Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010

Tan, Chao; Ma, Mingguo; Kuang, Honghai

doi:10.3390/rs9020150

Cited by 39 publications

(24 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The time series for each pixel had a length of n = 15, spanning from 2003 to 2017. The rate of change was applied to estimate the regional trend using linear regression with the effects of the constant bias inherent in the data considered negligible [51][52][53][54][55]. Thus, we assessed the interannual variations in LST from the slope [51,55].…”

Section: Mean Lstmentioning

confidence: 99%

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

et al. 2020

View full text Add to dashboard Cite

It is very important to understand the temporal and spatial variations of land surface temperature (LST) in Africa to determine the effects of temperature on agricultural production. Although thermal infrared remote sensing technology can quickly obtain surface temperature information, it is greatly affected by clouds and rainfall. To obtain a complete and continuous dataset on the spatiotemporal variations in LST in Africa, a reconstruction model based on the moderate resolution imaging spectroradiometer (MODIS) LST time series and ground station data was built to refactor the LST dataset (2003–2017). The first step in the reconstruction model is to filter low-quality LST pixels contaminated by clouds and then fill the pixels using observation data from ground weather stations. Then, the missing pixels are interpolated using the inverse distance weighting (IDW) method. The evaluation shows that the accuracy between reconstructed LST and ground station data is high (root mean square er–ror (RMSE) = 0.84 °C, mean absolute error (MAE) = 0.75 °C and correlation coefficient (R) = 0.91). The spatiotemporal analysis of the LST indicates that the change in the annual average LST from 2003–2017 was weak and the warming trend in Africa was remarkably uneven. Geographically, “the warming is more pronounced in the north and the west than in the south and the east”. The most significant warming occurred near the equatorial region in South Africa (slope > 0.05, R > 0.61, p < 0.05) and the central (slope = 0.08, R = 0.89, p < 0.05) regions, and a nonsignificant decreasing trend occurred in Botswana. Additionally, the mid-north region (north of Chad, north of Niger and south of Algeria) became colder (slope > −0.07, R = 0.9, p < 0.05), with a nonsignificant trend. Seasonally, significant warming was more pronounced in winter, mostly in the west, especially in Mauritania (slope > 0.09, R > 0.9, p < 0.5). The response of the different types of surface to the surface temperature has shown variability at different times, which provides important information to understand the effects of temperature changes on crop yields, which is critical for the planning of agricultural farming systems in Africa.

show abstract

Section: Mean Lstmentioning

confidence: 99%

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Lakes are very sensitive to climate change or human activities [5]. In recent decades, many lakes have shrunk significantly due to intensive human activities and climate change [6,7]. Moreover, shrinking and drying of lakes has aggravated the deterioration of the regional environment and directly threatened the livelihoods of local people [8].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Dynamic Changes of the Baiyangdian Lake Surface Based on a Complex Water Extraction Method

Wang

Jiang

et al. 2018

Water

View full text Add to dashboard Cite

Lakes have an important role in human life and the ecological environment, but they are easily affected by human activity and climate change, especially around urban areas. Hence, it is critical to extract water with a high precision method and monitor long-term sequence dynamic changes in lakes. As the greatest natural lake of the Beijing-Tianjin-Hebei region, Baiyangdian Lake has a significant function in human life, socio-economic development, and regional ecological balance. This lake area has shown large changes due to human activity and climate change. The change monitoring process of the water surface is of great significance in providing support for the management and protection of the lake. The Spectrum Matching based on Discrete Particle Swarm Optimization (SMDPSO) method is a new, robust, and low-cost method for water extraction, that has obvious advantages in extracting complex water surfaces. In this paper, the SMDPSO method was used to extract the water surface of Baiyangdian Lake by Landsat images from 1984 to 2018. This method has a good effect on complex water surface extraction with vegetation, shadows, and so forth, and the Landsat images have higher resolution and longer time series. The main contents and results of this paper are as follows: (1) We verified the applicability of the SMDPSO method in the Baiyangdian Lake using visual interpretation and correlation analysis. The relative errors between observed and extracted results were all less than 5% in spring, summer, and fall, and the correlation coefficient between the water area and water level was 0.96. (2) According to seasonal verification and comparison of the extraction results, the SMDPSO method was used to extract the water surface area of Baiyangdian Lake during spring of the years 1984–2018. Water area changes of Baiyangdian Lake can be divided into four periods: Dry period (1984–1988), degraded period (1989–2000), stable period (2000–2008), and recovery period (2008–2018). The water area reached a maximum of 280 km2 in 1989 and a minimum of 44 km2 in 2002. (3) The possible causes of the changes in the water area of Baiyangdian Lake were also analyzed. The changes were caused by climate and human activities during the first and second periods, but mainly human activities during the third and fourth periods. In fact, effective policies combined with water conservancy projects were directly conducive to improving or even recovering the water and ecological environment of Baiyangdian Lake. Considering its importance for the benign development of the Beijing-Tianjin-Hebei Region and the construction of the Xiong’an New Area, a policy is necessary to ensure that the lake’s ecological environment will not be destroyed under the premise of economic development.

show abstract

“…In addition, the NDVI value increases with the increase in vegetation coverage [44]. After extracting the lake area, the change rate of the lake area was calculated by using Equation (1) [45]:…”

Section: Modis Ndvi Datamentioning

confidence: 99%

Lake Area Changes and Their Influence on Factors in Arid and Semi-Arid Regions along the Silk Road

et al. 2018

Self Cite

View full text Add to dashboard Cite

Abstract:In the context of global warming, the changes in major lakes and their responses to the influence factors in arid and semi-arid regions along the Silk Road are especially important for the sustainable development of local water resources. In this study, the areas of 24 lakes were extracted using MODIS NDVI data, and their spatial-temporal characteristics were analyzed. In addition, the relationship between lake areas and the influence factors, including air temperature, precipitation, evapotranspiration, land use and land cover change (LULCC) and population density in the watersheds, were investigated. The results indicated that the areas of most lakes shrank, and the total area decreased by 22,189.7 km 2 from 2001 to 2016, except for those of the lakes located on the Qinghai-Tibetan Plateau. The air temperature was the most important factor for all the lakes and increased at a rate of 0.113 • C/a during the past 16 years. LULCC and the increasing population density markedly influenced the lakes located in the middle to western parts of this study area. Therefore, our results connecting lake area changes in the study region highlight the great challenge of water resources and the urgency of implementation of the green policy in the One Belt and One Road Initiative through international collaboration.

show abstract

Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010

Cited by 39 publications

References 31 publications

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

Analysis of the Dynamic Changes of the Baiyangdian Lake Surface Based on a Complex Water Extraction Method

Lake Area Changes and Their Influence on Factors in Arid and Semi-Arid Regions along the Silk Road

Contact Info

Product

Resources

About