Two-Stage Trapezoid: A New Interpretation of the Land Surface Temperature and Fractional Vegetation Coverage Space

2016 ◽  
Vol 9 (1) ◽  
pp. 336-346 ◽  
Author(s):  
Hao Sun
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Coverage ◽  
Two Stage ◽  
New Interpretation ◽  
Coverage Space

scholarly journals Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia

2020 ◽  
Vol 13 (9) ◽  
pp. 3975-3993 ◽  
Author(s):  
Miguel Nogueira ◽  
Clément Albergel ◽  
Souhail Boussetta ◽  
Frederico Johannsen ◽  
Isabel F. Trigo ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Added Value ◽  
Vegetation Coverage ◽  
Daily Maximum ◽  
Cold Bias ◽  
Weather Forecasts ◽  
Surface Models

Abstract. Earth observations were used to evaluate the representation of land surface temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium-Range Weather Forecasts (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modeling platform (SURFEX-ISBA) for the 2004–2015 period. The results showed that the daily maximum LST simulated by CHTESSEL over Iberia was affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 ∘C over wide portions of central and southwestern Iberia. This error was shown to be tightly linked to a misrepresentation of the vegetation cover.  In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) leaf area index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also included a clumping approach that introduces seasonality to the vegetation cover. The results showed significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guiding the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface–atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve the model's representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis; hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we showed that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth-generation reanalysis (ERA5). Finally, our results provided hints about the interaction between vegetation land–atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrated the added value of using multiple earth observation products for constraining and improving weather and climate simulations.

scholarly journals Remote sensing inversion and spatial variation of land surface temperature over mining areas of Jixi, Heilongjiang, China

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10257
Author(s):  
Jia-shuo Cao ◽  
Zheng-yu Deng ◽  
Wen Li ◽  
Yuan-dong Hu
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Coal Mining ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Coverage ◽  
Landsat 8 ◽  
Mining Activities ◽  
Patch Area ◽  
Mining Areas

Background Jixi is a typical mining city in China that has undergone dramatic changes in its land-use pattern of mining areas over the development of its coal resources. The impacts of coal mining activities have greatly affected the regional land surface temperature and ecological system. Methods The Landsat 8 Operational Land Imager (OLI) data from 2015 and 2019 were used from the Jiguan, Didao, and Chengzihe District of Jixi in Heilongjiang, China as the study area. The calculations to determine the land-use classification, vegetation coverage, and land surface temperature (LST) were performed using ArcGIS10.5 and ENVI 5.3 software packages. A correlation analysis revealed the impact of land-use type, vegetation coverage, and coal mining activities on LSTs. Results The results show significant spatial differentiation in the LSTs of Jixi City. The LSTs for various land-use types were ranked from high to low as follows: mining land > construction land > grassland > cultivated land > forest land > water area. The LST was lower in areas with high vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the LST is expected to drop by approximately 0.75 °C. An analysis of mining land patches indicates that the patch area of mining lands has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area, and within 200,000 m2, the average patch temperature increases significantly. The maximum patch temperature shows a linear increase with the patch area growth, and for every 100,000 m2 increase in the patch area of mining lands, the maximum patch temperature increases by approximately 0.81 °C. The higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater its influence scope. This study provides a useful reference for exploring the warming effects caused by coal mining activities and the definition of its influence scope.

On the added value of improving the spatial representation and seasonal variations of vegetation cover in land surface models for simulated land surface temperature

2020 ◽  
Author(s):  
Miguel Nogueira ◽  
Clément Albergel ◽  
Souhail Boussetta ◽  
Frederico Johanssen ◽  
Emanuel Dutra
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Added Value ◽  
Vegetation Coverage ◽  
Daily Maximum ◽  
Cold Bias ◽  
Earth Observations ◽  
Surface Models

