A5084017794- Land Use and Ecosystem Services
- Flood Risk Assessment and Management
- Urban Transport and Accessibility
- Impact of Light on Environment and Health
- Environmental Changes in China
- Urban Heat Island Mitigation
- Educational Technology and Pedagogy
- Environmental Impact and Sustainability
- Remote Sensing and Land Use
- Urban Green Space and Health
- Soil Carbon and Nitrogen Dynamics
- Energy, Environment, Economic Growth
- Ideological and Political Education
- Innovative Teaching Methods
- Wildlife-Road Interactions and Conservation
- Air Quality and Health Impacts
- Climate change impacts on agriculture
- Disaster Management and Resilience
- Soil Geostatistics and Mapping
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
2021
Nanjing Normal University
2021
Tsinghua University
2017-2020
Peking University
2017
Tiangong University
2014
Nighttime light data can characterize urbanization, economic development, population density, energy consumption and other human activities. Additionally, carbon dioxide (CO2) emissions are closely related to the scope intensity of In this study, we assess utility nighttime as a powerful tool reflect CO2 from consumption, analyze uncertainty associated with different for modeling emissions, provide guidance reference based on data. paper, Mainland China was taken case datasets (the Defense...
Abstract The rapid urbanization in China has been associated with a growing hunger for energy consumption and steadily-increasing CO 2 emissions. In this paper, an integrated system dynamics model composed of four sub-models is developed to simulate the from 1998 2050. Three scenarios are provided: accelerated economic development, emission reduction constraint, low-carbon oriented. result reveals that growth sufficient supply will foster China’s all three scenarios. Under low carbon...
Abstract:
For the scientific management of farmland, it is significant to understand spatio-temporal variability soil organic matter and study influences related factors. Using geostatistical theory, GIS spatial analysis, trend analysis a Geographically Weighted Regression (GWR) model, this analyzed response climate socio-economic factors in central Heilongjiang Province during past 25 years. Second survey data China for 1979–1985, 2005 field sampling data, observations 1980–2005 were analyzed. First,...