Li Xuecao

• Doctor of Philosophy
• Professor (Full) at China Agricultural University

Soybeans are a globally important crop, both commercially and nutritionally. Accurate mapping of soybean cultivation is essential for optimizing production and informing market strategies. However, traditional sample-driven soybean mapping algorithms often rely on extensive, representative datasets, which can limit their applicability across differ...

Accurate regional mapping of soil organic carbon (SOC) in croplands is essential for assessing soil carbon sequestration potential. However, accurate SOC mapping of cropland at a regional scale is challenging due to numerous natural and anthropogenic management factors. The impact of covered crop residue remains under-valued when mapping surface SO...

Africa is set to drive future global urbanization, yet the evolution of its urban systems remains underexplored. Here we show this evolution during 1950–2020 using three urban system rules based on a unified urban definition across the African continent. Zipf’s law quantified increasing population concentration in large cities, leading to a shift f...

Background China's growth over recent decades rapidly transformed the urban landscapes. Green spaces provide numerous health benefits including acting as nature-based solutions for climate change risks. Our study aims to track greenness trends in urban areas in China and quantify the health impact of greenness on adult mortality. Methods In China,...

Satellite-derived solar-induced chlorophyll fluorescence (SIF) offers valuable opportunities for monitoring large-scale ecosystem functions. However, the inherent trade-off between satellite scan range and spatial resolution, along with incomplete spatial coverage and irregular temporal sampling, limits its broader application. In this study, we de...

Cities in the Global South face dual pressures from intensifying heat stress and widespread urban browning. However, the specific trends in urban heat stress across these cities, alongside those induced by urban browning, remain inadequately quantified, hampering effective urban planning and intervention strategies. Here we present a data-driven me...

Understanding the complex relationships between humans and nature is crucial for achieving global sustainability and enhancing human welfare. China, with its vast population, stark human-nature contradictions, and considerable regional disparities, currently lacks grid-scale research methodologies and practices. We utilized the Human Footprint (HF)...

Recently, solar-induced chlorophyll fluorescence (SIF) from satellites has shown potential for evaluating vegetation status and stress responses. Fluorescence quantum yield (Φ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub>) is essentially linked to vegetation stress. However, the complex physio...

In the last two decades, rapid corn expansion has significantly impacted local and regional climates in Northeastern China. However, its climatic effects and underlying biophysical mechanisms have rarely been investigated, particularly in accurately describing the changes in surface physiological structure throughout different phenological stages....

Urban building height, as a fundamental 3D urban structural feature, has far-reaching applications. However, creating readily available datasets of recent urban building heights with fine spatial resolutions and global coverage remains a challenging task. Here, we provide a 150-m global urban building heights dataset around 2020 by combining the sp...

Understanding urban vertical structures, particularly building heights, is essential for examining the intricate interaction between humans and their environment. Such datasets are indispensable for a variety of applications, including climate modeling, energy consumption analysis, and socioeconomic activities. Despite the importance of this inform...

Public release of the entire Landsat data archive and cloud-based geocomputation platforms have greatly facilitated land-cover mapping worldwide. The acquisition of training samples presents a significant challenge in mapping. In this study, we have developed an approach based on transfer learning to creatively use existing global land-cover produc...

Accurate yield prediction is essential for global food security and effective agricultural management. Traditional empirical statistical models and crop models face significant limitations, including high computational demands and dependency on high-resolution soil and daily weather data, that restrict their scalability across different temporal an...

Nearly a third of the world's population suffers from pollen-induced respiratory allergies—and the number is rising. For those affected, the situation is becoming more stressful every year with climate change, rising atmospheric CO2 levels, and urbanization. These phenomena form a complex interface between human health and global change, yet the cr...

For many applications, raw satellite observations need to be converted to high-level products of various essential environmental variables. While numerous products are available at kilometer spatial resolutions, there are few global products at high spatial resolutions (10-30 m), which are also referred to fine or medium resolutions in the literatu...

Synthetic aperture radar (SAR) records important information about the interaction of electromagnetic waves with the Earth’s surface. However, long-term and high-resolution backscatter coefficient data are still lacking in many urban studies (e.g., building height estimation). Here, we proposed a framework to reconstruct the 1-km backscatter coeffi...

