Machine learning–based assessment of long-term climate variability of Kerala

Vijay, Anjali; Varija, K.

doi:10.1007/s10661-022-10011-0

Cited by 5 publications

(1 citation statement)

References 65 publications

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“…After normalizing the greenness, humidity, dryness, and heat indexes of the five periods of 2000, 2005, 2010, 2015, and 2020, the principal components were extracted to derive the RSEI of each period [37]. Table 2 shows the eigenvalue and eigenvalue contribution rate of each period of Panzhihua City.…”

Section: Principal Component Analysis Resultsmentioning

confidence: 99%

Effects of Mining on Urban Environmental Change: A Case Study of Panzhihua

Dai

Liu

et al. 2022

Remote Sensing

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The environment supplies water, land, biological resources, and climate resources for people’s daily life and development, dramatically affecting the subsistence and development of human beings. Panzhihua City is a representative resource-based industrial city of southwestern China. The abundant mineral resources provide the material basis for the city’s development. However, while the overdevelopment of the past decades has provided the preconditions for its rapid economic growth, it has also inevitably had a huge impact on its environmental quality and land use structure. In this study, the landsat remote sensing images, terrain data, socio-economic data, and mining resources exploitation data of Panzhihua were used to extract the NDVI (Normalized Difference Vegetation Index), NDBSI (Normalized Difference Build and Soil Index) and LST (Land Surface Temperature) of the past 20 years at 5-year intervals. We normalized four indicators by Principal Component Analysis to derive a remote sensing ecological index of each factor and build the Remote Sensing-based Ecological Index evaluation model. This research quantified the changes in environmental quality in the past 20 years through the range method, showing that the environmental quality of Panzhihua City first declined and then increased slowly. This research also analyzed the influence of land use types, terrain, mining area, and socio-economy on the environmental quality of Panzhihua City by grey relational analysis and buffer analysis. It is found that with the influence of its unique topographical factors and economic aspects, the environmental quality of Panzhihua City changed to varying degrees. The results provide a reliable basis for the future environmental planning of Panzhihua City and a reference for the ecological restoration of mining areas with different mineral species accurately.

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Section: Principal Component Analysis Resultsmentioning

confidence: 99%