<p>Earth observations were used to evaluate and improve the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models - the European Center for Medium Range Weather Forecasting (ECMWF) Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL) and the Méteo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modelling platform (SURFEX-ISBA) for the 2004-2015 period.</p><p>The results show that the daily maximum LST simulated by HTESSEL over Iberia is affected by a large cold bias during summer months when compared against the Satellite Application Facility Land Surface Analysis (LSA-SAF), reaching magnitude larger than 10ºC over wide portions of central and southwestern Iberia. This error is shown to be tightly linked to a misrepresentation of the vegetation cover.  In contrast, SURFEX simulations did not had such a cold bias. This was due to the better representation of vegetation coverage in SURFEX, which uses an updated land cover dataset (ECOCLIMAP II) and an interactive vegetation evolution, representing seasonality.</p><p>The representation of vegetation over Iberia in HTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) Leaf Area Index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement vegetation includes a clumping approach to introduce seasonality to the vegetation coverage. The results show significant added value, removing the daily maximum LST summer cold bias completely while never reducing the accuracy over all seasons and hours of the day.</p><p>This work has important implications: First, LST is a key variable in surface-atmosphere energy and water exchanges and, thus, its accurate representation in earth system models is very important. Second, HTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis, hence systematic errors are propagated into these products. Indeed, we show that the summer daily maximum LST cold bias over Iberia in HTESSEL is present in the widely used ECMWF fifth generation reanalysis (ERA5) and fourth generation reanalysis (ERA-Interim).  Finally, our results provide hints into the interaction between vegetation land-atmosphere exchanges, highlight the consistent relevance of the vegetation cover and seasonality in representing land surface temperature in both models, and how earth observations play a critical role for constraining and improving weather and climate simulations.</p>

scholarly journals Wind Speed-Independent Two-Source Energy Balance Model Based on a Theoretical Trapezoidal Relationship between Land Surface Temperature and Fractional Vegetation Cover for Evapotranspiration Estimation

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Xiao-Gang Wang ◽  
Qing Kang ◽  
Xiao-Hong Chen ◽  
Wen Wang ◽  
Qing-Hua Fu
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Wind Speed ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vertical Direction ◽  
Accurate Estimation ◽  
Two Stage ◽  
Mean Square Errors

An accurate estimation of terrestrial evapotranspiration over heterogeneous surfaces using satellite imagery and few meteorological observations remains a challenging task. Wind speed (u), which is known to exhibit high temporal-spatial variation, is a significant constraint in the abovementioned task. In this study, a wind speed-independent two-source energy balance (WiTSEB) model is proposed on the basis of a theoretical land surface temperature (Tr)-fractional vegetation coverage (fc) trapezoidal space and a two-stage evapotranspiration decomposing method. The temperatures in theoretically driest boundaries of the Tr-fc trapezoid are iteratively calculated without u by using an assumption of the absence of sensible heat exchange between water-saturated surface and atmosphere in the vertical direction under the given atmospheric condition. The WiTSEB was conducted in HiWATER-MUSOEXE-12 in the middle reaches of the Heihe watershed across eight landscapes by using ASTER images. Results indicate that WiTSEB provides reliable estimates in latent heat flux (LE), with root-mean-square-errors (RMSE) and coefficient of determination of 68.6 W m−2 and 0.88, respectively. The RMSE of the ratio of the vegetation transpiration component to LE is 5.7%. Sensitivity analysis indicates WiTSEB does not aggravate the sensitivity on meteorological and remote sensing inputs in comparison with other two-source models. The errors of estimated Tr and observed soil heat flux result in LE overestimation/underestimation over parts of landscapes. The two-stage evapotranspiration decomposing method is carefully verified by ground observation.

scholarly journals EFFECT OF EARTH COVERING AND WATER BODY ON LAND SURFACE TEMPERATURE (LST)

2020 ◽  
Vol 11 (1) ◽  
pp. 45-56
Author(s):  
Md. Jahir Uddin ◽  
Chandan Mondal
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Water Body ◽  
Land Surface ◽  
Drainage Basin ◽  
Vegetation Coverage ◽  
Important Place ◽  
Barren Area ◽  
The Impact ◽  
Surface Covering

