Article
Environmental Sciences
Meiyu Wang, Hongyan Zhang, Bohan Wang, Qingyu Wang, Haihua Chen, Jialu Gong, Mingchen Sun, Jianjun Zhao
Summary: The increase in global average surface temperature has led to advancements in spring vegetation phenology, but the response to different temperature parameters varies. The sensitivity of green-up dates (GUDs) in the Mongolian Plateau grasslands to various temperature parameters was investigated. The results showed that GUDs responded differently to near-surface temperature, near-surface temperature maximum, near-surface temperature minimum, and diurnal temperature range. GUDs advanced with increasing temperature, particularly minimum temperature, while an increase in diurnal temperature range inhibited the advancement of GUDs. The sensitivity of GUDs to temperature maximum and minimum was higher than to near-surface temperature. The sensitivity of GUDs to diurnal temperature range increased over time and was found to be of great importance. The spatial and temporal distribution of temperature sensitivity was related to climatic zones rather than aridity.
Article
Biodiversity Conservation
Meiyu Wang, Jianjun Zhao, Hongyan Zhang, Zhengxiang Zhang, Xiaoyi Guo, Tingting Zhang, Rihan Wu
Summary: Understanding the response characteristics and thresholds of grassland spring phenology (GSP) to different climatic factors in arid and semi-arid regions is crucial for dealing with global climate change. This study investigated the response characteristics and thresholds of GSP to climate factors in the Mongolian Plateau using statistical analysis, random forest, and geographical detector. The findings show significant advancements in GSP over the past three decades, with vapor pressure being the most important influencing factor. The study provides valuable insights into the impact of climate change on GSP.
ECOLOGICAL INDICATORS
(2023)
Review
Environmental Sciences
Zhaobin Wang, Yikun Ma, Yaonan Zhang, Jiali Shang
Summary: The paper provides a comprehensive review of the application of remote sensing technology in grassland monitoring and management. It discusses the estimation methods for various grassland parameters and reviews the applications of remote sensing monitoring, including grassland degradation, grassland use, disaster monitoring, and carbon cycle monitoring. The study suggests that advanced estimation methods and deep learning should be explored in future research.
Article
Environmental Sciences
Xin Lyu, Xiaobing Li, Dongliang Dang, Huashun Dou, Kai Wang, Anru Lou
Summary: This paper provides a systematic and comprehensive review of the application of unmanned aerial vehicle (UAV) remote sensing in grassland ecosystem monitoring. It analyzes the application trends, introduces common UAV platforms and remote sensing sensors, reviews the application scenarios, and summarizes the current limitations and future development directions. The results are important for improving the understanding of UAV remote sensing application in grassland ecosystem monitoring and providing a scientific reference for ecological remote sensing research.
Article
Agronomy
Zhenxing Zhou, Xiaojing Yue, Heng Li, Jiajia Zhang, Junqin Liang, Xueting Yuan, Jingyi Ru, Jian Song, Ying Li, Mengmei Zheng, Dafeng Hui, Shiqiang Wan
Summary: This study investigated the impacts of climate change on the phenological sensitivity of dominant temperate grasslands in northern China. The results showed that the sensitivity of flowering phenology to precipitation change was symmetric, while warming stimulated the phenological sensitivity. These findings suggest that arid grasslands are more sensitive to climate warming and that soil moisture and vegetation index play important roles in controlling phenological sensitivity.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Agronomy
Yu Bai, Shenggong Li, Junxiong Zhou, Menghang Liu, Qun Guo
Summary: Understanding the changes and characteristics of vegetation activity on the Mongolian Plateau is crucial for addressing climate change. By analyzing satellite vegetation datasets and environmental factor datasets, it was found that vegetation activity on the plateau exhibits spatial heterogeneity and is closely related to hydrothermal conditions. The study also revealed the significant influence of temperature, vapor pressure deficit, and deep soil moisture on vegetation activity, emphasizing the importance of water availability in vegetation change.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Lijuan Miao, Zhanli Sun, Yanjun Ren, Florian Schierhorn, Daniel Mueller
Summary: The Mongolian Plateau experienced vegetation greening from 1982 to 2015, with precipitation and animal density being the most influential factors contributing to higher NDVI on the grasslands of Inner Mongolia and Mongolia. The findings challenge the common belief that higher grazing pressure is the key driver for land degradation.
LAND DEGRADATION & DEVELOPMENT
(2021)
Article
Environmental Sciences
Wu Rihan, Jianjun Zhao, Hongyan Zhang, Xiaoyi Guo
Summary: This study investigated the impacts of preseason drought on the start of the growing season in Mongolian Plateau grasslands. The findings showed that preseason drought had a significant inhibitory effect on the grassland SOS, especially in typical steppes. The research results can be used to improve the interpretation of drought response in land surface models.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Menghan Li, Juanle Wang, Kai Li, Altansukh Ochir, Chuluun Togtokh, Chen Xu
Summary: In this study, a new artificial neural network (ANN) model was selected and compared with other machine learning models to accurately estimate grass yield in the Mongolian Plateau (MP). The ANN performed better and showed that grassland productivity decreased from north to south, with 92.64% of grasslands exhibiting an increasing trend. Areas of grassland degradation were primarily located in Inner Mongolia and the central Gobi region of Mongolia. The findings suggest that the ANN model-based grass yield estimation is effective for evaluating grassland productivity in the MP and can be applied more widely.
