Paper Info
Title
Decision support system based on spatial and temporal pattern evolution of ecological environmental quality in the Yellow River Delta from 2000 to 2020
Abstract
The Yellow River Delta is the youngest large river delta in the world and is an important part of the national coordinated regional development strategy. In this paper, using the Google Earth Engine (GEE) platform, Landsat remote sensing images in the summer (June–September) of 2000, 2005, 2010, 2015, and 2020 were selected to remove clouds and mask water body information. The median value is taken to synthesize the remote sensing images of each year and extract multiple indices of greenness, wetness, heatness, and dryness. Then integrate the population density data by principal component analysis to quickly construct an improved composite remote sensing ecological index (CRSEI). The results showed that the average contribution of the six indicators of greenness (NDVI and FVC), wetness (NDMI), heatness (LST), dryness (NDBSI), and population density (Pop) to the first principal component (PC1) was above 79%, and the construction of an improved comprehensive remote sensing ecological index (CRSEI) based on PC1 was feasible in the Yellow River Delta. In the past 20 years, the ecological and environmental quality of the Yellow River Delta has shown a continuous trend of improvement. The ecological environment quality has improved by 3570.95 square kilometers, accounting for 48.0% of the total area, while the ecological environment quality has degraded by 712.99 square kilometers, accounting for only 9.6% of the total area. The improved area is 38.4% more than the degraded area, which shows that the ecological environment quality has improved in general. The ecological environment quality in Kenli County has improved the most. The ecological projects have been implemented in this area with the most obvious effect, and the investment in ecological environmental protection in this area should be continued or increased. The use of the GEE platform can obtain timely and accurate spatial and temporal patterns and evolution of ecological environmental quality in the Yellow River Delta, which is of great significance for ecological environmental protection and construction.
Year
DOI
Venue
2022
10.1007/s00500-022-07399-9
Soft Computing
Keywords
DocType
Volume
Yellow River Delta, Eco-environment, Remote sensing ecological index, Google earth engine
Journal
26
Issue
ISSN
Citations 
20
1432-7643
0
PageRank 
References 
Authors
0.34
3
4
Name
Order
Citations
PageRank
Xin Zhao14712.60
Ping Wang21012.69
Yasir Muhammad310.68
Liu Zhan400.34