| 论文题目 |
刊物名称 |
收录类别 |
发表年月 |
第一作者或全部作者 |
第一作者单位 |
排名 |
|---|
| Mapping global urban boundaries from the global artificial impervious area (GAIA) data |
Environmental Research Letters |
SCI |
2020 |
Xuecao Li |
Iowa State University |
1 |
| A harmonized global nighttime light dataset 1992-2018 |
Scientific Data |
SCI |
2020 |
Xuecao Li |
Iowa State University |
1 |
| An improved urban cellular automata model by using the trend adjusted neighborhood |
Ecological Processes |
SCI |
2020 |
Xuecao Li |
Iowa State University |
1 |
| High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015 |
Nature Sustainability |
SCI |
2020 |
Xiaoping Liu |
Sun Yat-Sen University |
4 |
| eveloping a method to estimate building height from Sentinel-1 data |
Remote Sensing of Environment |
SCI |
2020 |
Xuecao Li |
Iowa State University |
1 |
| A national dataset of 30-m annual urban extent dynamics (1985–2015) in the conterminous United States |
Earth System Science Data |
SCI |
2020 |
Xuecao Li |
Iowa State University |
1 |
| Urban warming advances spring phenology but reduces temperature response of plants in the conterminous United States |
Proceedings of the National Academy of Sciences of the United States of America |
SCI |
2020 |
Lin Meng |
Iowa State University |
8 |
| Annual maps of global artificial impervious areas (GAIA) between 1985 and 2018 |
Remote Sensing of Environment |
SCI |
2020 |
Peng Gong |
Tsinghua University |
2 |
| Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018 |
Science Bulletin |
SCI |
2020 |
Peng Gong |
Tsinghua University |
3 |
| A dataset of 30-meter annual vegetation phenology indicators (1985-2015) in urban areas of the conterminous Unites States |
Earth System Science Data |
SCI |
2019 |
Xuecao Li |
Iowa State University |
1 |
| Projecting global urban area growth through 2100 based on historical time-series data and future Shared Socioeconomic Pathways |
Earth’s Future |
SCI |
2019 |
Xuecao Li |
Iowa State University |
1 |
| 40-year (1978-2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing |
Science Bulletin |
SCI |
2019 |
Peng Gong |
Tsinghua University |
2 |
| Characterizing the relationship between satellite phenology and pollen season: a case study of birch |
Remote Sensing of Environment |
SCI |
2019 |
Xuecao Li |
Tsinghua University |
1 |
| A global record of annual urban dynamics (1992-2013) from nighttime lights |
Remote Sensing of Environment |
SCI |
2019 |
Yuyu Zhou |
Iowa State University |
2 |
| Mapping annual urban dynamics (1985-2015) using time series of Landsat data |
Remote Sensing of Environment |
SCI |
2018 |
Xuecao Li |
Iowa State University |
1 |
| Exploring the performance of spatio-temporal assimilation in an urban cellular automata model |
International Journal of Geographic Information Science |
SCI |
2017 |
Xuecao Li |
Tsinghua University |
1 |
| A segment derived patch-based logistic cellular automata for urban growth modeling with heuristic rules |
Computers, Environment & Urban Systems |
SSCI |
2017 |
Xuecao Li |
Tsinghua University |
1 |
| Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data |
Science of the Total Environment |
SCI |
2017 |
Xuecao Li |
Iowa State University |
1 |
| A Stepwise Calibration of Global DMSP/OLS Stable Nighttime Light Data (1992–2013) |
Remote Sensing |
SCI |
2017 |
Xuecao Li |
Iowa State University |
1 |
| Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance |
Ecological Modeling |
SCI |
2017 |
Lu Liang |
University of Arkansas |
2 |
| Urban mapping using DMSP/OLS stable night-time light: a review |
International Journal of Remote Sensing |
SCI |
2017 |
Xuecao Li |
Iowa State University |
1 |
| Using a global reference sample set and a cropland map for area estimation in China |
Science China: Earth Science |
SCI |
2017 |
Le Yu |
Tsinghua University |
2 |
| Response of vegetation phenology to urbanization in the conterminous United States |
Global Change Biology |
SCI |
2017 |
Xuecao Li |
Iowa State University |
1 |
| An “exclusion-inclusion” framework for extracting human settlements in rapidly developing regions of China from Landsat images |
Remote Sensing of Environment |
SCI |
2016 |
Xuecao Li |
Tsinghua University |
1 |
| Ten years after Hurricane Katrina: monitoring recovery in New Orleans and the surrounding areas using remote sensing. |
Science Bulletin |
SCI |
2016 |
Xuecao Li |
Tsinghua University |
1 |
| A cellular automata downscaling based 1 km global land use datasets (2010–2100) |
Science Bulletin |
SCI |
2016 |
Xuecao Li |
Tsinghua University |
1 |
| Urban growth models: progress and perspective |
Science Bulletin |
SCI |
2016 |
Xuecao Li |
Tsinghua University |
1 |
| Mapping urban land use by using Landsat images and open social data |
Remote Sensing |
SCI |
2016 |
Tengyun Hu |
Tsinghua University |
3 |
| A 30-year (1984–2013) record of annual urban dynamics of Beijing City derived from Landsat data |
Remote Sensing of Environment |
SCI |
2015 |
Xuecao Li |
Tsinghua University |
1 |
| Integrating ensemble-urban cellular automata model with an uncertainty map to improve the performance of a single model |
International Journal of Geographical Information Science |
SCI |
2015 |
Xuecao Li |
Tsinghua University |
1 |
| A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules |
International Journal of Geographical Information Science |
SCI |
2014 |
Xuecao Li |
Tsinghua University |
1 |
| Aggregative model-based classifier ensemble for improving land-use/cover classification of Landsat TM Images |
International Journal of Remote Sensing |
SCI |
2014 |
Xuecao Li |
Tsinghua University |
1 |
