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Zhiyong Jiang
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China

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Journal article
Published: 08 July 2021 in Remote Sensing
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China’s largest desert freshwater lake, Hongjian Nur (HN), which is the largest habitat of relict gull (Larus relictus), has rapidly changed in recent years. However, it is difficult to quantitatively monitor the dynamics of the lake and determine the causes of its changes due to the lack of in situ observation. In this study, a remote sensing-based approach was utilized to overcome these limitations. The monthly water areas during 1990–2017 were first extracted from Landsat multispectral images via an improved method based on the floating algae index (FAI). Then, lake surface elevations measured by real-time kinematics (RTK) were used to calculate the variations in the water storage of HN. Finally, the driving factors of the rapidly changed HN in different periods were investigated by correlation analysis. The result indicated that the drivers affecting the water storage of HN in different periods were not the same. Climate change was the main driving factor of lake level fluctuation during the HN relatively stable stage (1990–1998). Drought and the intensification of human activities were the main factors for the rapid shrinkage of the HN during 1999–2010. Human activities, especially coal-related industries and reservoir impoundment, likely was the primary factors driving the decrease in the water storage of HN from 2010 to 2015. After 2015, the policies that decreased the water consumed by human activities formulated by the government and humid climate were the main factor for the expansion of HN.

ACS Style

Zhiyong Jiang; Lian Feng; Sen Li; Jida Wang; Xiaobin Cai; Peirong Lin; Xiaoyan Wang; Hongmei Zhao. The Dynamics of Hongjian Nur, the Largest Desert Freshwater Lake in China, during 1990–2017. Remote Sensing 2021, 13, 2690 .

AMA Style

Zhiyong Jiang, Lian Feng, Sen Li, Jida Wang, Xiaobin Cai, Peirong Lin, Xiaoyan Wang, Hongmei Zhao. The Dynamics of Hongjian Nur, the Largest Desert Freshwater Lake in China, during 1990–2017. Remote Sensing. 2021; 13 (14):2690.

Chicago/Turabian Style

Zhiyong Jiang; Lian Feng; Sen Li; Jida Wang; Xiaobin Cai; Peirong Lin; Xiaoyan Wang; Hongmei Zhao. 2021. "The Dynamics of Hongjian Nur, the Largest Desert Freshwater Lake in China, during 1990–2017." Remote Sensing 13, no. 14: 2690.

Journal article
Published: 18 December 2015 in Remote Sensing
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The Normalized Difference Snow Index (NDSI) is an effective index for snow-cover mapping at large scales, but in forested regions the identification accuracy for snow using the NDSI is low because of forest cover effects. In this study, typical evergreen coniferous forest zones on Qilian Mountain in the Upper Heihe River Basin (UHRB) were chosen as example regions. By analyzing the spectral signature of snow-covered and snow-free evergreen coniferous forests with Landsat Operational Land Imager (OLI) data, a novel spectral band ratio using near-infrared (NIR) and shortwave infrared (SWIR) bands, defined as (ρnir − ρswir)/(ρnir + ρswir), is proposed. Our research shows that this band ratio, named the normalized difference forest snow index (NDFSI), can be used to effectively distinguish snow-covered evergreen coniferous forests from snow-free evergreen coniferous forests in UHRB.

ACS Style

Xiao-Yan Wang; Jian Wang; Zhi-Yong Jiang; Hong-Yi Li; Xiao-Hua Hao. An Effective Method for Snow-Cover Mapping of Dense Coniferous Forests in the Upper Heihe River Basin Using Landsat Operational Land Imager Data. Remote Sensing 2015, 7, 17246 -17257.

AMA Style

Xiao-Yan Wang, Jian Wang, Zhi-Yong Jiang, Hong-Yi Li, Xiao-Hua Hao. An Effective Method for Snow-Cover Mapping of Dense Coniferous Forests in the Upper Heihe River Basin Using Landsat Operational Land Imager Data. Remote Sensing. 2015; 7 (12):17246-17257.

Chicago/Turabian Style

Xiao-Yan Wang; Jian Wang; Zhi-Yong Jiang; Hong-Yi Li; Xiao-Hua Hao. 2015. "An Effective Method for Snow-Cover Mapping of Dense Coniferous Forests in the Upper Heihe River Basin Using Landsat Operational Land Imager Data." Remote Sensing 7, no. 12: 17246-17257.