Bai Yun

Hebei Normal University · School of Geographic Sciences

The temporal dynamics of optimum stomatal conductance (g smax), as well differences between C 3 and C 4 crops, have rarely been considered in previous remote sensing (RS)-based Jarvis-type canopy conductance (G c) models. To address this issue, a RS-based two-leaf Jarvis-type G c model, RST-G c , was optimized and validated for C 3 and C 4 crops us...

Accurately mapping of regional-scale evapotranspiration (ET) from the croplands using remote sensing is currently challenged by limited spatial information on crop and field management to properly characterize the biophysical constraints on ET. A multi-model ensemble can potentially address this challenge, however, conventional ensemble models usin...

Satellite-based gross primary productivity (GPP) monitoring in croplands is challenging due to our limited ability to empirically constrain photosynthetic capacity and associated parameters. Here, we investigated if integrating land surface temperature (TR)-based evapotranspiration (ET) or latent heat flux (λE) into a Remote sensing-driven approach...

The current regional-scale process-based photosynthesis models use biome-specified values of maximum carboxylation rate at 25 °C ( V _{m 25}) in simulating ecosystem gross primary productivity (GPP). These models ignore the variations in V _{m 25} over time and space, resulting in substantial errors in regional estimates of cropla...

Global evapotranspiration modeling faces significant challenges in understanding the complex interplay between aerodynamic and canopy-surface conductance, especially in water-scarce environments. To address this issue, we developed a hybrid model called HSTIC by integrating a machine learning (ML) model for estimating surface relative humidity (RH_...

[Study region] The watersheds of the four flux sites in the United States were selected as the study areas for this research. [Study focus] This study validates the efficiency of Convolutional Long Short-Term Memory Network (ConvLSTM) models for site-scale ET_a prediction. We enhanced the ConvLSTM model by adding a Spatial Pyramid Pooling module (...

Photosynthesis (a key ecological process) is measured based on gross primary productivity (GPP), emphasizing the criticality of accurate GPP estimation to climate change research. The extant remote sensing-based approaches for GPP estimation were typically based on optical remote sensing data, neglecting the potential supplementary information from...

Gross Primary Productivity (GPP) plays a vital role in the carbon cycle of terrestrial ecosystems. For the purpose of assessing the performance of various GPP products in a typical tropical area, this study conducted an intercomparison of seven different GPP products over Hainan Island, China, and analyzed spatiotemporal characteristics of GPP in d...

Accurately quantifying terrestrial gross primary productivity (GPP) can provide insights into the dynamics of global ecosystems. Light Use Efficiency (LUE) models with simple and effective structures have been widely used to estimate GPP. However, GPP estimation using LUE models was biased due to inaccurately representing the nonlinear effect of so...

Accurately predicting actual evapotranspiration (ETa) at the regional scale is crucial for efficient water resource allocation and management. While previous studies mainly focused on predicting site-scale ETa, in-depth studies on regional-scale ETa are relatively scarce. This study aims to address this issue by proposing a MulSA-ConvLSTM model, wh...

Evapotranspiration (ET) represents a significant component of the global water flux cycle, yet nocturnal evapotranspiration (ETn) is often neglected, leading to underestimation of global evapotranspiration. As for cropland, accurate modeling of ETn is essential for rational water management and is important for sustainable agriculture development....

Accurately classifying and mapping winter wheat is important for agricultural development. It is difficult to meet the requirement of high accuracy when using single models to identify winter wheat; thus, model fusion methods have been used to improve classification accuracy. However, complex model fusion methods are challenging for winter wheat cl...

Quantifying the gap between actual and exploitable yields (Ya and Ye, respectively) at the regional scale is critical for understanding the scope and hotspots for future yield improvements. Remote sensing can provide geospatially continuous observations of crop growth, which is perceived as an effective means to overcome the scaling issue commonly...

Despite recent developments in geoscientific (e.g., physics- or data-driven) models, effectively assembling multiple models for approaching a benchmark solution remains challenging in many sub-disciplines of geoscientific fields. Here, we proposed an automated machine-learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this c...

Partitioning evapotranspiration (ET) into vegetation transpiration (T) and soil evaporation (E) is challenging, but it is key to improving the understanding of plant water use and changes in terrestrial ecosystems. Considering that the transpiration of vegetation at night is minimal and can be negligible, we established a machine learning model (i....

Accurately estimating aboveground biomass (AGB) is essential for assessing the ecological functions of coastal wetlands, and AGB of coastal wetlands is affected by Land use/land cover (LULC) types of conversion. To address this issue, in the current study, we used the Boreal Ecosystem Productivity Simulator (BEPS) model to simulate the AGB of the Y...

