Vohra Rubeena, Kumar Ashish, Jain Rachna, Hemanth D Jude
Bharati Vidyapeeth's College of Engineering, New Delhi, India.
Bennett University, Greater Noida, U.P., India.
Heliyon. 2024 Nov 14;10(22):e40378. doi: 10.1016/j.heliyon.2024.e40378. eCollection 2024 Nov 30.
The unplanned growth of urbanization in towns and cities has led to variations in Land Surface Temperature (LST) as the green lands are converted into impervious structures without land cover management. In this study, an effort is made to study the transformational change in natural land cover area over the years and its impact on LST in Ernakulum District of Kerala, India. As per the current statistics from one of the reports on "Observed Rainfall Variability and Changes Over Kerala State", by Indian Metrological Department in January 2020 shows that there is a significant decreasing trend in rainy days in many districts of Kerala which has resulted in highest temperature records in recent years. To understand the change in temperature trends in the district, Landsat data is collected for four different years 2005, 2010, 2015 and 2020 that maps Land Use and Land Cover (LULC) pattern for vegetation cover and built-up areas. It is important to interpret LULC maps as converting the vegetative land in built-up areas leads to multiple reflecting surfaces and temperature trapping which serves as the most direct way to understand the influence of global warming. The major merit of this research is (i) to interpret the temporal changes in LULC for categorizing the images in different land covers, (ii) to analyze Urban Thermal Field Variance Index (UTFVI) to quantify the urban heat island (UHI) effect in the region, (iii) to assess change in temperature by analyzing the spatio-temporal variations in mean temperatures for different land cover classes, and (iv) to analyze the trend of LST wrt to vegetation spectral index i.e., Normalized Differential Vegetation Index (NDVI) and spectral building index i.e., Normalized Difference Building Index (NDBI) to predict the percentage change in temperature in successive years using the widely used regression model. The computational simulation findings show that the percentage area of vegetated land decreases from 47.91 % to 29.04 % and the LST change analysis observed for years from 2005 to 2020 is 2.55 °C. For built up land, the percentage area is increased from 6.50 % to 15.27 % and the change in LST observed from year 2005-2020 is 4.82 °C which is a significant rise in temperature. The overall accuracy achieved for four respective years comes out to be 93, 89, 90, and 92 %. It has been observed from the analysis, that there is a change in temperature over the period of time from 2005 to 2020 b 3.45 °C. This is due to unplanned use of land cover classes that show considerable change in LULC maps that can be seen in the simulated results for a given study area. If the rate of change in area appeared to constantly change in this manner, then there is a possibility of further increase in land surface temperature and that will contribute in increase of temperature. The rise in mean LST from year 2020-2025 would be 0.5 °C and 1.0 °C for year 2030.
城镇地区城市化的无序发展导致了地表温度（LST）的变化，因为绿地被转变为不透水结构，且缺乏土地覆盖管理。在本研究中，我们致力于研究印度喀拉拉邦埃纳库卢姆区多年来自然土地覆盖面积的转变及其对地表温度的影响。根据印度气象部门2020年1月发布的一份关于“喀拉拉邦观测到的降雨变化和变化情况”报告中的当前统计数据，喀拉拉邦许多地区的降雨天数呈显著下降趋势，这导致了近年来的最高温度记录。为了解该地区温度趋势的变化，我们收集了2005年、2010年、2015年和2020年这四个不同年份的陆地卫星数据，这些数据绘制了植被覆盖和建成区的土地利用和土地覆盖（LULC）模式。解读LULC地图很重要，因为将植被土地转变为建成区会导致多个反射面和热量聚集，这是理解全球变暖影响的最直接方式。本研究的主要优点在于：（i）解读LULC的时间变化，以便对不同土地覆盖的图像进行分类；（ii）分析城市热场方差指数（UTFVI），以量化该地区的城市热岛（UHI）效应；（iii）通过分析不同土地覆盖类别平均温度的时空变化来评估温度变化；（iv）分析地表温度与植被光谱指数即归一化差分植被指数（NDVI）和光谱建筑指数即归一化差异建筑指数（NDBI）的关系，以使用广泛应用的回归模型预测连续几年的温度变化百分比。计算模拟结果表明，植被土地的面积百分比从47.91%降至29.04%，2005年至2020年观测到的地表温度变化为2.55°C。对于建成区土地，面积百分比从6.50%增加到15.27%，2005 - 2020年观测到的地表温度变化为4.82°C，这是温度的显著上升。四个年份各自的总体准确率分别为93%、89%、90%和92%。从分析中可以看出，2005年至2020年期间温度变化了3.45°C。这是由于土地覆盖类别的无序使用，LULC地图显示出了相当大的变化，这在给定研究区域的模拟结果中可以看到。如果面积变化率以这种方式持续变化，那么地表温度有可能进一步上升，这将导致气温升高。2020 - 2025年平均地表温度将上升0.5°C，2030年将上升1.0°C。