Understanding urban vertical structures, particularly building heights, is essential for examining the intricate interaction between humans and their environment. Such datasets are indispensable for a variety of applications, including climate modeling, energy consumption analysis, and socioeconomic activities. Despite the importance of this inform...

Urban warming significantly advances spring vegetation phenology. However, the potential effect of daytime and nighttime warming on the start of the urban vegetation growing season (SOS) remains to be determined. Here, we characterized the interannual response of SOS to daytime and nighttime warming from 2003 to 2020 using remotely sensed phenologi...

Tracking long-term tidal flat dynamics is crucial for coastal restoration decision making. Accurately capturing the loss and gain of tidal flats due to human-induced disturbances is challenging in the micro-tidal areas. In this study, we developed an automated method for mapping the annual tidal flat changes in the micro-tidal areas under intense h...

Urban modelers have long interpreted urban growth as a coupled evolution of two processes, namely spontaneous and self-organized processes. However, most scholars have always paid attention to the exploration of the driving mechanisms of the spontaneous process. While for the self-organized process, most simulations based on cellular automata (CA)...

Corn is the dominant crop planted in Northeast China, and its accurate and timely mapping is important for food security and agricultural management in China. However, the absence of enough labels is challenging for corn accurate mapping in a regional area using machine learning methods or deep learning methods. In this study, an efficient way of a...

The Russia–Ukraine War is impacting global food systems, which may trigger global cropland expansion and consequently lead to biodiversity loss far from war zones. To quantify such impacts on biodiversity, we simulated the global cropland expansion provoked by the reshaping of international virtual cropland flows under different war scenarios and c...

Crop residue cover plays a key role in the protection of black soil by covering the soil in the non-growing season against wind erosion and chopping for returning to the soil to increase organic matter in the future. Although there are some studies that have mapped the crop residue coverage by remote sensing technique, the results are mainly on a s...

A R T I C L E I N F O Keywords: Spring vegetation phenology urbanization urban heat island effect climates rural-urban ecosystem A B S T R A C T Cities have been considered ideal surrogates for evaluating ecological responses to climate warming. Although research has revealed that the urban heat island effect is not the only determinant that drives...

Urban renewal planning and development are vital for enhancing the living quality of city residents. However, such improvement activities are often expensive, time-consuming, and in need of standardization. The convergence of remote sensing technologies, social big data, and artificial intelligence solutions has created unprecedented opportunities...

The intensified thermal environment in suburban areas is raising wide concerns for human society and public health due to rapid urbanization. Although the satellite-derived surface urban heat island intensity (SUHII) is a commonly used indicator, it still needs to be determined the SUHII between urban and suburban areas due to the challenges in del...

The global carbon dioxide (CO) concentration has shown a consistent and substantial increase over the years, representing the dominant component of greenhouse gases (GHGs). Hence, there is an urgent demand to accurately quantify a broad spectrum of CO concentration at a fine-scale level to aid policymakers in making informed decisions. Consequently...

Solar-induced chlorophyll fluorescence (SIF) shows potential in exploring plant responses to environmental changes caused by extreme climatic factors. However, how to accurately assess climate stresses (especially the low-temperature stress) suffered on crops at the regional scale in a systematic approach has not been extensively explored. In this...

Building height dataset is crucial in urban studies, holding significant importance in understanding the interactions of human activities and the built-up environment. However, high-resolution three-dimensional building datasets covering large areas are limited. A rapid and accurate method for revealing fine-scale urban morphology is required. In t...

Living spaces are a crucial component of communities and social interactions, whereas the vertical structure of buildings in these spaces, particularly at a large-scale, has received limited attention yet. Here, we produced a detailed height map of each building in the conterminous United States (US) in circa 2020. Leveraging multi-source satellite...

Extracting building construction time is crucial for effective land resource management and sustainable urban development, particularly in fast-growing urban areas. However, acquiring building construction time remains challenging due to limited observations with multiple changes. To address this issue, we applied a monthly time series of remote se...

