Browsing by Author "Song, Kaishan"
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Item A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018(Copernicus, 2022-01-13) Tao, Hui; Song, Kaishan; Liu, Ge; Wang, Qiang; Wen, Zhidan; Jacinthe, Pierre-Andre; Xu, Xiaofeng; Du, Jia; Shang, Yingxin; Li, Sijia; Wang, Zongming; Lyu, Lili; Hou, Junbin; Wang, Xiang; Liu, Dong; Shi, Kun; Zhang, Baohua; Duan, Hongtao; Earth and Environmental Sciences, School of ScienceWater clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red blue band ratio algorithm was applied to map SDD for lakes (>0.01 km2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD <2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of <0.5 and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km2, whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).Item Characterization of CDOM in saline and freshwater lakes across China using spectroscopic analysis(Elsevier, 2019-03) Song, Kaishan; Shang, Yingxin; Wen, Zhidan; Jacinthe, Pierre-André; Liu, Ge; Lyu, Lili; Fang, Chong; Earth Sciences, School of ScienceColored dissolved organic matter (CDOM) is a major component of DOM in waters, and plays a vital role in carbon cycling in inland waters. In this study, the light absorption and three-dimensional excitation-emission matrix spectra (EEMs) of CDOM of 936 water samples collected in 2014–2017 from 234 lakes in five regions across China were examined to determine relationships between lake water sources (fresh versus saline) and their fluorescence/absorption characteristics. Results indicated significant differences regarding DOC concentration and aCDOM(254) between freshwater (6.68 mg C L−1, 19.55 m-1) and saline lakes (27.4 mg C L−1, 41.17 m-1). While humic-like (F5) and fulvic-like (F3) compounds contributed to CDOM fluorescence in all lake waters significantly, their contribution to total fluorescence intensity (FT) differed between saline and freshwater lakes. Significant negative relationships were also observed between lake altitude with either F5 (R2 = 0.63, N = 306) or FT (R2 = 0.64, N = 306), suggesting that the abundance of humic-like materials in CDOM tends to decrease with increased in lakes altitude. In high-altitude lakes, strong solar irradiance and UV exposure may have induced photo-oxidation reactions resulting in decreased abundance of humic-like substances and the formation of low molecular weight compounds. These findings have important implications regarding our understanding of C dynamics in lacustrine systems and the contribution of these ecosystems to the global C cycle.Item Climate-driven variations in suspended particulate matter dominate water clarity in shallow lakes.(Optica, 2022-01) Fang, Chong; Jacinthe, Pierre-Andre; Song, Changchun; Zhang, Chi; Song, Kaishan; Earth Science, School of ScienceSecchi disk depth (SDD) has long been considered as a reliable proxy for lake clarity, and an important indicator of the aquatic ecosystems. Meteorological and anthropogenic factors can affect SDD, but the mechanism of these effects and the potential control of climate change are poorly understood. Preliminary research at Lake Khanka (international shallow lake on the China-Russia border) had led to the hypothesis that climatic factors, through their impact on suspended particulate matter (SPM) concentration, are key drivers of SDD variability. To verify the hypothesis, Landsat and MODIS images were used to examine temporal trend in these parameters. For that analysis, the novel SPM index (SPMI) was developed, through incorporation of SPM concentration effect on spectral radiance, and was satisfactorily applied to both Landsat (R= 0.70, p < 0.001) and MODIS (R= 0.78, p < 0.001) images to obtain remote estimates of SPM concentration. Further, the SPMI algorithm was successfully applied to the shallow lakes Hulun, Chao and Hongze, demonstrating its portability. Through analysis of the temporal trend (1984-2019) in SDD and SPM, this study demonstrated that variation in SPM concentration was the dominant driver (explaining 63% of the variation as opposed to 2% due to solar radiation) of SDD in Lake Khanka, thus supporting the study hypothesis. Furthermore, we speculated that variation in wind speed, probably impacted by difference in temperature between lake surface and surrounding landscapes (greater difference between 1984-2009 than after 2010), may have caused varying degree of sediment resuspension, ultimately controlling SPM and SDD variation in Lake Khanka.Item Convolutional neural network model for soil moisture prediction and its transferability analysis based on laboratory Vis-NIR spectral data(Elsevier, 2021-12) Chen, Yu; Li, Lin; Whiting, Michael; Chen, Fang; Sun, Zhongchang; Song, Kaishan; Wang, Qinjun; Earth Sciences, School of ScienceLaboratory visible near infrared reflectance (Vis-NIR, 400–2500 nm) spectroscopy has the advantages of simplicity, fast and non-destructive which was used for SM prediction. However, many previously proposed models are difficult to transfer to unknown target areas without recalibration. In this study, we first developed a suitable Convolutional Neutral Network (CNN) model and