Centrality and city size effects on NO2 ground and tropospheric concentrations within European cities

Scientific Conference (2022, July 06)

Centrality and city size effects on NO2 ground and tropospheric concentrations within European cities

Scientific Conference (2021, November 05)

Scaling of urban heat island and nitrogen dioxide with urban population: a meta-analysis

Scientific Conference (2021, June 10)

Scaling of urban heat island & NO2 with urban population: a meta-analysis

Scientific Conference (2020, September 16)

Scaling of urban heat island & NO2 with urban population: a meta-analysis

Scientific Conference (2019, December 05)

Developing a web-based system to visualize vegetation trends by a nonlinear regression algorithm

Bachelor/master dissertation (2016)

Comparing with traditional linear regression methods that used to monitor vegetation trends, a nonlinear regression algorithm (PolyTrend) developed by Jamali et al. (2014) can provide more accurate ... [more ▼]

Comparing with traditional linear regression methods that used to monitor vegetation trends, a nonlinear regression algorithm (PolyTrend) developed by Jamali et al. (2014) can provide more accurate information of vegetation trends by fitting a polynomial line with a degree of up to three for ASCII-formed time-series NDVI (Normalized Difference Vegetation Index) dataset of a single pixel. To extend the ability of the PolyTrend algorithm for processing time-series NDVI satellite imagery and to increase its accessibility, a web-based system for visualizing vegetation trends by the PolyTrend algorithm has been developed. The PolyTrend web-based system allows users to define the value of statistical significance of the PolyTrend algorithm, the nominal range of the input data, and the range of desired NDVI input to be processed. It applies the PolyTrend algorithm to each pixel of the uploaded time-series NDVI satellite imagery dataset. It returns the types of vegetation changes, the slope of the changes of NDVI values in the whole time span, and whether the net change of NDVI increases or decreases during this period, in the forms of ASCII files (i.e. text files) and binary files (i.e. images). By refining the existing PolyTrend algorithm written in MATLAB and embedding it in a web environment, the PolyTrend web-based system has proved its ability in monitoring global vegetation trends using raw time-series NDVI satellite imagery. [less ▲]