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Publications (82)
Accurate measurements of maize yields at field or subfield scales are useful for guiding agronomic practices and investments and policies for improving food security. Data on smallholder maize systems are currently sparse, but satellite remote sensing offers promise for accelerating learning about these systems. Here we document the use of Google E...
The increasing availability of satellite data at higher spatial, temporal and spectral resolutions is enabling new applications in agriculture and economic development, including agricultural insurance. Yet, effectively using satellite data in this context requires blending technical knowledge about their capabilities and limitations with an unders...
Land cover classification in remote sensing is often faced with the challenge of limited ground truth labels. Incorporating historical ground information has the potential to significantly lower the expensive cost associated with collecting ground truth and, more importantly, enable early- and in-season mapping that is helpful to many pre-harvest d...
How climate change will affect overwintering crops is largely unknown due to the complex and understudied interactions among temperature, rainfall and snowpack. Increases in average winter temperature should release cold limitations yet warming-induced reductions of snowpack thickness should lead to decreased insulation effects and more exposure to...
Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gas (GHG) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human act...
Tile drainage removes excess water and is an essential, widely adopted management practice to enhance crop productivity in the U.S. Midwest. Tile drainage has been shown to significantly change hydrological and biogeochemical cycles by lowering the water table and reducing the residence time of soil water, although such impacts and their connection...
The ability to automatically build 3D digital twins of plants from images has countless applications in agriculture, environmental science, robotics, and other fields. However, current 3D reconstruction methods fail to recover complete shapes of plants due to heavy occlusion and complex geometries. In this work, we present a novel method for 3D rec...
Crop rotation has been widely used to enhance crop yields and mitigate adverse climate impacts. The existing research predominantly focuses on the impacts of crop rotation under growing season (GS) climates, neglecting the influences of non‐GS (NGS) climates on agroecosystems. This oversight limits our understanding of the comprehensive climatic im...
Streamflow, vital for water resource management, is governed by complex hydrological systems involving intermediate processes driven by meteorological forces. While deep learning models have achieved state-of-the-art results of streamflow prediction, their end-to-end single-task learning approach often fails to capture the causal relationships with...
Agriculture’s global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture’s environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil er...
The olive tree holds great cultural, environmental, and economic significance in the Mediterranean region. In particular, Morocco has been making dedicated investments over $10 billion since 2008 to fuel the transition from cereal to olive production. Understanding the spatial extent of this large-scale land conversion is critical for a variety of...
Multiple lines of evidence confirm a widespread increase in vegetation growth across China over the past few decades. The relationship between vegetation growth and water availability is thought to be becoming stronger under climate change, that is, water constraints on vegetation growth have been increasing. However, our understanding of how water...
Monitoring and modeling the growth of strawberries at the individual fruit level can open up new opportunities for yield prediction, fruit grading and supply chain optimization. However, existing strawberry growth models mainly focus on plot or plant level and can not simulate the growth of individual fruits, and existing computer vision (CV)-based...
Accurate prediction of water quality and quantity is crucial for sustainable development and human well-being. However, existing data-driven methods often suffer from spatial biases in model performance due to heterogeneous data, limited observations, and noisy sensor data. To overcome these challenges, we propose Fair-Graph, a novel graph-based re...
Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes...
Process-based models are widely used to predict the agroecosystem dynamics, but such modeled results often contain considerable uncertainty due to the imperfect model structure, biased model parameters, and inaccurate or inaccessible model inputs. Data assimilation (DA) techniques are widely adopted to reduce prediction uncertainty by calibrating m...
Agricultural irrigation induces greenhouse gas emissions directly from soils or indirectly through the use of energy or construction of dams and irrigation infrastructure, while climate change affects irrigation demand, water availability and the greenhouse gas intensity of irrigation energy. Here, we present a scoping review to elaborate on these...
Cover crops have long been seen as an effective management practice to increase soil organic carbon (SOC) and reduce nitrogen (N) leaching. However, there are large uncertainties in quantifying these ecosystem services using either observation (e.g. field measurement, remote sensing data) or process-based modeling. In this study, we developed and i...
Improving the estimation of CO exchange between the atmosphere and terrestrial ecosystems is critical to reducing the large uncertainty in the global carbon budget. Large amounts of the atmospheric CO assimilated by plants return to the atmosphere by ecosystem respiration (Reco), including plant autotrophic respiration (Ra) and soil microbial heter...
Cashews are grown by over 3 million smallholder farmers in >40 countries worldwide as a principal source of income. Expanding the area of cashew plantations and increasing productivity are critical to improving the livelihood of many smallholder communities. As the third largest cashew producer in Africa, Benin has nearly 200,000 smallholder cashew...
