scholarly journals Retrieving Crop Albedo Based on Radar Sentinel-1 and Random Forest Approach

2021 ◽  
Vol 13 (16) ◽  
pp. 3181
Author(s):  
Abdelhakim Amazirh ◽  
El Houssaine Bouras ◽  
Luis Enrique Olivera-Guerra ◽  
Salah Er-Raki ◽  
Abdelghani Chehbouni

Monitoring agricultural crops is of paramount importance for preserving water resources and increasing water efficiency over semi-arid areas. This can be achieved by modelling the water resources all along the growing season through the coupled water–surface energy balance. Surface albedo is a key land surface variable to constrain the surface radiation budget and hence the coupled water–surface energy balance. In order to capture the hydric status changes over the growing season, optical remote sensing becomes impractical due to cloud cover in some periods, especially over irrigated winter crops in semi-arid regions. To fill the gap, this paper aims to generate cloudless surface albedo product from Sentinel-1 data that offers a source of high spatio-temporal resolution images. This can help to better capture the vegetation development along the growth season through the surface radiation budget. Random Forest (RF) algorithm was implemented using Sentinel-1 backscatters as input. The approach was tested over an irrigated semi-arid zone in Morocco, which is known by its heterogeneity in term of soil conditions and crop types. The obtained results are evaluated against Landsat-derived albedo with quasi-concurrent Landsat/Sentinel-1 overpasses (up to one day offset), while a further validation was investigated using in situ field scale albedo data. The best model-hyperparameters selection was dependent on two validation approaches (K-fold cross-validation ‘k = 10’, and holdout). The more robust and accurate model parameters are those that represent the best statistical metrics (root mean square error ‘RMSE’, bias and correlation coefficient ‘R’). Coefficient values ranging from 0.70 to 0.79 and a RMSE value between 0.0002 and 0.00048 were obtained comparing Landsat and predicted albedo by RF method. The relative error ratio equals 4.5, which is acceptable to predict surface albedo.

2013 ◽  
Vol 62 (20) ◽  
pp. 209201
Author(s):  
Yue Ping ◽  
Zhang Qiang ◽  
Zhao Wen ◽  
Wang Jin-Song ◽  
Wang Run-Yuan ◽  
...  

2017 ◽  
Vol 17 (9) ◽  
pp. 5809-5828 ◽  
Author(s):  
Karl-Göran Karlsson ◽  
Kati Anttila ◽  
Jörg Trentmann ◽  
Martin Stengel ◽  
Jan Fokke Meirink ◽  
...  

Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided.


2008 ◽  
Vol 21 (18) ◽  
pp. 4723-4748 ◽  
Author(s):  
A. Bodas-Salcedo ◽  
M. A. Ringer ◽  
A. Jones

Abstract The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN). Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2. Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out. Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.


2018 ◽  
Vol 6 (2) ◽  
pp. 64
Author(s):  
Zakaria Marouf BARKA ◽  
Théophile Lealea ◽  
Rene Tchinda

Surface albedo is one parameter of the climate variables. It influences the surface radiation budget for a given site. The availability of surface albedo data at both temporally and spatially levels are needed. In the lack of ground recorded values of albedo, we have to estimate surface albedo from the climatic variables. The model generated in this study enables the continuous observation of land surface albedo through relative model established from the multivariate regression method. From satellite recorded data, we estimate the ground surface albedo for some selected sites. The result were satisfactory with the root mean square error (RMSE) is 0.035. The Mean Absolute Error (MAE) was computed and indicated to be as low as 0.027 and mean absolute percentage error (MAPE) is 7.58.  


2021 ◽  
Vol 13 (23) ◽  
pp. 4869
Author(s):  
Congying Shao ◽  
Yanmin Shuai ◽  
Latipa Tuerhanjiang ◽  
Xuexi Ma ◽  
Weijie Hu ◽  
...  

Surface albedo, as an important parameter for land surface geo-biophysical and geo-biochemical processes, has been widely used in the research communities involved in surface energy balance, weather forecasting, atmospheric circulation, and land surface process models. In recent years, operational products using satellite-based surface albedo have, from time to time, been rapidly developed, contributing significantly to the estimation of energy balance at regional or global scales. The increasing number of research topics on dynamic monitoring at a decades-long scale requires a combination of albedo products generated from various sensors or programs, while the quantitative assessment of agreement or divergence among different surface albedo products still needs further understanding. In this paper, we investigated the consistency of three classical operational surface albedo products that have been frequently used by researchers globally via the official issued datasets-MODIS, GLASS (Global LAnd Surface Satellite), and CGLS (Copernicus Global Land Service). The cross-comparison was performed on all the identical dates available during 2000–2017 to represent four season-phases. We investigated the pixel-based validity of each product, consistency of global annual mean, spatial distribution and different temporal dynamics among the discussed products in white-sky (WSA) and black-sky (BSA) albedo at visible (VIS), near-infrared (NIR), and shortwave (SW) regimes. Further, varying features along with the change of seasons was also examined. In addition, the variation in accuracy of shortwave albedo magnitude was explored using ground measurements collected by the Baseline Surface Radiation Network (BSRN) and the Surface Radiation Budget Network (SUFRAD). Results show that: (1) All three products can provide valid long-term albedo for dominant land surface, while GLASS can provide additional estimation over sea surfaces, with the highest percentage of valid land surface pixels, at up to 93% in October 24. The invalid pixels mainly existed in the 50°N–60°N latitude belt in December for GLASS, Central Africa in April and August for MODIS, and northern high latitudes for CGLS. (2) The global mean albedo of CGLS at the investigated bands has significantly higher values than those of MODIS and GLASS, with a relative difference of ~20% among the three products. The global mean albedo of MODIS and GLASS show a generally increasing trend from April to December, with an abrupt rise at NIR and SW of CGLS in June of 2014. Compared with SW and VIS bands, the linear temporal trend of the NIR global albedo mean in three products continues to increase, but the slope of CGLS is 10–100 times greater than that of the other two products. (3) The differences in albedo, which are higher in April, October, and December than in August, exhibit a small variation over the main global land surface regions, except for Central Eurasia, North Africa, and middle North America. The magnitude of global absolute difference among the three products usually varies within 0.02–0.06, but with the largest value occasionally exceeding 0.1. The relative difference is mainly within 10%–20%, and can deviate more than 40% away from the baseline. In addition, CGLS has a greater opportunity to achieve the largest difference compared with MODIS and GLASS. (4) The comparison with ground measurements indicates that MODIS generally performs better than GLASS and CGLS at the sites discussed. This study demonstrates that apparent differences exist among the three investigated albedo products due to the ingested source data, algorithm, atmosphere correction etc., and also points at caution regarding data fusion when multiple albedo products were organized to serve the following applications.


