Evaluation of a deep-learning model for multispectral remote sensing of land use and crop classification

High-resolution deep-learning-based remote-sensing imagery analysis has been widely used in land-use and crop-classification mapping. However, the influence of composite feature bands, including complex feature indices arising from different sensors on the backbone, patch size, and predictions in transferable deep models require further testing. The experiments were conducted in six sites in Henan province from2019 to 2021. This study sought to enable the transfer of classification models across regions and years for Sentinel-2 A(10-m resolution) and Gaofen PMS(2-m resolution) imagery. With feature selection and up-sampling of small samples, the performance of UNet++ architecture on five backbones and four patch sizes was examined. Joint loss, mean Intersection over Union(m Io U), and epoch time were analyzed, and the optimal backbone and patch size for both sensors were Timm-Reg Net Y-320 and 256 × 256, respectively. The overall accuracy and Fscores of the Sentinel-2 A predictions ranged from 96.86% to 97.72%and 71.29% to 80.75%, respectively, compared to 75.34%–97.72% and 54.89%–73.25% for the Gaofen predictions. The accuracies of each site indicated that patch size exerted a greater influence on model performance than the backbone. The feature-selection-based predictions with UNet++ architecture and upsampling of minor classes demonstrated the capabilities of deep-learning generalization for classifying complex ground objects, offering improved performance compared to the UNet, Deeplab V3+, Random Forest, and Object-Oriented Classification models. In addition to the overall accuracy, confusion matrices,precision, recall, and F1 scores should be evaluated for minor land-cover types. This study contributes to large-scale, dynamic, and near-real-time land-use and crop mapping by integrating deep learning and multi-source remote-sensing imagery.

Case study of a driven pile foundation in diatomaceous soil.II:Pile installation,dynamic analysis,and pore pressure generation

This paper presents the results from a case study highlighting the difficulties of pile driving in diatomaceous soils.In the companion(first)paper to this article,results of an extensive laboratory and in situ testing program were presented while the results from pile driving and further analysis of field observations were presented herein.Unexpected high pile rebound(HPR)was observed during driving of a closed-end pipe pile,with refusal occurring at a depth of less than 5 m.Subsequent open-ended piles were thus driven.Piezometer and case pile wave analysis program(CAPWAP)data were collected during driving of both closed-and open-end piles.Piezometer data indicated that negative pore water pressures(PWPs)were generated while the closed-ended pile exhibited high rebound.Results from in situ tests indicated change in material stiffness and strong dilative tendencies near the depth of refusal.A hypothesis for observed behavior was proposed that considers the soil beneath the pile as a medium with an effectively infinite bulk modulus.

Case study of a driven pile foundation in diatomaceous soil.I:Site characterization and engineering properties

Diatomaceous soils are comprised of the silica frustules of diatom microalgae that are present in marine and lacustrine environments throughout the world.Owing to their unique origin,diatomaceous soils are typically characterized by high intraparticle porosity,complex particle shapes,and uniform mineralogy,causing them to exhibit atypical physical and engineering behaviors.A substantial deposit of diatomaceous silt was observed during site exploration for construction of the Buck Creek Bridge on OR140 near Klamath Falls,OR,USA.A comprehensive laboratory and in situ testing program indicated that the diatomaceous soil possessed“non-textbook”engineering properties.Specifically,tested samples had high liquid limits(≈100%-140%)with natural water contents at or near the liquid limit.Geologically,the soil is expected to be normally consolidated,yet high apparent overconsolidation ratios(OCR)(≈15-40)were observed both in oedometric consolidation tests and through cone penetration test(CPT)correlations.Standard penetration test(SPT)results show a corrected standard penetration resistance consistent with a medium-dense sand(i.e.(N1)_(60)≈25).CPT results include corrected tip resistances(qt)of approximately 7-10 MPa and excess pore pressures(u_(2))of up to 4 MPa.In CPT dissipation tests,pore water pressures(PWPs)returned to hydrostatic pressure in less than 1 h.In this work,we synthesize these seemingly disparate material properties in an attempt to infer appropriate engineering properties for the diatomaceous deposit at the Buck Creek Bridge and attempt to provide insight into the underlying reasons for the observed behavior.

Benefit of aerosol reduction to winter wheat during China's clean air action:A case study of Henan Province

A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action,yet its impact on wheat(Triticum aestivum L.)production remains unclear.We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018.After calibrating parameters with the extended Fourier Amplitude Sensitivity Test(EFAST)and the generalized likelihood uncertainty estimation(GLUE)method,the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately.We found that the aerosol negatively impacted wheat biomass by 21.87%and yield by 22.48%from 2006 to 2018,and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity.Due to the strict clean air action,under all-sky conditions,the surface solar shortwave radiation(SSR)in 2018 increased by about 7.08%over 2006-2013 during the wheat growing seasons.As a result of the improvement of crop photosynthesis,winter wheat biomass and yield increased by an average of 5.46%and 2.9%,respectively.Our findings show that crop carbon uptake and yield will benefit from the clean air action in China,helping to ensure national food and health security.

A Model of the Sea-Land Transition of the Mean Wind Profile in the Tropical Cyclone Boundary Layer Considering Climate Changes

The tropical cyclone boundary layer(TCBL)connecting the underlying terrain and the upper atmosphere plays a crucial role in the overall dynamics of a tropical cyclone system.When tropical cyclones approach the coastline,the wind field inside the TCBL makes a sea-land transition to impact both onshore and offshore structures.So better understanding of the wind field inside the TCBL in the sea-land transition zone is of great importance.To this end,a semiempirical model that integrates the sea-land transition model from the Engineering Sciences Data Unit(ESDU),Huang's refined TCBL wind field model,and the climate change scenarios from the Coupled Model Intercomparison Project Phase 6(CMIP6)is used to investigate the influence of climate changes on the sea-land transition of the TCBL wind flow in Hong Kong.More specifically,such a semiempirical method is employed in a series of Monte-Carlo simulations to predict the wind profiles inside the TCBL across the coastline of Hong Kong under the impact of future climate changes.The wind profiles calculated based on the Monte-Carlo simulation results reveal that,under the influences of the most severe climate change scenario,slightly higher and significantly lower wind speeds are found at altitudes above and below 400 m,respectively,compared to the wind speeds recommended in the Hong Kong Wind Code of Practice.Such findings imply that the wind profile model currently adopted by the Hong Kong authorities in assessing the safety of low-to high-rise buildings may be unnecessarily over-conservative under the influence of climate change.On the other hand,the coded wind loads on super-tall buildings slightly underestimate the typhoon impacts under the severe climate change conditions anticipated for coastal southern China.