Estimating gross primary productivity (GPP) is important for simulating the subsequent carbon cycle elements and assessing the capacity of terrestrial ecosystems to support the sustainable development of human society. Light use efficiency (LUE) models were widely used to estimate GPP due to their concise model structures. However, quantifying LUEm...

Wetlands are one of the world’s most significant and vulnerable ecosystems. The wetlands of the Yellow River Delta are subject to multiple influences of ocean tidal action and the massive sediment deposits of the Yellow River, resulting in a more complex and unstable composition of land cover types. To better distinguish the wetlands in the region,...

Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security. However, using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to...

Despite recent developments in geoscientific (e.g., physics/data-driven) models, effectively assembling multiple models for approaching a benchmark solution remains challenging in many sub-disciplines of geoscientific fields. Here, we proposed an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this chall...

Drought is an extremely dangerous natural hazard that causes water crises, crop yield reduction, and ecosystem fires. Researchers have developed many drought indices based on ground-based climate data and various remote sensing data. Ground-based drought indices are more accurate but limited in coverage; while the remote sensing drought indices cov...

The slope (g1) of stomatal conductance to photosynthesis is an important parameter in the optimal stomatal behavior theory-based stomatal conductance model of Medlyn et al. (2011). Although studies have modelled the spatial variations in g1, disclosing its variations over environmental gradients and different plant functional types. However, the ab...

Terrestrial ecosystems in China are threatened by land use and future climate change. Understanding the effects of these changes on vegetation and the climate-vegetation interactions is critical for vegetation preservation and mitigation. However, land-use impacts on vegetation are neglected in terrestrial ecosystems exploration, and a deep underst...

Accurate extraction of crop cultivated area and spatial distribution is essential for food security. Crop classification methods based on machine learning and deep learning and remotely sensed time-series data are widely utilized to detect crop planting area. However, few studies assess the effectiveness of machine learning and deep learning algori...

Soil salinization is recognized as a key issue negatively affecting agricultural productivity and wetland ecology. It is necessary to develop effective methods for monitoring the spatiotemporal distribution of soil salinity at a regional scale. In this study, we proposed an optimized remote sensing-based model for detecting soil salinity in differe...

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the st...

Croplands play an important role in China’s agricultural production and food security. However, the shortage of water resource due to climate change and unsuitable utilization poses heavy pressure on agricultural water use in China. Water productivity (WP), defined as the amount of crop production per unit of water consumption by croplands, provide...

Achieving high crop yield with less irrigation is important to improve water productivity (WP) and irrigation water productivity (IWP) in water-limited regions in the North China Plain (NCP). Coupling the impacts of precipitation and irrigation on the crop yield is, therefore, an essential tool for understanding crop response to different water sou...

Accurate estimates of evapotranspiration (ET) over croplands on a regional scale can provide useful information for agricultural management. The hybrid ET model that combines the physical framework, namely the Penman-Monteith equation and machine learning (ML) algorithms, have proven to be effective in ET estimates. However, few studies compared th...

Accurate estimation of evapotranspiration (ET) can provide useful information for water management and sustainable agricultural development. However, most of the existing studies used physical models, which are not accurate enough due to our limited ability to represent the ET process accurately or rarely focused on cropland. In this study, we trai...

Estimating yield potential (Yp) and quantifying the contribution of suboptimum field managements to the yield gap (Yg) of crops are important for improving crop yield effectively. However, achieving this goal on a regional scale remains difficult because of challenges in collecting field management information. In this study, we retrieved crop mana...

Understanding the coupling of terrestrial ecosystem evapotranspiration (ET) and photosynthesis (gross primary productivity, GPP) is limited by inherent difficulties to provide accurate approximations of transpiration (T) and leaf-to-air vapor pressure difference (D) that is a key variable needed to define the stomata behaviors in generic methods. T...

Accurate information on cropland evapotranspiration (ET) can facilitate effective agricultural management. However, the application of existing physical models over broad regions may be impeded due to the need for difficult to acquire information about environmental factors that constrain ET. The recently developed near-infrared reflectance of vege...

Understanding the spatiotemporal dynamics of drought and its potential effect on crop production is critical in decision-making processes to support sustainable food production under climate change. This is especially true for China, the largest producer of cereal crops in the world, where production losses could significantly impact the global foo...

Drought is pervasive global hazard and seriously impacts ecology. Particularly, vegetation drought, which is chiefly driven by soil moisture (SM) deficiency, has a direct bearing on grain production and human livelihoods. Various drought indices associated with vegetation and SM conditions have been proposed to monitor and detect vegetation drought...