Article
Ecology
Xuening Fang, Jianguo Wu
Summary: This study aims to explore the causes of overgrazing in Xilingol, Inner Mongolia, and identify intervention points. The research finds that herders have a general recognition of grassland degradation but do not consider overgrazing as a significant factor. They prioritize economic benefits and food provisioning services. Herders tend to protect their own grasslands while over-exploiting leased grasslands. Additionally, the government's policies are widely ignored by herders. Therefore, future grassland policies should focus on reducing poverty, improving property systems, linking the health of leased grasslands to herders' livelihoods, and developing holistic livestock management strategies.
ECOLOGY AND SOCIETY
(2022)
Article
Environmental Sciences
Emilie Delogu, Albert Olioso, Aubin Allies, Jerome Demarty, Gilles Boulet
Summary: Continuous daily estimates of evapotranspiration (ET) are crucial for water management in agriculture. This study evaluates the performance of different reference quantities in reconstructing seasonal ET from sparse estimates, highlighting the importance of revisit frequency for accurate results. Additionally, simple methods like using global radiation can provide robust estimates at a seasonal scale.
Article
Environmental Sciences
Guokun Chen, Yiwen Wang, Qingke Wen, Lijun Zuo, Jingjing Zhao
Summary: This study proposes an approach to support the restoration pattern for mountainous grasslands by integrating different aspects and key processes. The method is illustrated using the case of grasslands in southwestern China. The results show that the remote sensing identification of grassland distribution has an overall accuracy of 88.21% at the regional scale.
Article
Environmental Sciences
Ying Ma, Xiaodong Huang, Qisheng Feng, Tiangang Liang
Summary: In this study, the researchers analyzed the spatial and temporal variations in seasonal snow cover and the start of the growing season of alpine grasslands in the Tibetan Plateau in China from 2000 to 2020. The study found that the effects of seasonal snow cover on soil temperature and moisture indirectly influenced the start of the growing season of alpine grasslands.
Article
Geography, Physical
Siyuan Wang, Ming Shen, Weihua Liu, Yuanxu Ma, Hao Shi, Jingting Zhang, Di Liu
Summary: This study proposes a method for monitoring water quality in alpine rivers on the Tibetan Plateau using hyperspectral satellite data and field observations. Novel models are built to calculate key water quality parameters, and an integrated air-ground database is generated to capture the spatial heterogeneity of the water environment.
GISCIENCE & REMOTE SENSING
(2022)
Article
Environmental Studies
Huimin Zou, Jiquan Chen, Changliang Shao, Gang Dong, Meihui Duan, Qingsong Zhu, Xianglan Li
Summary: Selecting an appropriate model for simulating ecosystem respiration is crucial for understanding the carbon cycle of terrestrial ecosystems. In this study, six respiration models were evaluated and compared in four grassland ecosystems on the Mongolian Plateau. The results showed that ecosystem respiration increased exponentially with soil temperature and was influenced by soil moisture. The Martin model demonstrated the best performance among the six models. However, no single model performed best for all four grassland types, indicating the need for considering different factors in ecosystem respiration modeling.
Article
Green & Sustainable Science & Technology
Min Zhang, Juanle Wang
Summary: Disaster education is crucial for reducing disaster risks and losses worldwide. This study used bibliometrics and network analysis methods to analyze global disaster education research trends. The findings show that the research is unevenly distributed geographically, with Europe as the cluster, Asia and Africa as the evenly distributed areas, and North America and Oceania as the scattered areas. The research focuses on education, disaster nursing, disaster risk and reduction, disaster awareness, and earthquakes, and there is a need for further improvement and cooperation in the field.
Article
Environmental Sciences
Yezhi Zhou, Juanle Wang, Elena Grigorieva, Kai Li
Summary: This study investigates the spatiotemporal changes in potential evapotranspiration (PET) in the Heilongjiang River basin, China and their relationship with vegetation cover and land use. The results show significant differences in PET and fractional vegetation cover (FVC) changes according to land use, with a negative correlation between PET and vegetation coverage.
Article
Green & Sustainable Science & Technology
Yu Zhang, Juanle Wang, Yi Wang, Altansukh Ochir, Chuluun Togtokh
Summary: This study reveals the status of sustainable development in the Mongolian Plateau through analyzing land cover changes. The research finds that there is a stable rate of land cover change with diverse shifting trends for various land cover types and Sustainable Development Goals (SDGs) indicators. The study shows an increase in croplands, a decrease in water resources, a continuous increase in built areas, a decline in forest areas with recent recovery, diverse changes in grasslands with land degradation, and expansion of sand areas posing a risk of sandstorms. Additionally, there are clear differences between Mongolia and Inner Mongolia due to government policies.