This paper proposes a physics-guided neural network model to predict crop yield and maintain the fairness over space. Failures to preserve the spatial fairness in predicted maps of crop yields can result in biased policies and intervention strategies in the distribution of assistance or subsidies in supporting individuals at risk. Existing methods...
Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These applications greatly rely on regional features that characterize spatial and temporal differences. However, spatio-temporal data often exhibit complex patterns and signif...
Maize (Zea mays), the second most-produced crop worldwide, serves as the cornerstone for global food security and human livelihood. Early-season maize mapping benefits maize production forecasting and other pre-harvest decision-making applications. However, most existing early-season mapping efforts rely heavily on either the current-year or histor...
Cover crops have been reported as one of the most effective practices to increase soil organic carbon (SOC) for agroecosystems. Impacts of cover crops on SOC change vary depending on soil properties, climate, and management practices, but it remains unclear how these controlling factors affect SOC benefits from cover crops, as well as which managem...
Forage supply has been stressed due to the rapid increase in China's livestock consumption. However, the long-term dynamics of the relationships between forage demand and multi-sourced supply are not understood. Here, we examine the annual forage demand, or practical carrying capacity (PCC), and supply, or theoretical carrying capacity, (TCC) from...
Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland c...
Cashews are grown by over 3 million smallholders in more than 40 countries worldwide as a principal source of income. As the third largest cashew producer in Africa, Benin has nearly 200,000 smallholder cashew growers contributing 15% of the country's national export earnings. However, a lack of information on where and how cashew trees grow across...
Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These applications greatly rely on regional features that characterize spatial and temporal differences. However, spatio-temporal data are often complex and pose several unique...
In-season monitoring and forecasting of the carbon cycle of the agroecosystem are crucial to field management, market analysis, and policy making. When the researchers devote their efforts to depicting the comprehensive processes of the agroecosystem, biased model parameters and inaccessible management information introduce considerable uncertainty...
Annual food caloric production is the product of caloric yield, cropping frequency (CF, number of production seasons per year) and cropland area. Existing studies have largely focused on crop yield, whereas how CF responds to climate change remains poorly understood. Here, we evaluate the global climate sensitivity of caloric yields and CF at natio...
Achieving food security in sub-Saharan Africa (SSA) is a multidimensional challenge. SSA reliance on food imports is expected to grow in the coming decades to meet the population's demand, projected to double to over 2 billion people by 2050. In addition, climate change is already affecting food production and supply chains across the region. Addre...
Bangladesh is one of the most vulnerable countries to natural disasters such as droughts in the world. The pre-monsoon Aus rice in Bangladesh depends on rainfall and is threatened by increasing droughts. However, limited information on the changes in Aus rice as well as droughts hamper our understanding of the country’s agricultural resilience and...
Hydrological changes under climate warming drive the biogeomorphic succession of wetlands and may trigger substantial carbon loss from the carbon-rich ecosystems. Although many studies have explored the responses of wetland carbon emissions to short-term hydrological change, it remains poorly understood how the carbon cycle evolves with hydrology-d...
Variety adaptation to future climate for wheat is important but lacks comprehensive understanding. Here, we evaluate genetic advancement under current and future climate using a dataset of wheat breeding nurseries in North America during 1960-2018. Results show that yields declined by 3.6% per 1 °C warming for advanced winter wheat breeding lines,...
Agricultural N2O emission is a growing concern for climate change. Recent field evidence suggests that non-growing seasons (NGS) may contribute one-third to half of the annual N2O emissions, but implications on management adaptations remain unclear. Here we used an advanced process-based model, ecosys, to investigate the magnitude and drivers of NG...
Detailed and updated maps of actively cropped fields on a national scale are vital for global food security. Unfortunately, this information is not provided in existing land cover datasets, especially lacking in smallholder farmer systems. Mapping national-scale cropped fields remains challenging due to the spectral confusion with abandoned vegetat...
Wetland CH4 emissions are among the most uncertain components of the global CH4 budget. The complex nature of wetland CH4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH4 emissions. In this study, we used the flux measurements of CH4 from eddy covariance towers (30 sites from...
Improving nitrogen (N) use efficiency is urgently needed to achieve co-sustainability of agricultural productivity and environmental quality. Environmental conditions and farming management practices affect the N cycle in agroecosystems. Particularly, weather conditions during the pre-growing-season (e.g. winter and early spring for the U.S. Corn B...
Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N2O and CH4) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”...
Crop pests and diseases (CPDs) are emerging threats to global food security, but trends in the occurrence of pests and diseases remain largely unknown due to the lack of observations for major crop producers. Here, on the basis of a unique historical dataset with more than 5,500 statistical records, we found an increased occurrence of CPDs in every...
