Validation of six satellite-retrieved land surface emissivity products over two land cover types in a hyper-arid region

2012 ◽  
Vol 124 ◽  
pp. 149-158 ◽  
Author(s):  
Frank-M. Göttsche ◽  
Glynn C. Hulley
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Arid Region ◽  
Surface Emissivity ◽  
Land Cover Types ◽  
Land Surface Emissivity

scholarly journals Diurnal Cycle of Passive Microwave Brightness Temperatures over Land at a Global Scale

2021 ◽  
Vol 13 (4) ◽  
pp. 817
Author(s):  
Zahra Sharifnezhad ◽  
Hamid Norouzi ◽  
Satya Prakash ◽  
Reginald Blake ◽  
Reza Khanbilvardi
Keyword(s):  
Land Cover ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Global Scale ◽  
Passive Microwave ◽  
Surface Emissivity ◽  
Land Cover Types ◽  
Land Surface Emissivity ◽  
Microwave Imager ◽  
Microwave Sensors

Satellite-borne passive microwave radiometers provide brightness temperature (TB) measurements in a large spectral range which includes a number of frequency channels and generally two polarizations: horizontal and vertical. These TBs are widely used to retrieve several atmospheric and surface variables and parameters such as precipitation, soil moisture, water vapor, air temperature profile, and land surface emissivity. Since TBs are measured at different microwave frequencies with various instruments and at various incidence angles, spatial resolutions, and radiometric characteristics, a mere direct integration of them from different microwave sensors would not necessarily provide consistency. However, when appropriately harmonized, they can provide a complete dataset to estimate the diurnal cycle. This study first constructs the diurnal cycle of land TBs using the non-sun-synchronous Global Precipitation Measurement (GPM) Microwave Imager (GMI) observations by utilizing a cubic spline fit. The acquisition times of GMI vary from day to day and, therefore, the shape (amplitude and phase) of the diurnal cycle for each month is obtained by merging several days of measurements. This diurnal pattern is used as a point of reference when intercalibrated TBs from other passive microwave sensors with daily fixed acquisition times (e.g., Special Sensor Microwave Imager/Sounder, and Advanced Microwave Scanning Radiometer 2) are used to modify and tune the monthly diurnal cycle to daily diurnal cycle at a global scale. Since the GMI does not cover polar regions, the proposed method estimates a consistent diurnal cycle of land TBs at global scale. Results show that the shape and peak of the constructed TB diurnal cycle is approximately similar to the diurnal cycle of land surface temperature. The diurnal brightness temperature range for different land cover types has also been explored using the derived diurnal cycle of TBs. In general, a large diurnal TB range of more than 15 K has been observed for the grassland, shrubland, and tundra land cover types, whereas it is less than 5K over forests. Furthermore, seasonal variations in the diurnal TB range for different land cover types show a more consistent result over the Southern Hemisphere than over the Northern Hemisphere. The calibrated TB diurnal cycle may then be used to consistently estimate the diurnal cycle of land surface emissivity. Moreover, since changes in land surface emissivity are related to moisture change and freeze–thaw (FT) transitions in high-latitude regions, the results of this study enhance temporal detection of FT state, particularly during the transition times when multiple FT changes may occur within a day.

scholarly journals Assessment of the consistency among global microwave land surface emissivity products

2015 ◽  
Vol 8 (3) ◽  
pp. 1197-1205 ◽  
Author(s):  
H. Norouzi ◽  
M. Temimi ◽  
C. Prigent ◽  
J. Turk ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Surface Emissivity ◽  
Similar Frequency ◽  
Land Surface Emissivity ◽  
Microwave Imager

Abstract. The goal of this work is to intercompare four global land surface emissivity products over various land-cover conditions to assess their consistency. The intercompared land emissivity products were generated over a 5-year period (2003–2007) using observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and WindSat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity products were also compared to soil moisture estimates and a satellite-based vegetation index to assess their sensitivities to changes in land surface conditions. Results show the existence of systematic differences among the products. Also, it was noticed that emissivity values in each product have similar frequency dependency over different land-cover types. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower than the rest of the products across various land-cover conditions which may be attributed to the 01:30/13:30 LT overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analyzed products was lowest (less than 0.01) in rain forest regions for all products and highest at northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute emissivity estimates, all products were similarly sensitive to changes in soil moisture and vegetation. The correlation between the emissivity polarization differences and normalized difference vegetation index (NDVI) values showed similar spatial distribution across the products, with values close to the unit except over densely vegetated and desert areas.

scholarly journals Assessment of the consistency among global microwave land surface emissivity products

2014 ◽  
Vol 7 (9) ◽  
pp. 9993-10013 ◽  
Author(s):  
H. Norouzi ◽  
M. Temimi ◽  
C. Prigent ◽  
J. Turk ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Land Cover ◽  
Land Surface ◽  
Weather Prediction ◽  
Surface Boundary ◽  
Surface Emissivity ◽  
Similar Frequency ◽  
Land Surface Emissivity ◽  
Microwave Imager

