Coherence-guided InSAR deformation analysis in the presence of ongoing land surface changes in the Imperial Valley, California

While the Budyko framework has been a simple and convenient tool to assess runoff (Q) responses to climatic and surface changes, it has been unclear how parameters of a Budyko function represent the vertical land-atmosphere interactions. Here, we explicitly derived a two-parameter equation by correcting a boundary condition of the Budyko hypothesis. The correction enabled for the Budyko function to reflect the evaporative demand (Ep) that actively responds to soil moisture deficiency. The derived two-parameter function suggests that four physical variables control surface runoff; namely, precipitation (P), potential evaporation (Ep), wet-environment evaporation (Ew), and the catchment properties (n). We linked the derived Budyko function to a definitive complementary evaporation principle, and assessed the relative elasticities of Q to climatic and land surface changes. Results showed that P is the primary control of runoff changes in most of river basins across the world, but its importance declined with climatological aridity. In arid river basins, the catchment properties play a major role in changing runoff, while changes in Ep and Ew seem to exert minor influences on Q changes. It was also found that the two-parameter Budyko function can capture unusual negative correlation between the mean annual Q and Ep. This work suggests that at least two parameters are required for a Budyko function to properly describe the vertical interactions between the land and the atmosphere.

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Thermal and moisture response to land surface changes across different ecosystems over Heilong-Amur River Basin

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.151799 ◽

2021 ◽

pp. 151799

Author(s):

Tingxiang Liu ◽

Lingxue Yu ◽

Kun Bu ◽

Jiuchun Yang ◽

Fengqin Yan ◽

...

Keyword(s):

River Basin ◽

Land Surface ◽

Amur River Basin ◽

Amur River ◽

Surface Changes

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Improvement of Clustering Methods for Modelling Abrupt Land Surface Changes in Satellite Image Fusions

Remote Sensing ◽

10.3390/rs11151759 ◽

2019 ◽

Vol 11 (15) ◽

pp. 1759 ◽

Cited By ~ 4

Author(s):

Detang Zhong ◽

Fuqun Zhou

Keyword(s):

Land Surface ◽

Satellite Image ◽

Weighted Average ◽

Clustering Methods ◽

Fusion Model ◽

Dynamic Prediction ◽

New Methods ◽

Satellite Sensors ◽

Spectral Mixing ◽

Surface Changes

A key challenge in developing models for the fusion of surface reflectance data across multiple satellite sensors is ensuring that they apply to both gradual vegetation phenological dynamics and abrupt land surface changes. To better model land cover spatial and temporal changes, we proposed previously a Prediction Smooth Reflectance Fusion Model (PSRFM) that combines a dynamic prediction model based on the linear spectral mixing model with a smoothing filter corresponding to the weighted average of forward and backward temporal predictions. One of the significant advantages of PSRFM is that PSRFM can model abrupt land surface changes either through optimized clusters or the residuals of the predicted gradual changes. In this paper, we expanded our approach and developed more efficient methods for clustering. We applied the new methods for dramatic land surface changes caused by a flood and a forest fire. Comparison of the model outputs showed that the new methods can capture the land surface changes more effectively. We also compared the improved PSRFM to two most popular reflectance fusion algorithms: Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced version of STARFM (ESTARFM). The results showed that the improved PSRFM is more effective and outperforms STARFM and ESTARFM both visually and quantitatively.

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The influence of land surface changes on regional climate in Northwest China

Advances in Atmospheric Sciences ◽

10.1007/s00376-007-0527-6 ◽

2007 ◽

Vol 24 (3) ◽

pp. 527-537 ◽

Cited By ~ 5

Author(s):

Xingkui Xu ◽

Feng Zhang ◽

Jason K. Levy

Keyword(s):

Land Surface ◽

Regional Climate ◽

Northwest China ◽

Surface Changes

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Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Atmosphere ◽

10.3390/atmos12111525 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1525

Author(s):

Abdullah Ayub Khan ◽

Zaffar Ahmed Shaikh ◽

Asif Ali Laghari ◽

Sami Bourouis ◽

Asif Ali Wagan ◽

...

Keyword(s):

Land Surface ◽

P2p Network ◽

Dynamic Monitoring ◽

Distributed Data ◽

Distributed Monitoring ◽

Distributed Data Management ◽

Smart Contract ◽

Simulation Results ◽

Stored Information ◽

Surface Changes

In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based data are captured through drones and transmitted to the fog nodes. The main objective here is to enable process and schedule, to investigate individual captured entity (records) and to analyze changes in the blockchain storage with a secure hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. The proposed blockchain mechanism is also investigated for analyzing the fog-cloud-based stored information, which is referred to as smart contracts. These contracts are designed and deployed to automate the overall distributed monitoring system. They include the registration of UAVs (drones), the day-to-day dynamic captured drone-based images, and the update transactions in the immutable storage for future investigations. The simulation results show the merit of our framework. Indeed, through extensive experiments, the developed system provides good performances regarding monitoring and management tasks.