Land surface covering and water body play an important role on local environment especially on Land Surface Temperature (LST). In study above mentioned concept has been conducted on the drainage basin of Atai-Bhairab-Rupsha river confluence which is an important place both for agriculture and trade in the south-western part of Bangladesh. Here the impact of both surface covering and water body on local environmental factor like LST is being analyzed to determine the main catalyst in ever changing LST. LST study in this area which is changed dramatically recently may be a well-defined index, reflects environmental conditions. LST is mainly altered by the factors like land surface covering such as vegetation represented by NDVI, water body by NDWI, and barren or urban area by NDBI but only few are key factors. The gradual changes of these four parameters (LST, NDVI, NDWI, and NDBI) are studied for the years 1991, 1996, 2002, 2006, 2011 and 2017. From the LST study, it is observed that from 1991 to 2017 highest temperature decreased significantly and the difference between 1991 and 2017 is greater than 100C. Variation of lowest temperature all these years are insignificant. Meanwhile, from NDVI analysis if is observed that area of vegetation coverage increased in a significant rate from the years 1991 to 2017. The area of water body is being found almost unchanged in this time period from the NDWI analysis. Nevertheless, from the NDBI analysis it is found that the barren area is diminished significantly in this period and is obviously replaced by vegetation. At all, it can be said that the highest value of NDVI in 1991 is greater than 2017 denotes some short of drought or increasing salinity condition but in general viewpoint vegetation helps to keep surface temperature under control.

scholarly journals Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia

2020 ◽  
Author(s):  
Miguel Nogueira ◽  
Clément Albergel ◽  
Souhail Boussetta ◽  
Frederico Johannsen ◽  
Isabel F Trigo ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Added Value ◽  
Vegetation Coverage ◽  
Daily Maximum ◽  
Cold Bias ◽  
Land Surface Models ◽  
Surface Models

Abstract. Earth observations were used to evaluate the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium Range Weather Forecasting (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modelling platform (SURFEX-ISBA) for the 2004–2015 period. The results show that the daily maximum LST simulated by CHTESSEL over Iberia is affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 °C over wide portions of central and southwestern Iberia. This error is shown to be tightly linked to a misrepresentation of the vegetation cover. In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) Leaf Area Index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also includes a clumping approach that introduces seasonality to the vegetation cover. The results show significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guide the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface-atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve model’s representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis, hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we show that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth generation reanalysis (ERA5). Finally, our results provide hints into the interaction between vegetation land-atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrates the added value in using multiple earth observation products for constraining and improving weather and climate simulations.

scholarly journals Analyzing the Changes in Land Cover and Land Surface Temperature (LST) in the North Bandung Area (NBA)

2021 ◽  
Vol 3 (2) ◽  
pp. 51-59
Author(s):  
Dian Rosleine ◽  
Muhammad Irfan
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water System ◽  
Vegetation Coverage ◽  
Forest Conversion ◽  
West Java ◽  
The North ◽  
Reforestation Program

North Bandung Area (NBA) was designated as a protected area to regulate the water system around Bandung City. Land conversion from vegetated land into built-up areas can decrease groundwater, increase the risk of floods, landslides, and Land Surface Temperature (LST). This study was conducted to describe LST distribution based on land cover types in specific years of 2010, 2014, and 2018. Landsat 5 and 8 Surface Reflectance (SR) Tier 1 imagery data, West Java land cover maps established by BAPPEDA West Java, and RBI administration maps at a scale of 1: 25,000 were used to generate a map of land cover and LST in this research. There are four land cover classes in NBA, i.e., vegetation, water bodies, open areas, and constructed areas. Within eight years observation (2010 to 2018), bare land decreased from 67.6% (2010) to 57.5% (2018). However, coverage of constructed areas increased within eight years of observation from 22.8% to 27.7 %. In addition, due to the reforestation program, vegetation coverage has slightly increased from 9.6% to 14.7%. LST can be classified into three classes, i.e., low, medium, and high temperature. The area with low and medium-class temperatures decreased from 19% to 16% and 61.3% to 51.7%, respectively. However, high LST increased in NBA 18.7% to 30.3%. The enhancement of 5% vegetation area did not significantly reduce land surface temperature in NBA due to forest conversion to constructed area. Therefore, vegetation coverage must be escalated by reforestation program around NBA to reduce land surface temperature.

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