transferred the model to other target areas for two situations using different soil sample backgrounds under 1) the same measurement conditions (DSSM), and 2) under different measurement conditions (DSDM). We also developed the CNN models for the target areas based on their own datasets and traditional PLS models was developed to compare their performances. The results show that one dimensional model (1D-CNN) performed strongly for SM prediction with average R2 up to 0.989 and RPIQ up to 19.59 in the laboratory environment (DSSM). Applying the knowledge-based transfer learning method to an unknown target area improved the R2 from 0.845 to 0.983 under the DSSM and from 0.298 to 0.620 under the DSDM, which performed better than data-based spiking calibration method for traditional PLS models. The results show that knowledge-based transfer learning was suitable for SM prediction under different soil background and measurement conditions and can be a promising approach for remotely estimating SM with the increasing amount of soil dataset in the future.Item Dissolved carbon and CDOM in lake ice and underlying waters along a salinity gradient in shallow lakes of Northeast China(Elsevier, 2019) Song, Kaishan; Wen, Zhidan; Jacinthe, Pierre-André; Zhao, Ying; Du, Jia; Earth Sciences, School of ScienceThe variations of DOC and DIC concentrations in lake ice and underlying waters were examined in 40 shallow lakes across the Songnen Plain, Northeast China. The lakes, frozen annually during winter, included freshwater and brackish systems (EC > 1000 μS cm−1; range: 171–12607 μS cm−1 in underlying water). Results showed that lake ice contained lower DOC (7.2 mg L−1) and DIC (6.7 mg L−1) concentration compared to the underlying waters (58.2 and 142.4 mg L−1, respectively). Large differences in DOC and DIC concentrations of underlying waters were also observed between freshwater (mean ± SD: 22.3 ± 11.5 mg L−1, 50.7 ± 20.6 mg L−1) and brackish lakes (83.3 ± 138.0 mg L−1, 247.0 ± 410.5 mg L−1). A mass balance model was developed to describe the relative distribution of solutes and chemical attributes between ice and the underlying waters. Results showed that water depth and ice thickness were the key factors regulating the spatial distribution of solutes in the frozen lakes. Chromophoric dissolved organic matter (CDOM) absorption coefficient at 320 nm, aCDOM(320) and specific UV absorbance (SUVA254) were used to characterize CDOM composition and quality. Compared to the underlying waters, CDOM present in ice largely included low aromaticity organic substances, an outcome perhaps facilitated by ice formation and photo-degradation. In ice and underlying freshwaters, CDOM predominantly included organic C fractions of high aromaticity, while low aromaticity organic substances were observed for brackish lakes. Results of this study suggest that, if water salinity increases due to climate change and anthropogenic activities, significant changes can occur in the dissolved carbon and fate of CDOM in these shallow lakes.Item Global divergent trends of algal blooms detected by satellite during 1982–2018(Wiley, 2022-04) Fang, Chong; Song, Kaishan; Paerl, Hans W.; Jacinthe, Pierre-Andre; Wen, Zhidan; Liu, Ge; Tao, Hui; Xu, Xiaofeng; Kutser, Tiit; Wang, Zongming; Duan, Hongtao; Shi, Kun; Shang, Yingxin; Lyu, Lili; Li, Sijia; Yang, Qian; Lyu, Dongmei; Mao, Dehua; Zhang, Baohua; Cheng, Shuai; Lyu, Yunfeng; Earth and Environmental Sciences, School of ScienceAlgal blooms (ABs) in inland lakes have caused adverse ecological effects, and health impairment of animals and humans. We used archived Landsat images to examine ABs in lakes (>1 km2) around the globe over a 37-year time span (1982–2018). Out of the 176032 lakes with area >1 km2 detected globally, 863 were impacted by ABs, 708 had sufficiently long records to define a trend, and 66% exhibited increasing trends in frequency ratio (FRQR, ratio of the number of ABs events observed in a year in a given lake to the number of available Landsat images for that lake) or area ratio (AR, ratio of annual maximum area covered by ABs observed in a lake to the surface area of that lake), while 34% showed a decreasing trend. Across North America, an intensification of ABs severity was observed for FRQR (p < .01) and AR (p < .01) before 1999, followed by a decrease in ABs FRQR (p < .01) and AR (p < .05) after the 2000s. The strongest intensification of ABs was observed in Asia, followed by South America, Africa, and Europe. No clear trend was detected for the Oceania. Across climatic zones, the contributions of anthropogenic factors to ABs intensification (16.5% for fertilizer, 19.4% for gross domestic product, and 18.7% for population) were slightly stronger than climatic drivers (10.1% for temperature, 11.7% for wind speed, 16.8% for pressure, and for 11.6% for rainfall). Collectively, these divergent trends indicate that consideration of anthropogenic factors as well as climate change should be at the forefront of management policies aimed at reducing the severity and frequency of ABs in inland waters.Item Impacts of Climate Change on Tibetan Lakes: Patterns and Processes(MDPI, 