Jianfei Cao

Spatiotemporal Changes and Influencing Factors of Carbon Storage in the Jinan Metropolitan Area, China, Using the InVEST Model Coupled with XGBoost-SHAP and MGWR Models

Yubin Liu, Jianfei Cao, Chao Fan, Bing Zhang

Within the framework of the dual carbon strategy, investigating the spatiotemporal characteristics and driving factors of carbon sequestration in metropolitan areas through land use analysis is important for mitigating climate change and promoting regional ecological protection and sustainable development. On the basis …

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Enhancing the Estimation and Mapping of Soil Cadmium by Using Geospatial Information-Guided Machine Learning and Principal Component Spectra

Jianfei Cao, Yihui Liu, Xinrong Duan, Xiaoli Liu et autres

Integrating machine learning with spectral data provides an effective and cost-efficient scheme for estimating cadmium (Cd) contents in soils compared with labor-intensive laboratory analyses. However, conventional machine learning–based spectral estimation methods often yield unsatisfactory performance because they rely on an unrealistic assumption …

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Synthetic control inference for staggered adoption

Jianfei Cao, Shirley Lu, Hang Wu

Summary Many policies are replicated by other policymakers at different times. We introduce a synthetic control methodology to study policies with staggered adoption. Our method estimates the dynamic average treatment effects on the treated using variation introduced by the staggered adoption of …

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Nephrologist Affiliation With Dialysis Facilities and Patient Trajectories in End-Stage Kidney Disease

Farbod Alinezhad, Gary J. Young, Richard Hirth, Jianfei Cao et autres

Importance: Across the treatment modalities for end-stage kidney disease (ESKD), kidney transplantation offers the best survival and quality-of-life outcomes, yet most patients are unable to receive a transplant, making dialysis the most common long-term treatment option. Despite its advantages, home peritoneal dialysis …

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Exploring moisture-resistant Vis-NIR spectral indices for estimating salinity in coastal saline soil of eastern China

Jianfei Cao, Han Yang, Dongchao Wang

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Modeling Uncertainties in Spatiotemporal Dynamic of Vegetation Above- and Belowground Production on the Tibetan Plateau

Tao Zhou, Peng Hou, Benjamin Laffitte, Yuting Hou et autres

Net primary production (NPP), comprising both aboveground (ANPP) and belowground (BNPP) components, serves as a critical indicator for evaluating terrestrial ecosystem responses to climate change. However, poorly characterized BNPP spatiotemporal dynamics limit carbon allocation understanding on the Tibetan Plateau (TP), and the …

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The Labor-Market Impact of Board Gender Quotas and Disclosure Policies

Jianfei Cao, Yuling Han, Shirley Lu

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Robust IV inference with clustering dependence

Jianfei Cao

Summary Linear instrumental variables (IV) models with clustering dependence are widely used in empirical studies, although the common solution, the cluster covariance estimator, often produces undesirable inferential results, especially with weak instruments. In this paper, I propose a method that is robust …

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Artificial Geographically Weighted Neural Network: A Novel Framework for Spatial Analysis with Geographically Weighted Layers

Jianfei Cao, Dongchao Wang

Geographically Weighted Regression (GWR) is a widely recognized technique for modeling spatial heterogeneity. However, it is commonly assumed that the relationships between dependent and independent variables are linear. To overcome this limitation, we propose an Artificial Geographically Weighted Neural Network (AGWNN), a …

Predicting nickel concentration in soil using fractional-order derivative and visible-near-infrared spectroscopy indices

Jianfei Cao, Wei Liu, Yongyu Feng, Jianhua Liu et autres

Accurate monitoring and estimation of heavy metal concentrations is an important process in the prevention and treatment of soil pollution. However, the weak correlation between spectra and heavy metals in soil makes it difficult to use spectroscopy in predicting areas with a …

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A Novel Flexible Geographically Weighted Neural Network for High-Precision PM2.5 Mapping across the Contiguous United States

Dongchao Wang, Jianfei Cao, Baolei Zhang, Ye Zhang et autres

Air quality degradation has triggered a large-scale public health crisis globally. Existing machine learning techniques have been used to attempt the remote sensing estimates of PM2.5. However, many machine learning models ignore the spatial non-stationarity of predictive variables. To address this issue, …

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An Imputation Method Based on the Varimax Variant of Multivariate Singular Spectrum Analysis

Yuning Fu, Xincheng Fan, Jianfei Cao

Singular Spectrum Analysis (SSA) and its Multivariate extension (mSSA) are powerful tools for decomposing time series into ’skeleton’ signals and residual noise. To address the issue of eigenvector mixing, Groth and Ghil (2011) introduced the varimax mSSA algorithm. Despite its widespread use, …

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