Harita Mühendisliği Bölümü, Mühendislik Fakültesi, Aksaray Üniversitesi, 68100, Aksaray, Türkiye.
Environ Monit Assess. 2023 May 30;195(6):770. doi: 10.1007/s10661-023-11400-9.
Study of rapidly changing lakes and wetlands with remote sensing methods is critical for understanding the climatic and anthropogenic effects. However, most of the studies search for the change of water body in specific time periods. Although this approach reduces the workload related to downloading and processing a large number of satellite images in computer environment, it actually causes ignoring some critical changes that occurred out of specified time periods. On the other hand, this situation reduces the data volume and the limited data causes problems for the management of water resources. The Google Earth Engine (GEE) platform allows the opportunity to rapidly and practically process large-scale temporal data without downloading. In this study, areal changes in Lake Akşehir in Türkiye, from 1985 to 2020, were calculated and mapped by the GEE as a case. In order to calculate the changes, the Landsat 5 TM, 7 ETM + and 8 OLI&TIRS images were harmonized and created annual mosaics. The Normalized difference water index (NDWI) and the automated water extraction index (AWEI) were applied to these annual mosaics. By this approach, the change in the water area representing a shrank by 87% on average (according to the calculations 91% for the NDWI and 83% for the AWEI) from 1985 to 2020 was assessed practically and rapidly on annual mosaics created from all images between the studied period, instead of assessment based on images taken on only one date in the chosen years as in previous studies. Such an approach will provide time and labour savings and provide more meaningful and uninterrupted data for studies about changes in other wetland areas.
利用遥感方法研究快速变化的湖泊和湿地对于了解气候和人为影响至关重要。然而,大多数研究都在特定时期内寻找水体的变化。虽然这种方法减少了在计算机环境中下载和处理大量卫星图像的工作量,但实际上忽略了一些在指定时间之外发生的关键变化。另一方面,这种情况减少了数据量,有限的数据给水资源管理带来了问题。Google Earth Engine (GEE) 平台提供了无需下载即可快速、实际地处理大规模时间数据的机会。在这项研究中,以土耳其阿克谢希尔湖(Lake Akşehir)为例,通过 GEE 计算并绘制了从 1985 年到 2020 年的面积变化。为了计算这些变化,对 Landsat 5 TM、7 ETM + 和 8 OLI&TIRS 图像进行了调和,并创建了年度镶嵌图。对这些年度镶嵌图应用了归一化差异水体指数(NDWI)和自动水体提取指数(AWEI)。通过这种方法,可以快速实际地评估在研究期间内所有图像创建的年度镶嵌图上表示的水域面积变化,而不是像以前的研究那样仅基于所选年份中的某一天拍摄的图像进行评估。这种方法将节省时间和劳动力,并为其他湿地地区变化研究提供更有意义和不间断的数据。