Land cover classification in remote sensing is often faced with the challenge of limited ground truth labels. Incorporating historical ground information has the potential to significantly lower the expensive cost associated with collecting ground truth and, more importantly, enable early-and in-season mapping that is helpful to many pre-harvest de...
Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gases (GHGs) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human...
Growing cover crops is one of the most promising conservation practices with multiple benefits. However, the impacts of cover crops on the productivity of the maize-soybean [Zea mays L. - Glycine max (L.) Merr.] rotation system in the U.S. Midwest still have large uncertainties based on results obtained from field experiments, specifically across d...
Collecting large annotated datasets in Remote Sensing is often expensive and thus can become a major obstacle for training advanced machine learning models. Common techniques of addressing this issue, based on the underlying idea of pre-training the Deep Neural Networks (DNN) on freely available large datasets, cannot be used for Remote Sensing due...
As one of the major agricultural production areas in the world, the United States (U.S.) Midwest plays a vital role in the global food supply and agricultural ecosystem services. Although significant efforts have been made in modeling the carbon cycle dynamics over this area, large uncertainty still exists in the previous simulations in terms of re...
The high productivity in the US Corn Belt is largely enabled by the consumption of millions of tons of manufactured fertilizer. Excessive application of nitrogen (N) fertilizer has been pervasive in this region, and the unrecovered N eventually escaped from croplands in forms of nitrous oxide (N2O) emission and N leaching. Mitigating these negative...
The availability of massive earth observing satellite data provide huge opportunities for land use and land cover mapping. However, such mapping effort is challenging due to the existence of various land cover classes, noisy data, and the lack of proper labels. Also, each land cover class typically has its own unique temporal pattern and can be ide...
Timely and accurate monitoring of tree crop extent and productivities are necessary for informing policy-making and investments. However, except for a very few tree species (e.g., oil palms) with obvious canopy and extensive planting, most small-crown tree crops are understudied in the remote sensing domain. To conduct large-scale small-crown tree...
Foreknowledge of the spatiotemporal drivers of crop yield would provide a valuable source of information to optimize on-farm inputs and maximize profitability. In recent years, an abundance of spatial data providing information on soils, topography, and vegetation condition have become available from both proximal and remote sensing platforms. Give...
Imbalanced training sets are known to produce suboptimal maps for supervised classification. Therefore, one challenge in mapping land cover is acquiring training data that will allow classification with high overall accuracy (OA) in which each class is also mapped onto similar user's accuracy. To solve this problem, we integrated local adaptive reg...
Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. D...
Nitrogen (N) fertilizer management is one of the main concerns for precision agriculture under corn production, which aims to not only maximize the profits, but also ensure environmental sustainability. Effective N fertilizer management can either avoid N stress or provide timely and accurate detection of in-season N stress for remedies. Traditiona...
Understanding the determinants of agricultural productivity requires accurate measurement of crop output and yield. In smallholder production systems across low-and middle-income countries, crop yields have traditionally been assessed based on farmer-reported production and land areas in house-hold/farm surveys, occasionally by objective crop cuts...
Variable rate technology nitrogen (VRT-N) application, a precision management approach to synchronize N input with crop demand, has received increasing attention in recent years. Although existing field trials have suggested the agronomic and environmental feasibility of VRT-N adoption, the potential benefits at large scale remain a puzzle to farme...
The ratio of plant carbon gain to water use, known as water use efficiency (WUE), has long been recognized as a key constraint on crop production and an important target for crop improvement. WUE is a physiologically and genetically complex trait that can be defined at a range of scales. Many component traits directly influence WUE, including photo...
A better understanding of recent crop yield trends is necessary for improving the yield and maintaining food security. Several possible mechanisms have been investigated recently in order to explain the steady growth in maize yield over the US Corn‐Belt, but a substantial fraction of the increasing trend remains elusive. In this study, trends in gr...
Elevated atmospheric CO2 concentrations ([CO2]) are expected to increase C3 crop yield through the CO2 fertilization effect (CFE) by stimulating photosynthesis and by reducing stomatal conductance and transpiration. The latter effect is widely believed to lead to greater benefits in dry rather than wet conditions, although some recent experimental...
Precision nitrogen (N) management for corn has gained popularity due to both economic and environmental considerations. There is sufficient evidence demonstrating that N fertilizer efficiency can be improved by implementing sidedress and variable rate fertilization. In this paper, a crop model- and satellite imagery-based decision-support tool for...
Accurate measurements of crop production in smallholder farming systems are critical to the understanding of yield constraints and, thus, setting the appropriate agronomic investments and policies for improving food security and reducing poverty. Nevertheless, mapping the yields of smallholder farms is challenging because of factors such as small f...
