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

The present study analyses the seasonal influence of error estimated in downscaled land surface temperatures (LSTs) in a humid subtropical city using Landsat 8 data of summer and winter seasons in 2021. Thermal sharpening (TsHARP) algorithm is one of the most frequently used downscaling techniques which is originally based on normalised difference vegetation index (NDVI). This study assesses the capability of the TsHARP technique with a separate combination of four selected spectral indices (modified normalised difference water index, normalised difference bareness index, normalised difference built-up index [NDBI], and NDVI), and by determining the root mean square error (RMSE) and mean error produced by the sharpened LST. Besides, sharpened LST has also been estimated by combining the four spectral indices. It is observed that NDBI provides the most effective output (RMSE is 1.11 [30 m], 1.05 [120 m], 1.02 [240 m], and 0.99 [480 m] in summer, whereas RMSE is 0.61 [30 m], 0.59 [120 m], 0.57 [240 m], and 0.56 [480 m] in winter). NDBI-based sharpened LST generates the best relationship ( R  = 0.565 in summer and  R  = 0.537 in winter) with surface features. Fallow land generates the best relationship ( R  = 0.512 in summer and  R  = 0.530 in winter) with sharpened LST. The summer season ( R  = 0.438) generates a better relationship between surface features and sharpened LST than the winter season ( R  = 0.409).

Analysis of spectral indices-based downscaled land surface temperature in a humid subtropical city