Nighttime light (NTL) remote sensing data plays a crucial role in comprehending changes in human activities. The availability of the daily lunar BRDF-corrected Black Marble NTL product (VNP46A2) enables the use of NTL data to detect and assess the impact of short-term emergencies. However, daily NTL data often experience missing values due to cloud...

Allometric urban scaling law quantifies disproportional relationships between urban indicators and city size, which has been reported across developed countries and parts of the global south, but its applicability in Africa is neglected. Here, taking built-up areas derived from remote sensing in more than 7000 African agglomerations in 2015 as exam...

Characterizing urban environments with broad coverages and high precision is more important than ever for achieving the UN's Sustainable Development Goals (SDGs) as half of the world's populations are living in cities. Urban building height as a fundamental 3D urban structural feature has far-reaching applications. However, so far, producing readil...

The continuous dynamic of surface urban heat island (SUHI) effect is highly needed in urban climate studies. However, temporal variations of SUHI intensity (SUHII) have been understudied in previous studies owing to the lack of spatially seamless and temporally continuous land surface temperature (LST) data, particularly in urban domains. Also, the...

Understanding the distribution and land history of old urban areas (OUAs) and renewed urban areas (RUAs) has become the key point of urban management. However, it is hard to acquire adequate information for lack of pertinent detection methods. Here, we established a complete mapping framework on Google Earth Engine (GEE) platform to identify OUAs a...

Human activities have placed significant pressure on the terrestrial biosphere, leading to ecosystem degradation and carbon losses. However, the full impact of these activities on terrestrial biomass carbon remains unexplored. In this study, we examined changes in global human footprint (HFP) and human-induced aboveground biomass carbon (AGBC) loss...

The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by global urbanization and climate change. Although future dynamics of urban extent were commonly modeled with conversion from non-urban to urban extent using cellular-automata (CA)-based models, gradual changes of i...

The dynamics of built-up height are a crucial aspect of urban form, enabling the characterization of urban growth patterns and the attainment of sustainable development goals. While past studies have focused on urban extent mapping, little has been done to reveal changes in vertical structures in built-up areas. In this study, we reconstructed annu...

Accurate land surface reflectance plays an important role in the accurate inversion of surface parameters, and atmospheric correction plays a decisive role in obtaining accurate reflectance. For GF-1 WFV and GF-6 WFV images, there are two major issues to be addressed, including the spectral differences between nadir with far off-nadir pixels and th...

Land surface phenology (LSP) is beneficial to understand ecosystem response to climate change, vegetation and crop type discrimination, and ecological modeling. However, the existing efforts based on coarse resolution data (≥500 m) cannot perform well in regions with higher spatial heterogeneity and multi-cropping system, such as China. Given that...

The world is transitioning to renewable energy, with photovoltaic (PV) solar power being one of the most promising energy sources. Large-scale PV mapping provides the most up-to-date and accurate PV geospatial information, which is crucial for planning and constructing PV power plants, optimizing energy structure, and assessing the ecological impac...

Crop residue cover is vital for reducing soil erosion and improving soil fertility, which is an important way of conserving tillage to protect the black soil in Northeast China. How much the crop residue covers on cropland is of significance for black soil protection. Landsat-8 and Sentinel-2 images were used to estimate corn residue coverage (CRC)...

The crop model data assimilation approach has been acknowledged as an effective tool for monitoring crop growth and estimating yield. However, the choice of assimilated variables and the mismatch in scale between remotely sensed observations and crop model-simulated state variables have various effects on the performance of yield estimation. This s...

Data assimilation has been demonstrated as the potential crop yield estimation approach. Accurate quantification of model and observation errors is the key to determining the success of a data assimilation system. However, the crop growth model error is not fully taken into account in most of the previous studies. The objective of this study is to...

Northeast China is one of the most major grain banks in China and has an overwhelming influence on food security. To mitigate the challenges caused by increasing food demands and soil protection, crop rotation and fallowing policies have been introduced in Northeast China. These soil protection policies change annual crop planting area and crop dis...

In July 2021, a flooding event, which attracted the attention of the whole country and even the world, broke out in Henan, resulting in dramatic losses across multiple fields (e.g., economic and agricultural). The basin at the junction of Hebi, Xinxiang, and Anyang was the most affected region, as the spread of water from the Wei river submerged su...

