Construction of Half-century Dataset of Lake Area Changes in Mapam Yumco and La??ang Co (1972?C2023)

Zeng, L.  La, Z.  Deji, Y. Z.^*  Niu, X. J.

Climate Centre of Tibet Autonomous Region, Lhasa 850000, China

Abstract: This paper developed the vector boundary data of Mapam Yumco and La??ang Co through manual visual interpretation from 1972?C2023 using the Landsat series and GF1 remote sensing images as data sources. The corresponding lake area was calculated to obtain the Mapam Yumco and La??ang Co change datasets (1972?C2023). The two datasets include the vector boundary and area of Mapam Yumco and La??ang Co in 27 periods of 1972, 1977, 1994, and 2000?C2023. The spatial resolution of the data is 30 m. The datasets are archived in the.shp data format, and both Mapam Yumco and La??ang Co are composed of 189 data files. From 1972?C2023, the area of Mapam Yumco showed a slightly decreasing trend, with an area of about 412 km². The area of La??ang Co showed a significant decreasing trend, with an average rate of ?C4.238 km²/10a. The spatial change of the Mapam Yumco Lake surface was not obvious, while the shoreline of the northeast and south of the lake changed slightly. The large changes in La??ang Co were concentrated primarily in the north and southwest.

Keywords: Mapam Yumco; La??ang Co; lake area; remote sensing

DOI: https://doi.org/10.3974/geodp.2023.04.04

CSTR: https://cstr.escience.org.cn/CSTR:20146.14.2023.04.04

Dataset Availability Statement:

The dataset supporting this paper was published and is accessible through the Digital Journal of Global Change Data Repository at:

https://doi.org/10.3974/geodb.2024.02.01.V1 or https://cstr.escience.org.cn/CSTR:20146.11.2024.02.01.V1.

https://doi.org/10.3974/geodb.2024.02.02.V1 or https://cstr.escience.org.cn/CSTR:20146.11.2024.02.02.V1.

1 Introduction

The Tibetan Plateau is known as the ??Water Tower of Asia?? due to its largest area, highest altitude, and greatest number of plateau lakes in the world^[1,2]. Lakes participate in the natural water cycle process through the convergence and evaporation of surface water, which links the atmosphere, cryosphere, and hydrosphere and reflects the response characteristics to the climate and environment^[3]. As a sensitive area, the Tibetan Plateau has a greater amplitude and intensity of climate change than the global average^[4]. Under the influence of global climate change, lake areas^[5,6], water volumes^[7,8], and water levels^[9,10] are changing to varying degrees. Therefore, establishing a long time series of lacustrine datasets from Mapam Yumco and La??ang Co is vital to studying regional ecosystem changes and response characteristics to climate change within the Tibetan Plateau.

The Mapam Yumco and La??ang Co are located in Purang county, Ngari prefecture, Tibet autonomous region. These lakes are adjacent with a river connecting them. The main peak of the Kailas Range, Kailash, stands in the north of the Mapam Yumco basin with the Himalaya Mountains in the south. Therein, Mount Naimona??nyi is in the south of the basin^[11,12]. Mapam Yumco is an inland freshwater lake, with an altitude of about 4,500 m. The lake basin is wide in the north and narrow in the south with an approximately elliptical shape. La??ang Co is a saltwater lake with an altitude of about 4,570 m and is roughly spoon-shaped. The annual average temperature of the lake area is about 2 ??C^[13].

2 Metadata of the Dataset

The metadata of the Mapam Yumco^[14] and La??ang Co change dataset (1972?C2023)^[15] are summarized in Table 1. The dataset full name, short name, authors, year of the dataset, temporal resolution, spatial resolution, data format, data size, data files, data publisher, data sharing policy, and others are all given.

Table 1  Metadata summary of the Mapam Yumco and La??ang Co changes dataset (1972?C2023)

(To be continued on the next page)

(Continued)

Table 2  Areal dynamics of Mapam Yumco and La??ang Co

3 Methods

3.1 Data Sources

The lakes on the Tibetan Plateau fluctuate under the influence of temperature, precipitation, evaporation, and glacial meltwater. Thus, the lake areas vary significantly over a year. Therefore, the selected remote sensing image data are concentrated primarily from September to November, when the lake area is relatively stable. The selected images are of good quality, with clear sky or cloud cover never exceeding 5% over the lake. The data include ASTERGDEM 30 m resolution digital elevation model (DEM) data obtained from the Geospatial Data Cloud, Landsat MSS data (path: 155, row: 39) in 1972 and 1977, Landsat TM data (path: 144, row: 39) in 1994, Landsat ETM data (path: 144, row: 39) from 2000?C2012, and GF1-WFV data from 2013?C2023 obtained by the China Resources Satellite Application Center.