2018-02-26) Mao, Dehua; Wang, Zongming; Yang, Hong; Li, Huiying; Thompson, Julian R.; Li, Lin; Song, Kaishan; Chen, Bin; Gao, Hongkai; Wu, Jianguo; Earth Sciences, School of ScienceHigh-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures.Item Impacts of Climate Change on Tibetan Lakes: Patterns and Processes(MDPI, 2018-02-26) Mao, Dehua; Wang, Zongming; Yang, Hong; Li, Huiying; Thompson, Julian; Li, Lin; Song, Kaishan; Chen, Bin; Gao, Hongkai; Wu, Jianguo; Earth Sciences, School of ScienceHigh-altitude inland-drainage lakes on the Tibetan Plateau (TP), the earth’s third pole, are very sensitive to climate change. Tibetan lakes are important natural resources with important religious, historical, and cultural significance. However, the spatial patterns and processes controlling the impacts of climate and associated changes on Tibetan lakes are largely unknown. This study used long time series and multi-temporal Landsat imagery to map the patterns of Tibetan lakes and glaciers in 1977, 1990, 2000, and 2014, and further to assess the spatiotemporal changes of lakes and glaciers in 17 TP watersheds between 1977 and 2014. Spatially variable changes in lake and glacier area as well as climatic factors were analyzed. We identified four modes of lake change in response to climate and associated changes. Lake expansion was predominantly attributed to increased precipitation and glacier melting, whereas lake shrinkage was a main consequence of a drier climate or permafrost degradation. These findings shed new light on the impacts of recent environmental changes on Tibetan lakes. They suggest that protecting these high-altitude lakes in the face of further environmental change will require spatially variable policies and management measures.Item Monitoring of water surface temperature of Eurasian large lakes using MODIS land surface temperature product(Wiley, 2020-07) Du, Jia; Jacinthe, Pierre-Andre; Zhou, Haohao; Xiang, Xiaoyun; Zhao, Boyu; Wang, Min; Song, Kaishan; Earth Sciences, School of ScienceIn this study, data from MODIS land surface temperature product level 3 (MOD11A2) were used to investigate the spatiotemporal variation of Eurasian lakes water surface temperature (LSWT) from 2001 to 2015, and to examine the most influencing factors of that variation. The temperature of most lakes in the dry climate zone and in the equatorial climatic zone varied from 17 to 31°C and from 23 to 27°C, respectively. LSWTs in the warm temperate and cold climatic zones were in the range of 20 to 27°C and −0.6 and 17°C, respectively. The average day time LSWT in the polar climate zone was −0.71°C in the summer. Lakes in high latitude and in the Tibetan Plateau displayed low LSWT, ranging from −11 to 26°C during the night time. Large spatial variations of diurnal temperature difference (DTD) were observed in lakes across Eurasia. However, variations in DTDs were small in lakes located in high latitude and in tropical rainforest regions. The shallow lakes showed a rapid response of LSWT to solar and atmospheric forcing, while in the large and deep lakes, that response was sluggish. Results of this study demonstrated the applicability of remote sensing and MODIS LST products to capture the spatial–temporal variability of LSWT across continental scales, in particular for the vast wilderness areas and protected environment in high latitude regions of the world. The approach can be used in future studies examining processes and factors controlling large scale variability of LSWT.Item National wetland mapping in China: a new product resulting from object-based and hierarchical classification of Landsat 8 OLI images(Elsevier, 2020-06) Mao, Dehua; Wang, Zongming; Du, Baojia; Li, Lin; Tian, Yanlin; Jia, Mingming; Zeng, Yuan; Song, Kaishan; Jiang, Ming; Wang, Yeqiao; Earth Sciences, School of ScienceSpatially and thematically explicit information of wetlands is important to understanding ecosystem functions and services, as well as for establishment of management policy and implementation. However, accurate wetland mapping is limited due to lacking an operational classification system and an effective classification approach at a large scale. This study was aimed to map wetlands in China by developing a hybrid object-based and hierarchical classification approach (HOHC) and a new wetland classification system for remote sensing. Application of the hybrid approach and the wetland classification system to Landsat 8 Operational Land Imager data resulted in a wetland map of China with an overall classification accuracy of 95.1%. This national scale wetland map, so named CAS_Wetlands, reveals that China’s wetland area is estimated to be 451,084 ± 2014 km2, of which 70.5% is accounted by inland wetlands. Of the 14 sub-categories, inland marsh has the largest area (152,429 ± 373 km2), while coastal swamp has the smallest coverage (259 ± 15 km2). Geospatial variations in wetland areas at multiple scales indicate that China’s wetlands mostly present in Tibet, Qinghai, Inner Mongolia, Heilongjiang, and Xinjiang Provinces. This new map provides a new baseline data to establish multi-temporal and continuous datasets for China’s wetlands and biodiversity conservation.