The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by global urbanization and climate change. Although future dynamics of urban extent were commonly modelled with conversion from non-urban to urban using cellular automata (CA) based models, gradual changes of impervi...

Efficient, fast, and accurate crop lodging monitoring is urgent for farmers, agronomists, insurance loss adjusters, and policymakers. This study aims to explore the potential of Chinese GF-1 PMS high-spatial-resolution images for corn lodging monitoring and to find a robust and efficient way to identify corn lodging accurately and efficiently. Thre...

The cellular automata (CA) based models have been extensively used in urban sprawl modeling to support sustainable urban planning. However, in most existing urban CA models, only abrupt conversion (i.e., from non-urban to urban) was considered, whereas the difference in urbanization levels among different grids, as well as the nature of continuous...

Accurate and timely monitoring of flooded crop areas is crucial for disaster rescue and loss assessment. However, most flooded crop monitoring methods based on synthetic aperture radar (SAR) imagery were developed for rice, which is probably inappropriate for crops with complex canopy structures that strongly attenuate SAR signals. Additionally, th...

Against rapid development in urban areas, timely urban land cover changes (ULCC) information is beneficial for understanding the urban environment and promoting sustainable development. To realize real-time urban land cover change detection, high-frequency remotely sensed data are urgently needed. In this study, we tested the detection capability o...

Smallholder agriculture is the bedrock of the food production system in sub-Saharan Africa. Yields in Africa are significantly below potentially attainable yields for a number of reasons, and they are particularly vulnerable to climate change impacts. Monitoring of these highly heterogeneous landscapes is needed to respond to farmer needs, develop...

Accurate and timely mapping of essential urban land use categories (EULUC) is vital to understanding urban land use distribution, pattern, and composition. Recent advances in leveraging big open data and machine learning algorithms have demonstrated the possibility of large-scale mapping of EULUC in a new cost-effective way. However, they are still...

The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultura...

Information on urban built-up infrastructure is essential to understand the role of cities in shaping environmental, economic, and social outcomes. The lack of data on built-up heights over large areas has limited our ability to characterize urban infrastructure and its spatial variations across the world. Here, we developed a global atlas of urban...

Accurate and timely maize yield monitoring from satellite imagery is in great demand in developing countries. The spatial heterogeneity deprived of the large territory of China makes it a challenge. In this article, we developed a novel deep learning model for maize yield prediction at the county level based on multiple satellite data. The two-stag...

Assessing crop lodging at the regional scale is an important requirement for breeding lodging-resistant varieties and harvest planning. Accurately and continuously estimating crop lodging area from remote sensing data remains challenging due to the high randomness scattering signal of SAR images and the insufficient number of applicable optical ima...

Accurate and timely crop yield prediction over large spatial regions is critical to national food security and sustainable agricultural development. However, designing a robust model for crop yield prediction over a large spatial region remains challenging due to inadequate surveyed samples and an under-development of deep-learning frameworks. To t...

Assessing crop lodging at the regional scale is an important requirement for breeding lodging-resistant varieties and harvest planning. Accurately and continuously estimating crop lodging area from remote sensing data remains challenging due to the high randomness scattering signal of SAR images and the insufficient number of applicable optical ima...

Accurate mapping of winter wheat in its early stages is crucial for crop growth monitoring and crop yield forecasting. However, early mapping of winter wheat using remotely sensed data is challenging because remote sensing observations can only be used for a part of the growth period. In this study, a framework was proposed for early season mapping...

Crop growth models are powerful tools for predicting crop growth and yield. Gross primary production (GPP) is a major photosynthetic flux that is directly linked to crop grain yield. To better understand the potential of GPP for regional crop yield estimation, in this study, a novel crop data-model assimilation (CDMA) framework was proposed that as...

Most intensive human activities occur in lowlands. However, sporadic reports indicate that human activities are expanding in some Asian highlands. Here we investigate the expansions of human activities in highlands and their effects over Asia from 2000 to 2020 by combining earth observation data and socioeconomic data. We find that ∼23% of human ac...