Extrapolating continuous vegetation water content to understand sub-daily backscatter variations DOI Creative Commons
Paul Vermunt, Susan Steele‐Dunne, Saeed Khabbazan

et al.

Hydrology and earth system sciences, Journal Year: 2022, Volume and Issue: 26(5), P. 1223 - 1241

Published: March 4, 2022

Abstract. Microwave observations are sensitive to vegetation water content (VWC). Consequently, the increasing temporal and spatial resolution of spaceborne microwave creates a unique opportunity study dynamics its role in diurnal cycle. However, we currently have limited understanding sub-daily variations VWC how they affect observations. This is partly due challenges associated with measuring internal for validation, particularly non-destructively, at timescales less than day. In this study, aimed (1) use field sensors reconstruct continuous records corn (2) these interpret behaviour 10 d time series polarimetric L-band backscatter high resolution. Sub-daily were calculated based on cumulative difference between estimated transpiration sap flow rates base stems. Destructive samples used constrain estimates validation. The inclusion surface canopy (dew or interception) soil moisture allowed us attribute hour-to-hour either VWC, water, variations. Our results showed that varied by %–20 % during day non-stressed conditions, effect was significant. Diurnal nocturnal dew formation affected vertically polarized most. Moreover, multiple linear regression suggested cycle typical dry leads 2 (HH, horizontally, cross-polarized) almost 4 (VV, vertically, polarized) times higher variation drydown does. These demonstrate radar potential provide unprecedented insight into land–atmosphere interactions timescales.

Language: Английский

Forest foliage fuel load estimation from multi-sensor spatiotemporal features DOI Creative Commons

Yanxi Li,

Rui Chen, Binbin He

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 115, P. 103101 - 103101

Published: Nov. 10, 2022

Foliage fuel is the most flammable component in crown fires. Spatiotemporal dynamics of foliage load (FFL) are important for fire managers to assess risk. Here, we integrated optical data from Landsat 8 Operational Land Imager (OLI) with synthetic aperture radar (SAR) Sentinel-1 estimate FFL. We first reconstructed seamless time series and imagery by accounting unequal intervals between image observations outliers. then extracted temporal features that proxies intra- inter-annual these series. In addition, derived spatial quantify context therefore used varying window sizes. The random forest regression was implemented importance spatiotemporal features, reduce errors, derive robust FFL estimates. satellite estimates were validated against 96 field measurements Pinus yunnanensis forests Liangshan Yi Autonomous Prefecture, Sichuan Province, China. Both SAR importantly contributed estimation. When only used, model achieved a R2 0.75 (relative Root Mean Squared Error (rRMSE) = 25.3 %), while when 0.76 (rRMSE 25.6 %). However, combined, increased 0.81 23.2 also found more predictors than captured context. demonstrated our mapping method case study Chinese relation occurrence fire. Our needs additional validation over different tree species types, yet has potential loads

Language: Английский

Citations

14
Dew/hoar frost on the canopies and underlying surfaces of two typical desert shrubs in Northwest China and their relevance to drought DOI
Xiaonan Guo, Yanfang Wang,

Haiming Yan

et al.

Journal of Hydrology, Journal Year: 2022, Volume and Issue: 609, P. 127880 - 127880

Published: April 26, 2022

Language: Английский

Citations

13
Assessment of spatiotemporal dynamics of diurnal fog occurrence in subtropical montane cloud forests DOI
Hsin‐Ju Li, Min‐Hui Lo, Jehn‐Yih Juang

et al.

Agricultural and Forest Meteorology, Journal Year: 2022, Volume and Issue: 317, P. 108899 - 108899

Published: March 14, 2022

Language: Английский

Citations

12
First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry DOI
Zhiqing Peng, Tianjie Zhao, Jiancheng Shi

et al.

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 302, P. 113970 - 113970

Published: Dec. 26, 2023

Language: Английский

Citations

6
Extrapolating continuous vegetation water content to understand sub-daily backscatter variations DOI Creative Commons
Paul Vermunt, Susan Steele‐Dunne, Saeed Khabbazan

et al.

Hydrology and earth system sciences, Journal Year: 2022, Volume and Issue: 26(5), P. 1223 - 1241

Published: March 4, 2022

Abstract. Microwave observations are sensitive to vegetation water content (VWC). Consequently, the increasing temporal and spatial resolution of spaceborne microwave creates a unique opportunity study dynamics its role in diurnal cycle. However, we currently have limited understanding sub-daily variations VWC how they affect observations. This is partly due challenges associated with measuring internal for validation, particularly non-destructively, at timescales less than day. In this study, aimed (1) use field sensors reconstruct continuous records corn (2) these interpret behaviour 10 d time series polarimetric L-band backscatter high resolution. Sub-daily were calculated based on cumulative difference between estimated transpiration sap flow rates base stems. Destructive samples used constrain estimates validation. The inclusion surface canopy (dew or interception) soil moisture allowed us attribute hour-to-hour either VWC, water, variations. Our results showed that varied by %–20 % during day non-stressed conditions, effect was significant. Diurnal nocturnal dew formation affected vertically polarized most. Moreover, multiple linear regression suggested cycle typical dry leads 2 (HH, horizontally, cross-polarized) almost 4 (VV, vertically, polarized) times higher variation drydown does. These demonstrate radar potential provide unprecedented insight into land–atmosphere interactions timescales.

Language: Английский

Citations

9