Daily Soil Moisture Retrieval by Fusing CYGNSS and Multi-Source Auxiliary Data Using Machine Learning Methods
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The Cyclone Global Navigation Satellite System (CYGNSS), a publicly accessible spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) data, provides a new alternative opportunity for large-scale soil moisture (SM) retrieval, but with interference from complex environmental conditions (i.e., vegetation cover and ground roughness). This study aims to develop a high-accuracy model for CYGNSS SM retrieval. The normalized surface reflectivity calculated by CYGNSS is fused with variables that are highly related to the SM obtained from optical/microwave remote sensing to solve the problem of the influence of complicated environmental conditions. The Gradient Boost Regression Tree (GBRT) model aided by land-type data is then used to construct a multi-variables SM retrieval model with six different land types of multiple models. The methodology is tested in southeastern China, and the results correlate very well with the existing satellite remote sensing products and in situ SM data (R = 0.765, ubRMSE = 0.054 m3m−3 vs. SMAP; R = 0.653, ubRMSE = 0.057 m3 m−3 vs. ERA5 SM; R = 0.691, ubRMSE = 0.057 m3m−3 vs. in situ SM). This study makes contributions from two aspects: (1) improves the accuracy of the CYGNSS retrieval of SM based on fusion with other auxiliary data; (2) constructs the SM retrieval model with multi-layer multiple models, which is suitable for different land properties.Keywords:
Land Cover
This chapter discusses the contribution of field spectroradiometry and hyperspectral remote sensing in extracting information related to land cover mapping. It provides an overview on the use of field spectroradiometry in examining the spectral discrimination between different land cover targets. An overview on the main statistical approaches employed in spectral separation of different land cover targets is provided. The chapter focuses on the use of hyperspectral remote sensing imagery from airborne or satellite platforms for obtaining regional estimates of land use/cover. An overview of the different techniques employed in mapping land cover types from such data is presented with examples from case studies. The chapter also discusses the importance of observation scale in land cover extraction using remote sensing data. Finally, it highlights the challenges toward a more precise estimation of land use/cover from field spectroradiometry and hyperspectral remote sensing with respect to spectral information acquired at different spatial scales.
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Cameras on remote sensing satellites must be calibrated in a timely manner to ensure the quality of the images. This calibration process is done before launch and during on-orbit operation. There are several types of on-orbit calibration, some of them require a calibration area that has to be based on several characteristics. This research was conducted to analyze the feasibility of calibration sites in three areas in Indonesia. Those areas are Jaddih Hill, Kupang Cement Mine, and Bromo Tengger Semeru National Park. An objective method to determine the calibration areas was by observing the image's area from the multispectral camera of the LAPAN-A3 satellite (LISA), the multispectral camera of the LANDSAT-8 satellite (OLI), and Google Earth. Furthermore, it was conducted measuring reflectance and analyzing the uniformity of the area by Coefficient of Variation (CV) calculation. The results show that the Jaddih Hill and Kupang Cement Mine according to the requirements as a calibration area at a range of wavelength from 400–900 nm. Meanwhile, Bromo Tengger Semeru National Park is not recommended on those wavelenght.
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This paper summarizes the characteristics of China's civil satellite payloads and the research status of radiometric calibration,and ascertains the calibration method flow that suits China's civil satellite payloads.We perform the calibration and validation of civil satellite by using above mentioned methods.The retrieval algorithm of land surface property parameters,such as reflectance and temperature,are researched based on the civil satellite remote sensing data.At last,a application demonstration of land surface products is performed.The result shows that the method stipulated in the paper is appropriate to in-orbit calibration and validation of satellite payloads,and the calibration coefficients are accurate for quantitative application,the demonstration result based on our country remote sensing data is very well.
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Abstract. This paper reviews the development of in-orbit radiometric calibration methods in the past 40 years. It summarizes the development of in-orbit radiometric calibration technology of typical satellite sensors in the visible/near-infrared bands and the thermal infrared band. Focuses on the visible/near-infrared bands radiometric calibration method including: Lamp calibration and solar radiationbased calibration. Summarizes the calibration technology of Landsat series satellite sensors including MSS, TM, ETM+, OLI, TIRS; SPOT series satellite sensors including HRV, HRS. In addition to the above sensors, there are also summarizing ALI which was equipped on EO-1, IRMSS which was equipped on CBERS series satellite. Comparing the in-orbit radiometric calibration technology of different periods but the same type satellite sensors analyzes the similarities and differences of calibration technology. Meanwhile summarizes the in-orbit radiometric calibration technology in the same periods but different country satellite sensors advantages and disadvantages of calibration technology.
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