2022. Following the download of Landsat images in the study area, several procedures were taken to pre-process the images. This included performing radiometric and geometric corrections to eliminate undesired sensor data and atmospheric noise. The Maximum Likelihood Classification (MLC) was used as the main technique of image post-processing to derive land use maps for the target years. To evaluate the accuracy of outputs 525 ground control points were verified using the Google Earth Pro engine. The classification accuracy of the study was 86% for 2008, 79 % in 2015, and 80 % in 2022. The results showed that over the past 15 years, settlements and built-up areas increased from 20.84% to 28.14% and 0.33% to 2.71%, respectively, whereas coconut lands decreased from 58.3% to 48.6%. The settlement, which showed an increase of land area of 11.9 km2 throughout the period, was identified as the main land use gainer while coconut was the main land use that lost 15.9 km2 of its land area over the past fifteen years. The built-up area showed a 3.96 km2 overall gain during the period due to urbanization and the expansion of the industrial, educational, and service sectors in the study area. The other four land use classes have not undergone any significant changes throughout the relevant time. The study highlights the importance of combining accuracy evaluation and image classification algorithms to gain a more comprehensive understanding of the LULC changes. Hence, our findings could assist decision-makers in land use planning to efficiently guide the sustainable land management.
利用大地遥感卫星时间序列数据(2008-2022 年)评估斯里兰卡库鲁纳加拉区库里亚皮蒂亚西区秘书处分区的土地利用/土地覆被时空动态
本研究的主要目的是检测库里亚皮蒂亚西区秘书处分区在 2008-2022 年期间土地利用土地覆被的变化。在研究区域下载大地遥感卫星图像后,对图像进行了若干预处理。其中包括进行辐射和几何校正,以消除不需要的传感器数据和大气噪声。最大似然分类法(MLC)是图像后处理的主要技术,用于绘制目标年份的土地利用图。为了评估输出结果的准确性,使用谷歌地球专业引擎对 525 个地面控制点进行了验证。2008 年的分类准确率为 86%,2015 年为 79%,2022 年为 80%。结果显示,在过去 15 年中,定居点和建筑密集区分别从 20.84% 增加到 28.14%,从 0.33% 增加到 2.71%,而椰子地则从 58.3% 减少到 48.6%。在此期间,定居点的土地面积增加了 11.9 平方公里,被认为是土地使用面积增加的主要原因,而椰子地则是土地使用面积减少的主要原因,在过去 15 年中,椰子地的土地面积减少了 15.9 平方公里。由于城市化以及研究区工业、教育和服务业的扩张,建成区在此期间总体增加了 3.96 平方公里。其他四个土地利用等级在相关时间内未发生任何重大变化。这项研究强调了结合精度评估和图像分类算法来更全面地了解土地利用、土地利用变化和土地利用类型变化的重要性。因此,我们的研究结果可帮助土地利用规划决策者有效指导可持续土地管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信