scispace - formally typeset
T

Tong Qiu

Researcher at Duke University

Publications -  7
Citations -  214

Tong Qiu is an academic researcher from Duke University. The author has contributed to research in topics: Land cover & Phenology. The author has an hindex of 5, co-authored 7 publications receiving 82 citations. Previous affiliations of Tong Qiu include University of North Carolina at Chapel Hill.

Papers
More filters
Journal ArticleDOI

Urbanization and climate change jointly shift land surface phenology in the northern mid-latitude large cities

TL;DR: In this paper, the authors investigated the effects of urbanization on the spatial patterns of land surface phenology by comparing phenological metrics, e.g., start of season (SOS) and end-of-season (EOS), between urban center and the surrounding rural regions.
Journal ArticleDOI

Is there tree senescence? The fecundity evidence

Tong Qiu, +61 more
TL;DR: In this article, the authors combined global fecundity data, including a substantial representation of large trees, and compared size-fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture.
Journal ArticleDOI

Impacts of Urbanization on Vegetation Phenology over the Past Three Decades in Shanghai, China

TL;DR: It is demonstrated that vegetation phenology in the urban area is significantly different from its rural surroundings, and this findings have implications for urban environmental management, ranging from biodiversity protection to public health risk reduction.
Journal ArticleDOI

Divergent socioeconomic-ecological outcomes of China's Conversion of Cropland to Forest Program in the subtropical mountainous area and the semi-arid Loess Plateau.

TL;DR: Divergent CCFP outcomes on migration behavior are found, stimulating both local- and distant-migration in the Anhui site while discouraging distant-familiarity in the Shanxi site, after controlling for factors at the individual, household, community and regional levels.
Journal ArticleDOI

Understanding the continuous phenological development at daily time step with a Bayesian hierarchical space-time model: impacts of climate change and extreme weather events

TL;DR: In this paper, a Bayesian Hierarchical Space-Time model for Land Surface Phenology (BHST-LSP) was developed to synthesize remotely sensed vegetation greenness with climate covariates at a daily temporal scale from 1981 to 2014 across the entire conterminous United States.