Understanding the response of terrestrial ecosystems to future climate changes would substantially contribute to the scientific assessment of vegetation–climate interactions. Here, the spatiotemporal distribution and dynamics of vegetation in China were projected and compared based on comprehensive sequential classification system (CSCS) model unde...

Drought has serious consequences for terrestrial ecosystems, particularly for their carbon and water processes. As an important indicator to examine the balance of ecosystem water and carbon cycles, ecosystem water use efficiency (WUE) has been widely used to investigate ecosystem responses to drought. However, the response of WUE to drought and th...

Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing (RS) approaches limited their applications over broad regions. In this study, a process-based and remot...

Studying the significant impacts of drought on vegetation is crucial to understand its dynamics and interrelationships with precipitation, soil moisture, and temperature. In North and West Africa regions, the effects of drought on vegetation have not been clearly stated. Therefore, the present study aims to bring out the drought fluctuations within...

The impact of Land use/land cover (LULC) change was assessed through monitoring the distribution of ecological indicators and tracking the aeolian deposits, which provides valuable information on desertification and climate change in Tunisian arid regions. This study was conducted in Oum Zessar area, in southeastern Tunisia. Both visual interpretat...

Proper estimation and spatiotemporal trend analysis of net primary productivity (NPP) are very important for forest ecosystem monitoring and management. In this article, we investigate the spatiotemporal trend and variability of the Boreal Ecosystem Productivity Simulator (BEPS)-derived forest NPP over Nepal during the period 2000–2015. This study...

Ecosystem water-use efficiency (WUE) is a critical indicator to investigate the interaction between the terrestrial ecosystem carbon and water cycles. WUE, estimated from gross primary productivity (GPP) and evapotranspiration (ET) based on remote sensing (RS)-based ecosystem models and algorithms (e.g., MODIS (MODerate resolution Imaging Spectrora...

In South Asia, key differences in annual land use and land cover (LULC) take place due to climate change, global warming, human activity, biodiversity, and hydrology. So, it is very important to get accurate land cover information for this region. An annual LULC map that covers a comprehensive period is a major dataset for climatologically study. W...

Drought is a very complex natural hazard and has a negative impact on the global ecosystem as a whole. Recently Bangladesh has been experiencing by different degree of dryness as a consequence of high climate variability, affecting the crop production to a great extent in the last couple of decades. In this context, the present study was made an ef...

Drought is a very complex natural hazard and has a negative impact on the global ecosystem as a whole. Recently Bangladesh has been experiencing by different degree of dryness as a consequence of high climate variability, affecting the crop production to a great extent in the last couple of decades. In this context, the present study was made an ef...

Evapotranspiration (ET) is a pivotal process for ecosystem water budgets and accounts for a substantial portion of the global energy balance. In this paper, the exited actual ET main datasets in global scale, and the global ET modeling and estimates were focused on discussion. The Source energy balance (SEB) models, empirical models and other proce...

North and West Africa are the most vulnerable regions to drought, due to the high variation in monthly precipitation. An accurate and efficient monitoring of drought is essential. In this study, we use TRMM data with remote sensing tools for effective monitoring of drought. The Drought Severity Index (DSI), Temperature Vegetation Drought Index (TVD...

Mapping land cover changes (LCC) cover three decades over North and West Africa regions provides critical insights for the climate research that inspects the land-atmosphere interaction. LCC is a serious problem in the Earth science domain for this impacts the regional climate by modifying the distribution of terrestrial carbon stocking and roughne...

Evaluating the potential productivity of the terrestrial ecosystem is extremely important to ascertain the threshold of vegetation productivity, to maximize the utilization of regional climate resources, carbon sequestration and to mitigate climate warming caused by rising CO2 concentrations. However, most previous studies neglected the optimum sta...

Located across the equator, the East Africa region is among regions of Africa which have previously known the severe vegetation degradation. Some known reasons are associated with the climate change events and unprofessional agricultural practices. For this purpose, the Advanced Very High Resolution Radiometer (AVHRR) version 3 NDVI (NDVI3g) and Cl...

Better understanding of the temporal-spatial distribution of chlorophyll-a concentration (Chla) is crucial in controlling harmful water blooms. In this study, the dynamical change of Chl-a over the Bohai Sea and Yellow Sea from 2003-2017 were analyzed by using the MODIS/Aqua satellite data, and the effects of sea surface temperature (SST), wind and...

Drought is one of the most frequent disasters occurring in North China and has a great influence on agriculture, ecology and economy. To monitor drought of typical dry areas in North China, Shandong Province, this paper proposed composite drought indices using multivariable linear regression (MCDIs) to integrate Tropical Rainfall Measuring Mission...

Remote sensing (RS) is a convenient technology to estimate the regional cultivation areas of crops. However, the accurate estimation of maize areas using RS over a broad region is a sign