This research investigates the ecological importance,changes,and status of mangrove wetlands along China’s coastline.Visual interpretation,geological surveys,and ISO clustering unsupervised classification methods are...This research investigates the ecological importance,changes,and status of mangrove wetlands along China’s coastline.Visual interpretation,geological surveys,and ISO clustering unsupervised classification methods are employed to interpret mangrove distribution from remote sensing images from 2021,utilizing ArcGIS software platform.Furthermore,the carbon storage capacity of mangrove wetlands is quantified using the carbon storage module of InVEST model.Results show that the mangrove wetlands in China covered an area of 278.85 km2 in 2021,predominantly distributed in Hainan,Guangxi,Guangdong,Fujian,Zhejiang,Taiwan,Hong Kong,and Macao.The total carbon storage is assessed at 2.11×10^(6) t,with specific regional data provided.Trends since the 1950s reveal periods of increase,decrease,sharp decrease,and slight-steady increases in mangrove areas in China.An important finding is the predominant replacement of natural coastlines adjacent to mangrove wetlands by artificial ones,highlighting the need for creating suitable spaces for mangrove restoration.This study is poised to guide future mangroverelated investigations and conservation strategies.展开更多
Noise mapping is an effective tool to measure noise.By noise mappingone can represent noise graphically.Noise mapping was carried out for Ahmedabad city.Data was collected at 633 different locations across the city.La...Noise mapping is an effective tool to measure noise.By noise mappingone can represent noise graphically.Noise mapping was carried out for Ahmedabad city.Data was collected at 633 different locations across the city.Latitude,longitude and real-time noise levels were noted at each location.ArcGIS software was used for creating noise maps and colour noise maps.The percentage of the city covered by the respective value of contour of noise was also found using the software,as well as the number of people in the city suffering from the respective levels of noise.Considering all the results,a multi-linear regression model was developed to predict noise,using SPSS statistics software.The developed model was analysed using an R^(2)test as well as a paired t-test.展开更多
基金supported by China Geological Survey(DD20211301).
文摘This research investigates the ecological importance,changes,and status of mangrove wetlands along China’s coastline.Visual interpretation,geological surveys,and ISO clustering unsupervised classification methods are employed to interpret mangrove distribution from remote sensing images from 2021,utilizing ArcGIS software platform.Furthermore,the carbon storage capacity of mangrove wetlands is quantified using the carbon storage module of InVEST model.Results show that the mangrove wetlands in China covered an area of 278.85 km2 in 2021,predominantly distributed in Hainan,Guangxi,Guangdong,Fujian,Zhejiang,Taiwan,Hong Kong,and Macao.The total carbon storage is assessed at 2.11×10^(6) t,with specific regional data provided.Trends since the 1950s reveal periods of increase,decrease,sharp decrease,and slight-steady increases in mangrove areas in China.An important finding is the predominant replacement of natural coastlines adjacent to mangrove wetlands by artificial ones,highlighting the need for creating suitable spaces for mangrove restoration.This study is poised to guide future mangroverelated investigations and conservation strategies.
文摘Noise mapping is an effective tool to measure noise.By noise mappingone can represent noise graphically.Noise mapping was carried out for Ahmedabad city.Data was collected at 633 different locations across the city.Latitude,longitude and real-time noise levels were noted at each location.ArcGIS software was used for creating noise maps and colour noise maps.The percentage of the city covered by the respective value of contour of noise was also found using the software,as well as the number of people in the city suffering from the respective levels of noise.Considering all the results,a multi-linear regression model was developed to predict noise,using SPSS statistics software.The developed model was analysed using an R^(2)test as well as a paired t-test.