Article
Chemistry, Multidisciplinary
Min Zhang, Juanle Wang
Summary: This study utilizes natural language process technology to mine research trends and hotspots on flood disasters, and analyzes their quantitative and spatial distribution features. The research shows that the current focus of flood disaster research is on risk and prediction, and the global and intercontinental distribution of research is geographically imbalanced. A flood disaster knowledge graph has been constructed to provide more information on flood disaster risk and reduction.
APPLIED SCIENCES-BASEL
(2022)
Article
Environmental Sciences
Ariunsanaa Baterdene, Seiya Nagao, Baasanjav Zorigt, Altansukh Ochir, Keisuke Fukushi, Davaadorj Davaasuren, Baasansuren Gankhurel, Enkhuur Munkhsuld, Solongo Tsetsgee, Ariuntungalag Yunden
Summary: This study is the first seasonal observation on nutrient dynamics in a small freshwater lake with eutrophication in Mongolia. The vertical profile and seasonal fluctuation of nutrients play a crucial role in understanding the biogeochemical cycles in aquatic systems.
Article
Environmental Sciences
Meer Muhammad Sajjad, Juanle Wang, Haider Abbas, Irfan Ullah, Rehan Khan, Furman Ali
Summary: This study investigates the groundwater depletion resulting from land-use and climate change in the Faisalabad district, Pakistan from 2000 to 2015. The results show a significant declining trend in groundwater levels, which is correlated with high NDBI ratio and low NDVI.
Article
Computer Science, Information Systems
Xuehua Han, Juanle Wang
Summary: This study proposes a novel framework combining complex network, topic model, and GIS to analyze the semantic spatial-temporal evolution of social media users' behaviors during emergency disaster events. The framework effectively captures the topic change and reveals the geographical differences in users' semantic changes. The research provides new insights into behavioral response to disasters and supports data-driven decision making.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Environmental Sciences
Yezhi Zhou, Juanle Wang, Elena Grigorieva, Kai Li, Huanyu Xu
Summary: Precipitation data is important for research on agricultural production and vegetation growth. This study evaluates the performance of four mainstream precipitation products (PPs) in capturing precipitation intensity and agricultural drought characteristics in the Sino-Russian border region. The results show that GPM has the most balanced capability, ERA5-Land has strong abilities in depicting annual distribution, and MSWEP and GPM perform well in different agroclimatic areas.
Article
Environmental Sciences
Chen Xu, Juanle Wang, Yu Sang, Kai Li, Jingxuan Liu, Gang Yang
Summary: This study used Landsat 8 OLI imagery combined with NDVI and land use data to identify mangroves. A semantic segmentation model called MSNet, which fuses multiple-scale features, was proposed and outperformed three other models. The results showed an increase in mangrove-covered areas in the Indus Delta from 2014 to 2022.
Article
Chemistry, Multidisciplinary
Min Zhang, Juanle Wang
Summary: Flood control is a global problem caused by global climate change and extreme weather events. This paper aims to extract flood control knowledge from academic literature using deep learning techniques. The results show that deep learning methods outperform traditional machine learning methods in accuracy but have longer training time. Based on comprehensive feature extraction capability and computational efficiency, the performances of deep learning methods were ranked as: ERNIE > Bert-CNN > Bert > Bert-RNN. This study lays a foundation for knowledge extraction in the future as more literature with method sentences accumulates.
APPLIED SCIENCES-BASEL
(2023)
Article
Geography, Physical
Yu Zhang, Juanle Wang, Altansukh Ochir, Sonomdagva Chonokhuu, Chuluun Togtokh
Summary: According to SDG 15.3, frequent sand and dust storms on the Mongolian plateau pose a long-term challenge in preventing and controlling land degradation. This study utilized MODIS remote sensing data to monitor and analyze these events. Results show a decrease in the overall frequency of sand and dust storms, with the highest occurrence in the first decade. The cross-border regions between China and Mongolia, particularly in southern Mongolia, are identified as centers of high intensity. Precipitation exhibits a strong negative correlation with the affected area, and efforts by the Mongolian and Chinese governments in wind prevention and sand control contribute to regional restoration. Recommendations for policies regarding cross-border sandstorm responses are proposed.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Geosciences, Multidisciplinary
Uyangaa Udaanjargal, Noriko Hasebe, Davaadorj Davaasuren, Keisuke Fukushi, Yukiya Tanaka, Baasansuren Gankhurel, Nagayoshi Katsuta, Shinya Ochiai, Yoshiki Miyata, Tuvshin Gerelmaa
Summary: The study analyzed sediment cores from three lakes in Mongolia, finding a correlation between temperature and sediment characteristics such as grain size and amorphous silica content. High temperature and low precipitation lead to less vegetation, resulting in changes in related sediment characteristics.
