Zengjing Song

• Bachelor of Science
• Southwest University

Canopy closure is a critical indicator reflecting forest structure, biodiversity, and ecological balance. This study proposes an estimation method integrating U-Net segmentation with machine learning, significantly improving accuracy through multi-source remote sensing data and feature selection. Covering eight U.S. continental states, the study ut...

Drought-induced plant hydraulic failure is one of the main factors for large-scale plant mortality. Understanding the response of the plants to water stress is of paramount importance to elucidate the dynamics of water, energy and carbon fluxes under drought conditions. In this study, we implemented the plant hydraulics pathway in STEMMUS-SCOPE (he...

Water supply is the most critical constraint for vegetation growth and food security. The amount of water demand by plant growth is usually estimated by plant water requirement which unfortunately cannot be directly measured at any large scale in field conditions. Different estimation methods have been proposed in the past seven decades for estimat...

This study aims to examine the individual and combined effects of soil moisture (SM) and vapor pressure deficit (VPD) on ecosystem productivity in Southwest China. Utilizing the community land model (CLM) to simulate the regional soil moisture and vapor pressure deficit, we analyzed their impacts on ecosystem productivity through a data binning app...

The rapid advancement of remote sensing technology has given rise to numerous global- and regional-scale medium- to high-resolution land cover (LC) datasets, making significant contributions to the exploration of worldwide environmental shifts and the sustainable governance of natural resources. Nonetheless, owing to the inherent uncertainties embe...

Revegetation is one of the most effective ways to combat desertification and soil erosion in semiarid and arid regions. However, the impact of the perturbation of revegetation on ecohydrological processes, particularly its effects on the interplay between hydrological processes and vegetation growth under water stress, requires further investigatio...

Revegetation is one of the most effective ways to combat desertification and soil erosion in semiarid and arid regions. However, the perturbation of ecohydrological processes revegetation remains to be studied, especially its effect on the complex interaction between the hydrological processes and vegetation growth under water stress. This study ev...

The validation of remote sensing land surface temperature (LST) data necessitates a comparison between satellite retrieval outcomes and in situ observations. The efficiency of in situ observations can be ameliorated via analysis and modeling, whereby the heterogeneity of in situ observations on temporal and spatial scales is central to the an...

BackgroundsVegetation dynamics play a dominant role in the global carbon cycle and climate, especially in vulnerable karst ecosystem. Many studies have examined the past several decades changes in vegetation greenness and the associated with climate drivers. Yet, few studies have analyzed the vegetation change in global karst regions particularly i...

Land surface temperature (LST) is an essential parameter in land–atmosphere interaction. However, it is still poorly understood about the effects of seasonal LST on the interannual LST change and the dominant driving force for the variation in LST. In this study, trends of time-series LST were analyzed by using both linear and nonlinear methods. Tw...

This review has mainly focused on China and Bangladesh, as taken in some parts of comparison due to climate changes (CC) affected the country. The study implicated a range of socioeconomic and agro-economic literature that was developed subsequent two different development trail linked with the Intergovernmental Panel on Climate Change (IPCC) pessi...

While a number of machine learning (ML) models have been used to estimate RE, systematic evaluation and comparison of these models are still limited. In this study, we developed three traditional ML models and a deep learning (DL) model, stacked autoencoders (SAE), to estimate RE in northern China’s grasslands. The four models were trained with two...

Significant impact of extreme droughts on human society and ecosystem has occurred in many places of the world, for example, Southwest China (SWC). Considerable research concentrated on analyzing causes and effects of droughts in SWC, but few studies have examined seasonal indicators, such as variations of surface water and vegetation phenology. Wi...

With advantages of multispatial resolutions, a high retrieval accuracy, and a high temporal resolution, the satellite-derived land surface temperature (LST) products are very important LST sources. However, the greatest barrier to their wide application is the invalid values produced by large quantities of cloudy pixels, especially for regions freq...

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine p...