English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Our Earth’s surface is crowding continuously with built infrastructure, causing a significant role in climate change. Since urban areas combine many components, mainly consisting of four major biophysical components, i.e. vegetation, soil, water, and built-ups that provide the base for our livelihood. The increase in built-ups has become a significant ingredient behind all the changes on the Earth’s surface, either degradation of natural resources or the evolution of artificial elements. Therefore, monitoring, tracking, and mapping the urban or built-up areas is important in both cases to derive the spatiotemporal dynamics that cause it and the after-effects. This research is focused on developing an approach for built-up extraction and mapping. The approach is a new spectral index for built-up extraction through Landsat OLI/TIRS imageries using the independent component as one of the thematic layers with a hypothesis of reduced spectral mixing while retrieving features. And the results are positive in minimizing spectral mixing when using this new built-up index to retrieve impervious surfaces while considering the biophysical components of the urban areas. The new index is authenticated and compared for seven different urban areas visually and statistically (with spectral discrimination index and error of commission and omission) to verify its performance and acceptance.

New independent component-based spectral index for precise extraction of impervious surfaces through Landsat-8 images