Analysis of temporal and spatial characteristics about surface actual Evapotranspiration in Haihe river basin based on MODIS

Wu, Xinling; Meng, Dan

doi:10.1109/eorsa.2016.7552850

Cited by 2 publications

(2 citation statements)

References 1 publication

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“…We attributed the reasons for uncertainty in the validation process to different factors, such as the difference in geographical location and time period covered for each site. Some studies showed that that different elevations led to different LE values in the HRB [52]. The HL site is located at the junction of mountains and plains where the elevation is higher than at the other sites, which may explain the poor accuracy of the HL site in the crossvalidation process.…”

Section: Performance Of the Gbrtmentioning

confidence: 99%

GBRT-Based Estimation of Terrestrial Latent Heat Flux in the Haihe River Basin from Satellite and Reanalysis Datasets

et al. 2021

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An accurate and spatially continuous estimation of terrestrial latent heat flux (LE) is fundamental and crucial for the rational utilization of water resources in the Haihe River Basin (HRB). However, the sparsity of flux observation sites hinders the accurate characterization of spatiotemporal LE patterns over the HRB. In this study, we estimated the daily LE across the HRB using the gradient boosting regression tree (GBRT) from global land surface satellite NDVI data, reanalysis data and eddy covariance data. Compared with the random forests (RF) and extra tree regressor (ETR) methods, the GBRT obtains the best results, with R2 = 0.86 and root mean square error (RMSE = 18.1 W/m2. Then, we applied the GBRT algorithm to map the average annual terrestrial LE of the HRB from 2016 to 2018 with a spatial resolution of 0.05°. When compared with the Global Land Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) LE products, the difference between the terrestrial LE estimated by the GBRT algorithm and the GLASS and MODIS products was less than 20 W/m2 in most areas; thus, the GBRT algorithm was reliable and reasonable for estimating the long-term LE estimation over the HRB.

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Section: Performance Of the Gbrtmentioning

confidence: 99%

GBRT-Based Estimation of Terrestrial Latent Heat Flux in the Haihe River Basin from Satellite and Reanalysis Datasets

et al. 2021

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“…When K > 0, the evolution trend of SFR increases in the 33-year period; otherwise, this trend decreases. No uniform standard exists for the division of K-value trends [54,55]. According to the overall distribution of the SFR in the study area and the calculation of the changes in the K-value, the K-value conforms to a normal distribution [56].…”

Section: Least Squares Trend Analysismentioning

confidence: 99%

Change Detection of Soil Formation Rate in Space and Time Based on Multi Source Data and Geospatial Analysis Techniques

et al. 2020

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Spatialization of soil formation rate (SFR) is always a difficult problem in soil genesis. In this study, the dissolution rate in karst areas of China during the period 1983–2015 was estimated on the basis of geospatial analysis techniques and detection of variation via the law of chemical thermodynamics in conjunction with long-term serial ecohydrology data. SFR at different lithological backgrounds was calculated on the basis of the content of acid-insoluble substances. Results showed that the spatial dissolution rate of carbonate rock ranges between 0 and 106 mm/ka, averaged at 22.51 mm/ka, and the SFR ranges between 10 and 134.93 t km−2 yr−1, averaged at 18.59 t km−2 yr−1. The dissolution rate and SFR exhibit a slight increasing trend with 0.04 mm/ka and 0.003 t km−2 yr−1, respectively. The risk for soil erosion was reevaluated on the basis of the SFR results, and the area with erosion risk and the ecologically safe area were corrected. Results indicated that the area with erosion risk is four times higher than the ecologically safe area. This study will hopefully instigate and facilitate the application and popularization of geospatial analysis technology to the research field of rock weathering and soil formation.

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Analysis of temporal and spatial characteristics about surface actual Evapotranspiration in Haihe river basin based on MODIS

Cited by 2 publications

References 1 publication

GBRT-Based Estimation of Terrestrial Latent Heat Flux in the Haihe River Basin from Satellite and Reanalysis Datasets

GBRT-Based Estimation of Terrestrial Latent Heat Flux in the Haihe River Basin from Satellite and Reanalysis Datasets

Change Detection of Soil Formation Rate in Space and Time Based on Multi Source Data and Geospatial Analysis Techniques

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