Suppr超能文献

监测巴基斯坦开伯尔-普赫图赫瓦省马尔丹和恰尔萨达地区的土地利用/土地覆盖变化及其对地表温度的影响。

Monitoring land use land cover changes and its impacts on land surface temperature over Mardan and Charsadda Districts, Khyber Pakhtunkhwa (KP), Pakistan.

机构信息

Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China.

Key State Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, 430079, China.

出版信息

Environ Monit Assess. 2022 May 7;194(6):409. doi: 10.1007/s10661-022-10072-1.

Abstract

Land use/land cover (LULC) changes due to urban growth on the regional scale affect land surface temperature (LST). The present study aims to assess the LULC changes and their impact on LST over Mardan and Charsadda districts of Khyber Pakhtunkhwa (KP), Pakistan, in the period from 1990 to 2019. Landsat satellite (TM& ETM +) datasets in the period from 1990 to 2010 and Sentinel-2 images from 2016 to 2019 were used in this study. All the datasets were pre-processed and the LULC types were classified by maximum likelihood classification algorithm. The vegetation degradation was computed from normalized difference vegetation index (NDVI), and the LST was derived based on the LULC changes. The results showed that the overall accuracy of LULC classification was 87.84%. Dramatic LULC changes were observed during the last three decades, where the vegetation degradation area was decreased from 1307.8 (59.27%) to 1147.6 km (52.1%) and the barren land area increased from 816.6 (37.07%) to 961.4 km (42.64%). Similarly, the built-up area has also increased from 57.2 (2.5%) to 104.3 km (4.73%) in the years 1990 and 2019, respectively. These variations in LULC types have significantly influenced the LST from 1990 to 2019; specifically, the LST of built-up area, barren land, and vegetation cover increased from 20.1 to 32.1 °C, 21.5 to 35.5 °C, and 17.1 to 28.2 °C, respectively. The regression line plotted defines that the LST has a negative correlation with NDVI and a positive correlation with normalized difference of built-up index (NDBI). In particular, the vegetation and land covers dramatically transformed to barren land and/or to urban development over the study area in the period from 1990 to2019, which has severely affected the LST and the natural resources of the study area. Therefore, our study will be very helpful for managing the rapid environmental changes and urban planning.

摘要

土地利用/土地覆被(LULC)变化会对区域尺度的土地表面温度(LST)产生影响。本研究旨在评估 1990 年至 2019 年期间巴基斯坦开伯尔-普赫图赫瓦省马尔丹和恰尔萨达地区的土地利用/土地覆被变化及其对 LST 的影响。本研究使用了 1990 年至 2010 年期间的 Landsat 卫星(TM&ETM+)数据集和 2016 年至 2019 年期间的 Sentinel-2 图像。所有数据集都经过预处理,并通过最大似然分类算法对土地利用/土地覆被类型进行分类。从归一化差异植被指数(NDVI)中计算出植被退化情况,并根据土地利用/土地覆被变化得出 LST。结果表明,土地利用/土地覆被分类的整体精度为 87.84%。在过去的三十年中,观察到了显著的土地利用/土地覆被变化,其中植被退化面积从 1307.8 平方公里(59.27%)减少到 1147.6 平方公里(52.1%),而荒地面积从 816.6 平方公里(37.07%)增加到 961.4 平方公里(42.64%)。同样,在 1990 年至 2019 年期间,建成区面积也从 57.2 平方公里(2.5%)增加到 104.3 平方公里(4.73%)。这些土地利用/土地覆被类型的变化显著影响了 1990 年至 2019 年的 LST;具体而言,建成区、荒地和植被覆盖的 LST 分别从 20.1°C 增加到 32.1°C、从 21.5°C 增加到 35.5°C、从 17.1°C 增加到 28.2°C。绘制的回归线定义了 LST 与 NDVI 呈负相关,与归一化的建成区差异指数(NDBI)呈正相关。特别是在 1990 年至 2019 年期间,研究区域的植被和土地覆盖发生了剧烈变化,转化为荒地和/或城市发展,这严重影响了研究区域的 LST 和自然资源。因此,我们的研究将非常有助于管理快速的环境变化和城市规划。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验