First Assessment of Cloud‐Land Coupling in LASSO Large‐Eddy Simulations DOI Creative Commons
Haipeng Zhang, Tianning Su, Youtong Zheng

и другие.

Geophysical Research Letters, Год журнала: 2024, Номер 51(14)

Опубликована: Июль 26, 2024

Abstract To enhance our understanding of cloud simulations over land, this study provides the first assessment coupling between and land surface in Large‐Eddy Simulation (LES) Atmospheric Radiation Measurement Symbiotic Observation (LASSO) activity for shallow convection scenario. The analysis observation data reveals a diurnal cycle cloud‐land coupling, which co‐varies with fluxes. However, coupled (or decoupled) cumulus clouds are inadequately simulated, manifesting as too‐high low) occurrence frequency during afternoon. This discrepancy is mirrored by overestimated liquid water path cloud‐top height. These overestimations linked to overpredicted boundary‐layer development easier trigger misrepresented LES runs. Our underscores need improve representations processes interactions within better simulate future.

Язык: Английский

A novel vegetation-water resistant soil moisture index for remotely assessing soil surface moisture content under the low-moderate wheat cover DOI
Jibo Yue, Ting Li, Yang Liu

и другие.

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 224, С. 109223 - 109223

Опубликована: Июль 10, 2024

Язык: Английский

Процитировано

6
An inclusive approach to crop soil moisture estimation: Leveraging satellite thermal infrared bands and vegetation indices on Google Earth engine DOI Creative Commons

Fatima Imtiaz,

Aitazaz A. Farooque,

Gurjit S. Randhawa

и другие.

Agricultural Water Management, Год журнала: 2024, Номер 306, С. 109172 - 109172

Опубликована: Ноя. 15, 2024

Язык: Английский

Процитировано

6
The daily soil water content monitoring of cropland in irrigation area using Sentinel-2/3 spatio-temporal fusion and machine learning DOI Creative Commons

Ruiqi Du,

Youzhen Xiang, Junying Chen

и другие.

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 132, С. 104081 - 104081

Опубликована: Авг. 1, 2024

Understanding soil moisture dynamics is crucial for crop growth. The digital mapping of field distribution provides valuable information agricultural water management. optical satellite data fine scale a region. However, these are greatly limited due to cloud contamination and revisit period. Despite the reported beneficial effects spatiotemporal fusion methods, accurate estimates high-resolution through still unclear, particularly when using Sentinel-2/3 images. This study introduces new estimation framework integrating spatio-temporal spectral from images machine learning algorithm,and thus provide spatiotemporally continuous estimation. includes four methods (ESTARRFM, Fit-FC, FSDAF STFMF) models (PLSR, SVM, RF GBRT). feasibility was validated in Hetao Irrigation Area Inner Mongolia, China. results showed that fused image generated by Fit-FC visually closest true image, followed ESTARFM, FSDAF, STFMF. fusion-machine provided reliable multi-layer (0 ∼ 20, 20 40 60 cm) irrigation area. dense time series facilitated detection events irrigated farmland. Our findings highlighted effectiveness providing daily monitoring farmland on large scale. These high spatial–temporal resolution growth resource management, contributing further expanding application remote sensing precision agriculture.

Язык: Английский

Процитировано

4
Remote sensing vegetation Indices-Driven models for sugarcane evapotranspiration estimation in the semiarid Ethiopian Rift Valley DOI
Gezahegn Weldu Woldemariam, Berhan Gessesse Awoke, Raian Vargas Maretto

и другие.

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2024, Номер 215, С. 136 - 156

Опубликована: Июль 8, 2024

Язык: Английский

Процитировано

3
SAR2ET: End-to-End SAR-Driven Multisource ET Imagery Estimation Over Croplands DOI Creative Commons
Samet Çetin, Berk Ülker, Esra Erten

и другие.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2024, Номер 17, С. 14790 - 14805

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

3
Enhancing field soil moisture content monitoring using laboratory-based soil spectral measurements and radiative transfer models DOI Creative Commons
Jibo Yue, Ting Li, Haikuan Feng

и другие.

Agriculture Communications, Год журнала: 2024, Номер unknown, С. 100060 - 100060

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

3
Satellite-Based energy balance for estimating actual sugarcane evapotranspiration in the Ethiopian Rift Valley DOI
Gezahegn Weldu Woldemariam, Berhan Gessesse Awoke, Raian Vargas Maretto

и другие.

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2025, Номер 223, С. 109 - 130

Опубликована: Март 13, 2025

Язык: Английский

Процитировано

0
A universal triangle method for evapotranspiration estimation with MODIS products and routine meteorological observations: Algorithm development and global validation DOI Creative Commons
Wenbin Zhu, Xiaorui Shi,

Jiaxing Wei

и другие.

Agricultural Water Management, Год журнала: 2024, Номер 302, С. 109017 - 109017

Опубликована: Авг. 22, 2024

Язык: Английский

Процитировано

2
Vegetation Restoration Enhanced Canopy Interception and Soil Evaporation but Constrained Transpiration in Hekou–Longmen Section During 2000–2018 DOI Creative Commons

Peidong Han,

Guang Yang,

Yangyang Liu

и другие.

Agronomy, Год журнала: 2024, Номер 14(11), С. 2606 - 2606

Опубликована: Ноя. 5, 2024

The quantitative assessment of the impact vegetation restoration on evapotranspiration and its components is great significance in developing sustainable ecological strategies for water resources a given region. In this study, we used Priestley-Taylor Jet Pro-pulsion Laboratory (PT-JPL) to simulate ET Helong section (HLS) Yellow River basin. effects components, transpiration (Et), soil evaporation (Es), canopy interception (Ei) were separated by manipulating model variables. Our findings are as follows: (1) simulation results compared with calculated balance annual average MODIS products. R2 validation 0.61 0.78, respectively. show that PT-JPL tracks change HLS well. During 2000–2018, ET, Ei, Es increased at rate 1.33, 0.87, 2.99 mm/a, respectively, while Et decreased 2.52 mm/a. (2) Vegetation region from 331.26 mm (vegetation-unchanged scenario) 338.85 (vegetation during study period, an increase 2.3%. (3) TMP (temperature) VPD (vapor pressure deficit) dominant factors affecting changes most areas HLS. more than 37.2% HLS, dominated vapor difference (VPD) area 30.5% Overall, precipitation (PRE) main changes. Compared previous studies directly explore relationship between many influencing through correlation research methods, our uses control variables obtain under two different scenarios then performs analysis. This method can reduce excessive interference other results. provide strategic support future resource management

Язык: Английский

Процитировано

2
First Assessment of Cloud‐Land Coupling in LASSO Large‐Eddy Simulations DOI Creative Commons
Haipeng Zhang, Tianning Su, Youtong Zheng

и другие.

Geophysical Research Letters, Год журнала: 2024, Номер 51(14)

Опубликована: Июль 26, 2024

Abstract To enhance our understanding of cloud simulations over land, this study provides the first assessment coupling between and land surface in Large‐Eddy Simulation (LES) Atmospheric Radiation Measurement Symbiotic Observation (LASSO) activity for shallow convection scenario. The analysis observation data reveals a diurnal cycle cloud‐land coupling, which co‐varies with fluxes. However, coupled (or decoupled) cumulus clouds are inadequately simulated, manifesting as too‐high low) occurrence frequency during afternoon. This discrepancy is mirrored by overestimated liquid water path cloud‐top height. These overestimations linked to overpredicted boundary‐layer development easier trigger misrepresented LES runs. Our underscores need improve representations processes interactions within better simulate future.

Язык: Английский

Процитировано

0