Abstract. The goal of this work is to inter-compare a number of global land surface emissivity products over various land-cover conditions to assess their consistency. Ultimately, the discrepancies between the studied emissivity products will help interpreting the divergences among numerical weather prediction models in which land emissivity is a key surface boundary parameter. The intercompared retrieved land emissivity products were generated over five-year period (2003–2007) using observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E), Special Sensor Microwave Imager (SSM/I), The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Windsat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity values from four products were also compared to soil moisture estimates and satellite-based vegetation index to assess their sensitivities to the changes in land surface conditions. Results show that systematic differences among products exist and variation of emissivities at each product has similar frequency dependency at any land cover type. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower across various land cover condition which may be attributed to the 1.30 a.m./p.m. overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analysed products was the lowest (less than 0.01) in rain forest regions for all products and the highest in northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute emissivity estimates, all products were similarly sensitive to changes in soil moisture and vegetation. The correlation between the emissivity polarization differences and NDVI values showed similar spatial distribution across the products with values close to the unit except over densely vegetated and desert areas.

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

scholarly journals Study of Aerosol Influence on Nighttime Land Surface Temperature Retrieval Based on Two Methods

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Caixia Gao ◽  
Enyu Zhao ◽  
Chuanrong Li ◽  
Yonggang Qian ◽  
Lingling Ma ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Water Vapor ◽  
Standard Deviation ◽  
Land Surface ◽  
Simulated Data ◽  
Mean Square ◽  
Surface Emissivity ◽  
Land Surface Emissivity ◽  
Instrument Noise ◽  
Temperature Retrieval

The aim of this study is to evaluate the aerosol influence on LST retrieval with two algorithms (split-window (SW) method and a four-channel based method) using simulated data under typical conditions. The results show that the root mean square error (RMSE) decreases to approximately 2.3 K for SW method and 1.5 K for four channel based method when VZA = 60° and visibility = 3 km; an RMSE would be increased by approximately 1.0 K when visibility varies from 3 km to 23 km. Moreover, a detailed sensitivity analysis under a visibility of 3 km and 23 km is performed in terms of uncertainties of land surface emissivity (LSE), water vapor content (WVC), and instrument noise, respectively. It is noted that the four-channel based method is more sensitive to LSE than SW method, especially for dry atmosphere; LST error caused by a WVC uncertainty of 20% is within 1.5 K for SW method and within 0.8 K for four-channel based method; the instrument noise would introduce LST error with a maximum standard deviation of 0.5 K and 0.04 K for the four-channel based method and SW method, respectively.

Dependence of Simulation Biases at AHI Surface-Sensitive Channels on Land Surface Emissivity over China

2018 ◽  
Vol 35 (6) ◽  
pp. 1283-1298 ◽  
Author(s):  
X. Zhuge ◽  
X. Zou ◽  
F. Weng ◽  
M. Sun
Keyword(s):  
Brightness Temperature ◽  
Spectral Resolution ◽  
Land Surface ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Emissivity ◽  
Bare Rock ◽  
Land Surface Emissivity ◽  
M Channels

AbstractThis study compares the simulation biases of Advanced Himawari Imager (AHI) brightness temperature to observations made at night over China through the use of three land surface emissivity (LSE) datasets. The University of Wisconsin–Madison High Spectral Resolution Emissivity dataset, the Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer and Moderate Resolution Imaging Spectroradiometer Emissivity database over Land High Spectral Resolution Emissivity dataset, and the International Geosphere–Biosphere Programme (IGBP) infrared LSE module, as well as land skin temperature observations from the National Basic Meteorological Observing stations in China are used as inputs to the Community Radiative Transfer Model. The results suggest that the standard deviations of AHI observations minus background simulations (OMBs) are largely consistent for the three LSE datasets. Also, negative biases of the OMBs of brightness temperature uniformly occur for each of the three datasets. There are no significant differences in OMB biases estimated with the three LSE datasets over cropland and forest surface types for all five AHI surface-sensitive channels. Over the grassland surface type, significant differences (~0.8 K) are found at the 10.4-, 11.2-, and 12.4-μm channels if using the IGBP dataset. Over nonvegetated surface types (e.g., sandy land, gobi, and bare rock), the lack of a monthly variation in IGBP LSE introduces large negative biases for the 3.9- and 8.6-μm channels, which are greater than those from the two other LSE datasets. Thus, improvements in simulating AHI infrared surface-sensitive channels can be made when using spatially and temporally varying LSE estimates.

scholarly journals An objective methodology for infrared land surface emissivity evaluation

2010 ◽  
Vol 115 (D22) ◽  
Author(s):  
Zhenglong Li ◽  
Jun Li ◽  
Xin Jin ◽  
Timothy J. Schmit ◽  
Eva E. Borbas ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Emissivity ◽  
Land Surface Emissivity ◽  
Objective Methodology
Sign in / Sign up

Export Citation Format

Share Document