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Mid-Pliocene mesic subtropical hydroclimate over continents driven by land surface changes

10.5194/egusphere-egu21-13907 ◽

2021 ◽

Author(s):

Ran Feng ◽

Tripti Bhattacharya ◽

Bette Otto-bliesner ◽

Esther Brady ◽

Keyword(s):

Land Surface ◽

Atmospheric Carbon Dioxide ◽

Hadley Circulation ◽

Stationary Wave ◽

Wave Pattern ◽

Earth System ◽

Surface Warming ◽

Warming Pattern ◽

Earth System Models ◽

Surface Changes

Earth System Models (ESMs) project drying of the northern subtropics by the end of the 21st century. However, geologic evidence from intervals with elevated concentrations of atmospheric carbon dioxide (pCO2), like the mid-Pliocene, suggest mesic subtropical conditions. Several hypotheses, including an El Ni&#241;o-like SST pattern and weaker Hadley circulation, have been proposed to explain this mismatch. Here, we show that PlioMIP2 ensemble broadly capture the pattern of proxy reconstructed Pliocene hydroclimate, notably a wetter Sahel and southeast Asia. Sensitivity simulations reveal that this pattern is driven by summertime rainfall increases as a result of lowered albedo and a distinct surface warming pattern, generated by prescribed vegetation and ice sheet changes. The resultant tropospheric moistening and stationary wave pattern enhance moisture convergence into the northern subtropics. Our results suggest that mid-Pliocene hydroclimate is part of the Earth system feedback to sustained CO2 concentrations similar to today.<img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gepj.0005b442a70068203111161/sdaolpUECMynit/12UGE&app=m&a=0&c=d33f4ac1a0750ab37681b00412fa7633&ct=x&pn=gepj.elif&d=1" alt="">

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Water dynamics over a Western Patagonian watershed: Land surface changes and human factors

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.150221 ◽

2022 ◽

Vol 804 ◽

pp. 150221

Author(s):

L. Olivera-Guerra ◽

M. Quintanilla ◽

I. Moletto-Lobos ◽

E. Pichuante ◽

C. Zamorano-Elgueta ◽

...

Keyword(s):

Human Factors ◽

Land Surface ◽

Water Dynamics ◽

Surface Changes

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A robust adaptive spatial and temporal image fusion model for complex land surface changes

Remote Sensing of Environment ◽

10.1016/j.rse.2018.02.009 ◽

2018 ◽

Vol 208 ◽

pp. 42-62 ◽

Cited By ~ 38

Author(s):

Yongquan Zhao ◽

Bo Huang ◽

Huihui Song

Keyword(s):

Image Fusion ◽

Land Surface ◽

Fusion Model ◽

Robust Adaptive ◽

Surface Changes

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Sharpening the Sentinel-2 10 and 20 m Bands to Planetscope-0 3 m Resolution

Remote Sensing ◽

10.3390/rs12152406 ◽

2020 ◽

Vol 12 (15) ◽

pp. 2406 ◽

Cited By ~ 1

Author(s):

Zhongbin Li ◽

Hankui K. Zhang ◽

David P. Roy ◽

Lin Yan ◽

Haiyan Huang

Keyword(s):

Land Surface ◽

Large Scale ◽

Near Infrared ◽

Detailed Examination ◽

Modulation Transfer ◽

Computationally Efficient ◽

Red Edge ◽

Shortwave Infrared ◽

Sentinel 2 ◽

Surface Changes

Combination of near daily 3 m red, green, blue, and near infrared (NIR) Planetscope reflectance with lower temporal resolution 10 m and 20 m red, green, blue, NIR, red-edge, and shortwave infrared (SWIR) Sentinel-2 reflectance provides potential for improved global monitoring. Sharpening the Sentinel-2 reflectance with the Planetscope reflectance may enable near-daily 3 m monitoring in the visible, red-edge, NIR, and SWIR. However, there are two major issues, namely the different and spectrally nonoverlapping bands between the two sensors and surface changes that may occur in the period between the different sensor acquisitions. They are examined in this study that considers Sentinel-2 and Planetscope imagery acquired one day apart over three sites where land surface changes due to biomass burning occurred. Two well-established sharpening methods, high pass modulation (HPM) and Model 3 (M3), were used as they are multiresolution analysis methods that preserve the spectral properties of the low spatial resolution Sentinel-2 imagery (that are better radiometrically calibrated than Planetscope) and are relatively computationally efficient so that they can be applied at large scale. The Sentinel-2 point spread function (PSF) needed for the sharpening was derived analytically from published modulation transfer function (MTF) values. Synthetic Planetscope red-edge and SWIR bands were derived by linear regression of the Planetscope visible and NIR bands with the Sentinel-2 red-edge and SWIR bands. The HPM and M3 sharpening results were evaluated visually and quantitatively using the Q2n metric that quantifies spectral and spatial distortion. The HPM and M3 sharpening methods provided visually coherent and spatially detailed visible and NIR wavelength sharpened results with low distortion (Q2n values > 0.91). The sharpened red-edge and SWIR results were also coherent but had greater distortion (Q2n values > 0.76). Detailed examination at locations where surface changes between the Sentinel-2 and the Planetscope acquisitions occurred revealed that the HPM method, unlike the M3 method, could reliably sharpen the bands affected by the change. This is because HPM sharpening uses a per-pixel reflectance ratio in the spatial detail modulation which is relatively stable to reflectance changes. The paper concludes with a discussion of the implications of this research and the recommendation that the HPM sharpening be used considering its better performance when there are surface changes.

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