Eco-environmental changes due to human activities in the Erhai Lake Basin from 1990 to 2020.

Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit-based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.

Regional scale terrace mapping in fragmented mountainous areas using multi-source remote sensing data and sample purification strategy.

As a stepped cross section of farmland built along the contour lines, terrace is widely distributed on hill-slopes. It changes the original surface slope and runoff coefficient, reduces soil nutrient loss, and has become the most important soil erosion control measure in China. Accurate terrace mapping at regional scale is crucial for soil conservation, agriculture sustainability and ecological planning.

Spatiotemporal change patterns and driving factors of land surface temperature in the Yunnan-Kweichow Plateau from 2000 to 2020.

In this study, the spatiotemporal change patterns and driving factors of land surface temperature (LST) on the Yunnan-Kweichow Plateau (YKP) during 2000-2020 are investigated by using the Thermal and Reanalysis Integrating Moderate-resolution Spatial-seamless (TRIMS) LST dataset provided by National Tibetan Plateau Data Center. The YKP LST spatiotemporal change patterns are revealed at annual, seasonal, monthly, and daily scales. Furthermore, seven driving factors such as air temperature, land cover types, normalized difference vegetation index, precipitation, solar radiation, elevation, and latitude are quantified the impacts on LST spatial heterogeneity at annual scale.

Estimation of land surface temperature from three thermal infrared channels of MODIS data for dust aerosol skies.

Studies indicated that a root mean square error (RMSE) of 3.7 K was found if dust aerosol was not considered in the traditional land surface temperature (LST) retrieval algorithm. To reduce the influence of dust aerosol on LST estimation, a three-channel algorithm is proposed using MODIS channels 29, 31, and 32 with model coefficients irrelevant to the aerosol optical depth (AOD).

New method to estimate surface upwelling long-wave radiation from MODIS cloud-free data.

As an important component in the surface radiation budget, surface upwelling longwave radiation (SULR) is an outcome of the land surface energy exchange and mainly represents the capability of thermal radiation from the surface of the Earth. Existing satellite-derived SULR products are too coarse to support high-resolution numerical models, and their accuracy needs to be improved. In this study, an equivalent temperature is introduced through which a "split-window" atmospheric correction algorithm is developed for MODIS data to estimate the instantaneous clear-sky SULR.

Land surface temperature retrieved from airborne multispectral scanner mid-infrared and thermal-infrared data.

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes at local/global scales. In this paper, a LST retrieval method was proposed from airborne multispectral scanner data comparing one mid-infrared (MIR) channel and one thermal infrared (TIR) channel with the land surface emissivity given as a priori knowledge. To remove the influence of the direct solar radiance efficiently, a relationship between the direct solar radiance and water vapor content and the view zenith angle and solar zenith angle was established.

[Research on the Thermal Infrared Polarization Properties of Fresh Snow].

Snow can directly affect the surface energy balance and climate change and has a significant impact on human life and production. It is therefore of great significance to study the fresh snow emission spectroscopy properties by using the thermal infrared Polarization technique. This can provide a basis for quantitative thermal infrared remote sensing monitoring of snow as well as a deeper understanding of global warming and appropriate countermeasures.

Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds.

Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST) retrieval error of 11.0 K when using the generalized split-window (GSW) algorithm with a cirrus optical depth (COD) at 0.55 μm of 0.

Atmospheric corrections of passive microwave data for estimating land surface temperature.

Quantitative analysis of the atmospheric effects on observations made by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) has been performed. The differences between observed brightness temperatures at the top of the atmosphere and at the bottom of the atmosphere were analyzed using a database of simulated observations, which were configured to replicate AMSR-E data. The differences between observed brightness temperatures at the top of the atmosphere and land surface-emitted brightness temperatures were also computed.

Land surface reflectance retrieval from hyperspectral data collected by an unmanned aerial vehicle over the Baotou test site.

To evaluate the in-flight performance of a new hyperspectral sensor onboard an unmanned aerial vehicle (UAV-HYPER), a comprehensive field campaign was conducted over the Baotou test site in China on 3 September 2011. Several portable reference reflectance targets were deployed across the test site. The radiometric performance of the UAV-HYPER sensor was assessed in terms of signal-to-noise ratio (SNR) and the calibration accuracy.

Practical retrieval of land surface emissivity spectra in 8-14 μm from hyperspectral thermal infrared data.

A practical physics-based regression method was developed and evaluated for nearly real time estimate of land surface emissivity spectra in 8-14 μm from hyperspectral thermal infrared data. Two spectral emissivity libraries and one atmospheric profile database fully covering all the possible situations for clear sky conditions were elaborately selected to simulate the radiances at the top of the atmosphere (TOA). The regression coefficients were determined by the main principal components of emissivity spectra and those of simulated brightness temperature at TOA using a ridge regression method.

Validation of MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared channel with field measurements.

This work addressed the validation of the MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared (MIR) channel, proposed by Tang and Li [Int. J. Remote Sens.

Estimation of broadband surface emissivity from narrowband emissivities.

This work analyzed and addressed the estimate of the broadband emissivities for the spectral domains 3-14μm (ε(3-14)) and 3-∞μm (ε(3-∞). Two linear narrow-to-broadband conversion models were proposed to estimate broadband emissivities ε(3-14) and ε(3-∞) using the Moderate Resolution Imaging Spectroradiometer (MODIS) derived emissivities in three thermal infrared channels 29 (8.4-8.

Estimation of land surface directional emissivity in mid-infrared channel around 4.0 microm from MODIS data.

This work addressed the estimate of the directional emissivity in the mid-infrared (MIR) channel around 4.0 microm from MODIS data. A series of bidirectional reflectances in MODIS channel 22 (3.

A review of current methodologies for regional evapotranspiration estimation from remotely sensed data.

An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale.

Impact of Spatial LAI Heterogeneity on Estimate of Directional Gap Fraction from SPOT-Satellite Data.

Directional gap probability or gap fraction is a basic parameter in the optical remote sensing modeling. Although some approaches have been proposed to estimate this gap probability from remotely sensed measurements, few efforts have been made to investigate the scaling effects of this parameter. This paper analyzes the scaling effect through aggregating the high-resolution directional gap probability (pixel size of 20 meters) estimated from leaf area index (LAI) images of VALERI database by means of Beer's law and introduces an extension of clumping index, Ĉ, to compensate the scaling bias.

Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) Data.

On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST) from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C) data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.