scispace - formally typeset
K

Kun Shi

Researcher at Chinese Academy of Sciences

Publications -  135
Citations -  5151

Kun Shi is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Environmental science & Eutrophication. The author has an hindex of 32, co-authored 111 publications receiving 2968 citations. Previous affiliations of Kun Shi include Center for Excellence in Education & State Oceanic Administration.

Papers
More filters
Journal ArticleDOI

Global loss of aquatic vegetation in lakes

TL;DR: In this article, the authors conducted a comprehensive global assessment of aquatic vegetation at 155 study sites and found that aquatic vegetation loss is accelerating, especially that of submerged aquatic vegetation and particularly in lakes with an area larger than 50 km 2.
Journal ArticleDOI

Why Lake Taihu continues to be plagued with cyanobacterial blooms through 10 years (2007-2017) efforts

TL;DR: In this paper, the authors investigated the role of lake science and environment at the State Key Laboratory for Lake Science and Environment (SKLSE) and the University of North Carolina at Chapel Hill, Institute of Marine Sciences, Morehead City, NC 28557, USA College of Environment, Hohai University, Nanjing 210098.
Journal ArticleDOI

Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250 m MODIS-Aqua data

TL;DR: Li et al. as mentioned in this paper developed and validated a robust empirical model for estimating the concentrations of total suspended matter (TSM) in Lake Taihu (China), a large turbid inland water body.
Journal ArticleDOI

Dissolved oxygen stratification and response to thermal structure and long-term climate change in a large and deep subtropical reservoir (Lake Qiandaohu, China).

TL;DR: Climate warming has had a substantial effect on water quality through changing the DO regime in Lake Qiandaohu through the stable stratification period in summer and autumn.
Journal ArticleDOI

Fifteen-year monitoring of the turbidity dynamics in large lakes and reservoirs in the middle and lower basin of the Yangtze River, China

TL;DR: In this paper, a remote sensing algorithm was developed to estimate the concentrations of the total suspended sediments (TSS) in large lakes and reservoirs over the Middle and Lower Yangtze River (MLY) basin and was based on a band ratio between 555nm and 645nm of the atmosphereherically corrected surface reflectance of the MODIS.