| 引用本文: | 李昕悦,谢涛,马荣华.鄱阳湖全天候水位-面积逐日数据集（2014—2023年）.湖泊科学,2025,37(2):689-704. DOI:10.18307/2025.0247 |
| Li Xinyue,Xie Tao,Ma Ronghua.Daily water level-area dataset in Lake Poyang under all-weather (2014-2023). J. Lake Sci.2025,37(2):689-704. DOI:10.18307/2025.0247 |
|
| 摘要: |
| 在气候变化与人类活动的影响下，鄱阳湖洪涝灾害和干旱频发，严重影响鄱阳湖流域的生态环境。本研究旨在通过雷达遥感技术，准确监测鄱阳湖水域面积全天候的时空动态变化，为鄱阳湖水资源评估和旱涝灾害预警提供科学依据。基于2014—2023年Sentinel-1影像，分别利用单波段阈值法、双极化水体指数以及谱间关系法，结合最大类间方差法自适应确定阈值提取水体，通过精度评价，选定最优提取方法，应用于全天候鄱阳湖水域面积提取。结合星子站、湖口站水位数据，揭示水位变化与湖泊水域面积关系，得到鄱阳湖全天候水位-面积逐日数据集，该数据集包括2014—2023年共424期鄱阳湖水域栅格数据、水域面积汇总数据以及星子站、湖口站水位数据，数据集存储为.tif、.xlsx格式。同时，利用湖泊水域面积时间序列曲线的扰动事件识别方法，识别2020年和2022年面积突变的主要因素。结果表明：谱间关系法结合最大类间方差法的阈值分割法的提取精度最优(总体精度＞95%)；2016—2023年间，鄱阳湖的水域面积呈现显著的年内变化，主要集中在河道以及湖中部。水位与面积变化总体趋于一致，水位≥14 m时，水位变化与湖泊水域面积变化呈现显著正相关。从湖泊时间序列扰动结果分类可以看出，2020年湖泊水域面积扩张的主要原因是自然因素，2022年湖泊水域面积骤减的主要原因是人为因素。 |
| 关键词: 水域面积 鄱阳湖 Sentinel-1 Google Earth Engine 时序变化 |
| DOI：10.18307/2025.0247 |
| 分类号: |
| 基金项目:国家自然科学基金项目（42361144002）；自然资源部国土卫星遥感应用重点实验室项目（KLSMNR-K202302）联合资助 |
|
| Daily water level-area dataset in Lake Poyang under all-weather (2014-2023) |
|
Li Xinyue1，2，3，Xie Tao1，Ma Ronghua2，3
|
|
1.School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044 , P.R.China ；2.Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135 , P.R.China ；3.University of Chinese Academy of Science, Nanjing, Nanjing 211135 , P.R.China
|
| Abstract: |
| The occurrence of floods and droughts in Lake Poyang is becoming increasingly frequent as a consequence of climate change and human activities, with severe repercussions for the ecological environment of the Lake Poyang basin. The objective of this study is to accurately monitor the spatial and temporal dynamics of the Lake Poyang watershed area in all weather conditions using radar remote sensing technology. This will provide a scientific basis for the assessment of water resources and early warning of droughts and floods in Lake Poyang. The single-band threshold method, dual-polarized water body index and inter-spectral relationship method, when combined with the maximum interclass variance method, were used to adaptively determine the threshold value for the extraction of water bodies. The optimal extraction method was selected through the evaluation of the accuracy and applied to the all-weather extraction of the water area of Lake Poyang. The relationship between water level change and lake watershed area was revealed when the data from Xingzi Station and Hukou Station were combined. The resulting dataset which includes the raster data of the waters of Lake Poyang, represents the daily water level-area data for Lake Poyang under all-weather conditions. The data set comprises a total of 424 periods from 2014 to 2023, including the area of the water and the water level data from Xingzi Station and Hukou Station. The data set is stored in the .tif and .xlsx formats. Furthermore, the disturbance event identification method of lake watershed area time series curve was employed to identify the main factors of sudden area changes in 2020 and 2022. The results demonstrated that the inter-spectral relationship method, when combined with the threshold segmentation method utilising maximum interclass variance, exhibited optimal extraction accuracy (overall accuracy ＞95%). Additionally, the watershed area of Lake Poyang displayed notable intra-annual fluctuations during the 2016-2023 period, with the majority of these variations concentrated in the river and the middle portion of the lake. The changes in water level and area tended to be consistent. Furthermore, when the water level was ≥14 m, there was a significant positive correlation between the changes in water level and lake watershed area. The classification of the lake time series perturbation results indicated that the primary driver of the lake watershed area expansion in 2020 was natural, whereas the primary driver of the sudden decrease in 2022 was anthropogenic. |
| Key words: Water body area Lake Poyang Sentinel-1 Google Earth Engine time series change |
