A hybrid physics-based method for estimating land surface temperature using radiative transfer simulations and machine learning model from Sentinel-3A SLSTR observations

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 1, 2025

Language: Английский

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Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land

Open Geosciences, Journal Year: 2024, Volume and Issue: 16(1)

Published: Jan. 1, 2024

Abstract Normalized difference vegetation index (NDVI) and land surface temperature (LST) are important indicators of ecological changes, their spatial temporal variations coupling can provide a theoretical basis for the sustainable development environment. Based on MOD13A1 MOD11A2 datasets, distribution characteristics NDVI LST from 2000 to 2020 were analyzed, trend change slope method model used calculate significant changes. Finally, was degree between LST. The study shows that: (1) From 2020, annual value Mu Us Sandy Land 0.25 0.43, showing stable upward overall, with an increase rate 0.074/(10a). proportion improvement areas in area is 81.48%. (2) There differences Land, overall decreasing northwest southeast higher west than east. greatly affected by changes use types. spatiotemporal variation different gradual warming global climate change. main reason that human activities have changed types increased local coverage. (3) negative correlation R 2 0.5073 passing significance test at 0.01 level. This indicates engineering policies effectively reduce area, thereby achieving effect improving very high level, average 0.895 area. two mainly exhibit state mutual antagonism space, reflecting importance green regulating regional result joint influence change, dominated 2020.

Language: Английский

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All weather land surface temperature estimation by combining thermal infrared and passive microwave radiometry: a study over India

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 45(18), P. 6691 - 6718

Published: Sept. 2, 2024

Land Surface Temperature (LST) plays a crucial role in water and energy cycle studies. However, clouds pose significant challenge obtaining continuous LST time series from Thermal Infrared (TIR) sensors. To overcome this challenge, study leverages the potential of Passive Microwave Radiometry (PMR), which offers all-weather observation capabilities, albeit at coarser spatial resolution to estimate over India. In study, we trained Random Forest (RF) model using clear sky either Moderate Resolution Spectro Radiometer (MODIS) or Visible Imaging Suite (VIIRS) passive microwave observations Advanced Scanning Radiometer-2 (AMSR2), enabling estimation 1 km under cloudy conditions. The performance models was evaluated by comparing RF simulated with observed data MODIS VIIRS satellites. Root Mean Square Error (RMSE) for found be 2.17 K 2.29 respectively, coefficient determination (R2) values 0.97 both models. Furthermore, comparisons in-situ resulted RMSE 2.24–3.70 2.40–4.07 LST, MODIS. Similarly, prediction model, were 2.61–3.51 2.60–3.97 These findings demonstrate radiometers highlight applicability overcast

Language: Английский

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Improving estimation of diurnal land surface temperatures by integrating weather modeling with satellite observations

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 315, P. 114393 - 114393

Published: Sept. 7, 2024

Language: Английский

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Gap-filling of land surface temperature in arid regions by combining Landsat 8 and 9 imageries

Environmental Research Communications, Journal Year: 2024, Volume and Issue: 6(10), P. 105037 - 105037

Published: Oct. 1, 2024

Abstract Land surface temperature (LST) is an important factor in land monitoring studies, but due to the presence of clouds, dust and sensor issues, there are missing values. The aims this research determine optimal parameters for reconstruction Landsat-LST images, required many applications, by harmonic analysis time series algorithm (HANTS) investigate possibility improving LST accuracy using Landsat 8 9 images simultaneously. For these aims, 91 with 100 m spatial resolution 2022 2023 employed, covering Yazd-Ardakan plain Iran. Three methods used evaluation. In method one, a part image considered as gap compared initial value after reconstruction. two, on cloudy day cloudless day, values measured thermometers at fifty points lands, difference between gap-filled satellite measurements ground calculated. three, all reconstructed original images. root mean square error (RMSE) reduces 1.3 °C when combined RMSEs 6.1 5.4 9. Method three shows that 41% study region has RMSE less than 2 only 8, while becomes 72% combining general, use improves HANTS. findings crucial regional applications remote areas limited weather stations.

Language: Английский

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Time-series studies of Land Surface Temperature in Damascus, Syria through MODIS by Google Earth Engine

Advances in Space Research, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Language: Английский

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