Evaluation of Ecological Frangibility of River Source Protection Zone under the Support of Remote Sensing

Ming-qi, Chang

doi:10.1007/978-3-642-31006-5_17

Cited by 1 publication

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Abu et al [35] provided a detailed analysis of coastal land use and change patterns with Landsat imagery, which was helpful for coastal land use and environmental management practices. Chang et al [36] estimated the ecological vulnerability of a river with land use data and vegetation data from remote sensing data. Nityananda et al [37] applied remote sensing indexes such as normalized differences water index (NDWI), normalized differences vegetation index (NDVI), and normalized differences moisture index (NDMI) from Landsat 5 TM data to identify the water content pixel and its vulnerability level in the Keleghai River Basin, India.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data

Liu

Shi

2019

Sustainability

View full text Add to dashboard Cite

Ecological vulnerability assessment increases the knowledge of ecological status and contributes to formulating local plans of sustainable development. A methodology based on remote sensing data and spatial principal component analysis was introduced to discuss ecological vulnerability in the Toutun River Basin (TRB). Exploratory spatial data analysis and a geo-detector were employed to evaluate the spatial and temporal distribution characteristics of ecological vulnerability and detect the driving factors. Four results were presented: (1) During 2003 and 2017, the average values of humidity, greenness, and heat in TRB increased by 49.71%, 11.63%, and 6.51% respectively, and the average values of dryness decreased by 165.24%. However, the extreme differences in greenness, dryness, and heat tended to be obvious. (2) The study area was mainly dominated by a high and extreme vulnerability grade, and the ecological vulnerability grades showed the distribution pattern that the northern desert area was more vulnerable than the central artificial oasis, and the central artificial oasis was more vulnerable than the southern mountainous area. (3) Ecological vulnerability in TRB showed significant spatial autocorrelation characteristics, and the trend was enhanced. The spatial distribution of hot/cold spots presented the characteristics of “hot spot—cold spot—secondary hot spot—cold spot” from north to south. (4) The explanatory power of each factor of ecological vulnerability was temperature (0.5955) > land use (0.5701) > precipitation (0.5289) > elevation (0.4879) > slope (0.3660) > administrative division (0.1541). The interactions of any two factors showed a non-linear strengthening effect, among which, land use type ∩ elevation (0.7899), land use type ∩ precipitation (0.7867), and land use type ∩ temperature (0.7791) were the significant interaction for ecological vulnerability. Overall, remote sensing data contribute to realizing a quick and objective evaluation of ecological vulnerability and provide valuable information for decision making concerning ecology management and region development.

show abstract

Section: Introductionmentioning

confidence: 99%