3.2 Data Collection or Processing

The Landsat and GF1 remote sensing images were preprocessed using the ENVI software, including geometric correction, image enhancement, and reprojection. The projection adopted the CGCS2000 coordinate system, and the preprocessed Landsat8 image in 2015 was used as the benchmark to register the GF1 remote sensing data. Two technicians extracted the lake area using ArcGIS software via visual interpretation and cross-checked the extraction results. The vector data were added to the lake area field to obtain the lake area of Mapam Yumco and La??ang Co over the different years. Thus, the spatial database of the lake area was established.

4 Data Results and Validation

The Mapam Yumco change dataset (1972?C2023) and La??ang Co change dataset (1972?C2023) include vector data (.shp) of Mapam Yumco and La??ang Co from 1972, 1977, 1994, 2000?C2023, a total of 27 periods. The data consist of a surface element, including the lake area field (in km²) in addition to the necessary fields.

The overall area of Mapam Yumco showed a slightly decreasing trend from 1972?C2023, with an average rate of ‒0.051 km²/10a (Table 2, Figure 1). The Mapam Yumco area decreased from 414.15 to 409.19 km² from 1972?C1994, a decrease rate of 1.20%. Then, the area increased and reached a maximum in 2000 (415.78 km²). The area showed a significant decreasing trend from 2000?C2004, with an average rate of ‒10.88 km²/10a, and a fluctuating increasing trend from 2005?C2023, with an average rate of 1.63 km²/10a.

The area of La??ang Co showed a decreasing trend from 1972?C2023, with an average rate of ‒4.238 km²/10a (Table 2, Figure 2). The lake area was stable at about 268 km² from 1972?C2000. After 2000, the lake area fluctuated less, and decreased to a minimum of 248.32 km² in 2023, with an average rate of ‒5.563 km²/10a. There is no obvious overall change in Mapam Yumco based on the spatial variation of the lakes (1972?C2023) (Figure 3), and the water shoreline in the northeast and south changed slightly. The strong changes in La??ang Co were concentrated primarily in the north and southwest, and the northern part of the lake shrank obviously after 2004.

Figure 3  Spatial variations of Mapam Yumco and La??ang Co Lakes (1972?C2023)

5 Discussion and Conclusion

Lakes are an important part of the natural water cycle process and the link between the atmosphere, cryosphere, and hydrosphere. Under the influence of climate change, all these aspects change to varying degrees and are significant for studying sensitive responses to climate change. This paper used the Landsat and GF1 remote sensing image data from 1972?C2023 as sources and preprocessed the data via geometric correction, image enhancement, image registration, and reprojection. The lake areas over 27 periods were digitized and calculated through manual visual interpretation. The results of the area extraction of Mapam Yumco and La??ang Co from 1972?C2023 give a slightly decreasing trend in the area of Mapam Yumco, with an area of about 412 km²; and a decreasing trend in the area of La??ang Co, with an average rate of ‒4.238 km²/10a. After 2000, the La??ang Co area fluctuated less and reduced to a minimum in 2023. There was no strong spatial change in the Mapam Yumco Lake surface, and the shoreline in the northeast and south changed slightly. The obvious changes in La??ang Co were concentrated primarily in the north and southwest. The long-term spatial change vector datasets of Mapam Yumco and La??ang Co reveal the spatial characteristics of the lake area and surface change, which has a certain scientific reference significance for studying the sensitive response characteristics of lakes under the backdrop of climate change.

Author Contributions

Zeng, L. designed the algorithms of the dataset; La, Z. and Niu, X. J. collected and processed remote sensing image data from Landsat (MSS, TM, ETM+) and GF series satellites (GF1-WFV); Deji, Y. Z. designed the model and algorithm; and Zeng, L. wrote the data paper.

Conflicts of Interest

The authors declare no conflicts of interest.

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