A5052065564- Cryospheric studies and observations
- Landslides and related hazards
- Climate change and permafrost
- Flood Risk Assessment and Management
- Remote Sensing in Agriculture
- Arctic and Antarctic ice dynamics
- Nanomaterials for catalytic reactions
- Geotechnical Engineering and Analysis
- Catalytic Processes in Materials Science
- Species Distribution and Climate Change
- Ammonia Synthesis and Nitrogen Reduction
- Tree Root and Stability Studies
- Hydrology and Watershed Management Studies
- Climate variability and models
- Forest, Soil, and Plant Ecology in China
- Advanced Causal Inference Techniques
- Advanced Photocatalysis Techniques
- Adversarial Robustness in Machine Learning
- Geophysics and Gravity Measurements
- Health disparities and outcomes
- Voice and Speech Disorders
- Remote Sensing and Land Use
- TiO2 Photocatalysis and Solar Cells
- Intergenerational and Educational Inequality Studies
- Qualitative Comparative Analysis Research
East China Normal University
2021-2025
Ministry of Natural Resources
2022-2025
Anhui University
2023-2024
Southwest University
2024
Yanshan University
2023-2024
Pennsylvania State University
2019-2024
Northwest Normal University
2021-2023
Nanjing Institute of Geography and Limnology
2021-2022
Henan Polytechnic University
2022
Chinese Academy of Sciences
2021-2022
The present study aims to develop two hybrid models optimize the factors and enhance predictive ability of landslide susceptibility models. For this, a inventory map was created with 406 historical landslides 2030 non-landslide points, which randomly divided into datasets for model training (70%) testing (30%). 22 were initially selected establish factor database. We applied GeoDetector recursive feature elimination method (RFE) address optimization reduce information redundancy collinearity...
Abstract. A detailed understanding of snow cover and its possible feedback on climate change the Tibetan Plateau (TP) is great importance. However, spatiotemporal variability in phenology (SP) influencing factors TP remain unclear. Based daily gap-free product (HMRFS-TP) with 500 m resolution, this study investigated days (SCDs), onset date (SOD), end (SED) from 2002 to 2022. structural equation model was used quantify direct indirect effects meteorological factors, geographical location,...
Individuals do not respond uniformly to treatments, such as events or interventions. Sociologists routinely partition samples into subgroups explore how the effects of treatments vary by selected covariates, race and gender, on basis theoretical priors. Data-driven discoveries are also routine, yet analyses which sociologists typically go about them often problematic seldom move us beyond our biases new meaningful subgroups. Emerging machine learning methods based decision trees allow...
Traditional optical remote sensing data have been widely used for snow cover detection and monitoring. However, they are limited to daytime often suffer from large gaps due frequent cloud obscuration. This is in particular a serious challenge high-latitude polar regions where long nights prevail during the winter. Nighttime light sensors strong capability of low-level reflected moonlight. They potentially provide new way detect cover. In this study, we quantitatively analyzed moonlight...
This work aims to discuss and compare the inherent essence of different machine learning algorithms for landslide susceptibility models (LSMs), which is great significance accurate prevention detection landslides. A geospatial database was established in GIS based on various factors topography, geological conditions, environmental conditions human activities, including 22 conditioning 866 historical As model algorithms, ANN an operation composed a large number interconnected nodes, RF refers...
Non-noble metals have attracted worldwide attention for the catalytic hydrogenation of halonitrobenzene due to their high activity, low price, and abundance on Earth. However, construction effective stable non-noble-metal catalysts selective haloaniline by a simple method remains challenging. Herein, we report facile one-pot synthesis N,S-co-doped mesoporous carbon-supported through carbonization mixture metallic precursors 2-aminothiazole in molten ZnCl2. The prepared Co-NSPC catalyst...
Variations in snow cover resulting from global warming inevitably affect alpine vegetation growth on the Tibetan Plateau (TP), but our knowledge of such influences is still limited. Here, we investigated relationship between and during 2003–2020 TP using satellite-derived green-up date (GUD) metrics phenology, namely onset (SCOD), end (SCED), duration (SCD), snowmelt (SMOD). In this study, first analyzed spatiotemporal changes GUD phenology TP. Pearson’s correlation, gray relation analysis,...
Abstract. Snow cover plays an essential role in climate change and the hydrological cycle of Tibetan Plateau. The widely used Moderate Resolution Imaging Spectroradiometer (MODIS) snow products have two major issues: massive data gaps due to frequent clouds relatively low estimate accuracy complex terrain this region. Here we generate long-term daily gap-free over Plateau at 500 m resolution by applying a hidden Markov random field (HMRF) technique original MODIS past decades. were fully...
5%Co/NSPC-800 acted as an effective and robust heterogeneous catalyst for hydrogenation of halonitrobenzenes, the superior catalytic performance can be ascribed to synergistic effect Co–N x Co 0 .
Nowadays, various machine learning-based approaches using sequence information alone have been proposed for identifying DNA-binding proteins, which are crucial to many cellular processes, such as DNA replication, repair and modification. Among these methods, building a meaningful feature representation of the sequences choosing an appropriate classifier most trivial tasks. Disclosing significances contributions different spaces classifiers final prediction is utmost importance, not only...
• Using Sentinel-1/2 and bathymetry to analyze water storage of Poyang Lake. A new method reconstruct full area from partially cloud-free Sentinel-2 images. Observed at the temporal intervals 2–3 days 10-m resolution. Densified time series can more finely depict seasonal interannual variations. Lake, largest freshwater lake in China, is featured with high-frequency fluctuations unique changes level inundation areas, which plays a substantial part regulating runoff Yangtze River maintaining...
Snow depth (SD) is essential for studying climate change and hydrological cycle on the Tibetan Plateau (TP). Despite effectiveness of passive microwave remote sensing large-scale SD measurement, its low spatial resolution scanning gaps limit application, particularly in TP region where terrain complex snow distribution exhibits obvious heterogeneity. This study developed Advanced Microwave Scanning Radiometer 2 (AMSR2) downscaling models using ensemble learning methods AMSR2 brightness...
The vegetation green-up date (GUD) of the Tibetan Plateau (TP) is highly sensitive to climate change. Accurate estimation GUD essential for understanding dynamics and stability terrestrial ecosystems their interactions with climate. usually determined from a time-series indices (VIs). adoption different VIs extraction methods can lead GUDs. However, our knowledge uncertainty in these GUDs on TP still limited. In this study, we evaluated performance 2003 2020. were six Moderate Resolution...
The upper Brahmaputra River, China. long-term water level and storage variations of the River (UBR) are not yet clear due to low accessibility gauged data in high-altitude harsh environments. main objective this study is facilitate investigations river over UBR. Here we developed a hypsometric method reconstruct temporally resolved observations based on remote sensing-derived accumulative inundation area information short-term altimetric at 24 virtual stations (VSs) We further analyzed...