巴基斯坦俾路支省(Balochistan)绿地(Nasirabad)地区土地利用/土地变化探测与地表温度变化

IF 2.8 Q2 MULTIDISCIPLINARY SCIENCES
Ali Raza, Neyha Rubab Syed, Romana Fahmeed, Siham Acharki, Sajjad Hussain, Muhammad Zubair, Hussein Almohamad, Joseph Omeiza Alao, Md. Naimur Rahman, Hazem Ghassan Abdo
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引用次数: 0

摘要

研究了巴基斯坦俾路支省纳西拉巴德绿带地区土地利用/土地变化(LU/LC)和地表温度(LST)的变化。为了实现这一目标,我们使用GIS软件(ArcMap 10.7.1)分析了1993年、2003年、2013年和2023年从Landsat图像中获取的遥感数据。利用最大似然算法(MLC)的监督分类技术生成了一个真实的LU/LC分类。根据我们的研究结果,在过去的三十年中,近415.28平方公里(- 12.89%)的未开发土地已经转变为城市社区和绿地。1993 - 2023年,研究区植被面积增加288.29 km2(8.94%),居民点面积增加136.10 km2(4.22%)。整个30年的最小、最大和平均地表温度变化分别为7.50、- 5.06和1.22°C。总体而言,分析数据表明,调查地区人类住区的增加导致平均地表温度上升(1.22°C)。最后,GIS和RS可以一起用于跟踪土地的长期使用情况,这是生态友好型规划的关键数据。虽然土地用途分析/土地用途分析和土地用途分析为土地资源的合理和最佳利用提供了宝贵的见解,但政策的影响仍然有限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Land use/land change detection and determination of land surface temperature variation in green belt (Nasirabad) district of Balochistan, Pakistan
Abstract The current study determined the changes in Land Use/Land Change (LU/LC) and variation in land surface temperature (LST) in the Green Belt (Nasirabad district) area of Balochistan, Pakistan. To achieve this, we used GIS software (ArcMap 10.7.1) to analyze remote sensing data acquired from Landsat imagery taken in 1993, 2003, 2013, and 2023. A supervised classification technique using the maximum likelihood algorithm (MLC) was applied to generate a ground-truth LU/LC classification. Based on our findings, almost 415.28 km 2 (− 12.89%) of formerly undeveloped land has been transformed into urban neighborhoods and green spaces during the last three decades. Between 1993 and 2023, the study area gained 288.29 km 2 (8.94%) of vegetation and 136.10 km 2 (4.22%) of settled land. Minimum, maximum, and average LST changes were recorded as 7.50, − 5.06, and 1.22 °C for the whole thirty years. Overall, the analysis data showed that an increase in human settlements in the area investigated led to a rise in mean LST (1.22 °C). Finally, GIS and RS may be used together to track land usage over time, a crucial piece of data for eco-friendly planning. While the LU/LC and LST provide valuable insights into the rational and optimal use of land resources, the implications of policy remain constrained.
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来源期刊
SN Applied Sciences
SN Applied Sciences MULTIDISCIPLINARY SCIENCES-
自引率
3.80%
发文量
292
审稿时长
22 weeks
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