2016 ◽  
Author(s):  
Karl-Göran Karlsson ◽  
Kati Anttila ◽  
Jörg Trentmann ◽  
Martin Stengel ◽  
Jan Fokke Meirink ◽  
...  

Abstract. The second edition of the satellite-derived climate data record CLARA ("The CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data" – second edition denoted CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail as well as some major validation results. Some of the main improvements of the data record come from a major effort in cleaning and homogenising the basic AVHRR level 1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Polar Summer surface albedo and cloud conditions, as well as global cloud redistribution patterns, are provided.


2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chunlei Meng

Surface albedo is a crucial parameter in land surface radiation budget. As bias exists between the model simulated and observed surface albedo, data assimilation is an important method to improve the simulation results. Moreover, surface albedo is associated with the wavelength of the sunlight. So, solar radiation partitioning is important to parameterize the surface albedo. In this paper, the moderate resolution imaging spectroradiometer- (MODIS-) retrieved direct visible, direct near-infrared, diffuse visible, and diffuse near-infrared surface albedos were assimilated into the integrated urban land model (IUM). The solar radiation partitioning method was introduced to parameterize the surface albedo. Based on the albedo data from MODIS and the solar radiation partitioning method, the surface albedo data set for the Beijing municipal area was generated. Based on the surface albedo data set and the IUM, the impacts of the surface albedo on the surface radiation budget were discussed quantitatively. Surface albedo is inversely proportional to the net radiation. For urban areas, after assimilation, the annual average net radiation decreases about 5.6%. For cropland, grassland, and forest areas, after assimilation, the annual average net radiations increase about 20.2%, 24.3%, and 18.7%, respectively.


Urban Climate ◽  
2021 ◽  
Vol 39 ◽  
pp. 100940
Author(s):  
Chunlei Meng ◽  
Chengcheng Huang ◽  
Junxia Dou ◽  
Huoqing Li ◽  
Conglan Cheng

2018 ◽  
Vol 12 (6) ◽  
pp. 2159-2165 ◽  
Author(s):  
Donald K. Perovich

Abstract. The surface radiation budget of the Arctic Ocean plays a central role in summer ice melt and is governed by clouds and surface albedo. I calculated the net radiation flux for a range of albedos under sunny and cloudy skies and determined the break-even value, where the net radiation is the same for cloudy and sunny skies. Break-even albedos range from 0.30 in September to 0.58 in July. For snow-covered or bare ice, sunny skies always result in less radiative heat input. In contrast, leads always have, and ponds usually have, more radiative input under sunny skies than cloudy skies. Snow-covered ice has a net radiation flux that is negative or near zero under sunny skies, resulting in radiative cooling. Areally averaged albedos for sea ice in July result in a smaller net radiation flux under cloudy skies. For May, June, August, and September, the net radiation is smaller under sunny skies.


2020 ◽  
Vol 37 (4) ◽  
pp. 553-571
Author(s):  
Peiyang Cheng ◽  
Arastoo Pour-Biazar ◽  
Richard T. McNider ◽  
John R. Mecikalski

AbstractIncident solar radiation at Earth’s surface, also called surface insolation, plays an important role in the Earth system as it affects surface energy balance, weather, climate, water supply, biochemical emissions, photochemical reactions, etc. The University of Alabama in Huntsville (UAH) and the NASA Short-term Prediction Research and Transition Center (SPoRT) have been generating and archiving several products, including insolation, from the Geostationary Operational Environmental Satellite (GOES) Imager for over a decade. The NASA/UAH insolation product has been used in studies to improve air quality simulations, biogenic emission estimates, correcting surface energy balance, and for cloud assimilation, but has not been thoroughly evaluated. In this study, the NASA/UAH insolation product is compared to surface pyranometer measurements from the Surface Radiation Budget Network (SURFRAD) and the U.S. Climate Reference Network (USCRN) for a 12-month period from March 2013 to February 2014. The insolation product has normalized bias values within 6% of the mean observation, a root-mean-square error between 6% and 16%, and correlation coefficients greater than 0.96 for hourly insolation estimates. It also shows better performance without the presence of clouds. However, erroneous estimates may be produced for persistent snow-covered surfaces. Further, this study attempts to demonstrate the use of such a satellite-based insolation product for model evaluation. The NASA/UAH insolation product is compared to the downward shortwave radiation from the Rapid Refresh, version 1 (RAPv1), and successfully captures the overestimation tendency in surface energy input as mentioned in previous studies. Finally, future plans for improving the retrieval algorithm and developing a GOES-16 insolation product are discussed.


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