Tao ye

Beijing Normal University | bnu · Institute of Disaster Risk Science Faulty of Geographical Science

Climate change affects the spatial and temporal distribution of crop yields, which can critically impair food security across scales. A number of previous studies have assessed the impact of climate change on mean crop yield and future food availability, but much less is known about potential future changes in interannual yield variability. Here, w...

Global warming can have positive or negative impacts on society depending on sectors and changes in climate impact drivers, resulting in opportunities or risks. The same holds true for social-economic changes. However, past research has mostly focused on assessing risks, leaving potential opportunities under-addressed. Here, we simulated the impact...

Understanding the impacts of climate extremes on crop yields is critical for climate change adaptation and agricultural risk management. Excessive wetness is known to cause substantial damage to maize yields, but the heterogeneous impacts on yields based on growing stage, regional climate, and management practices are not well researched; additiona...

Understanding how crop phenology responds to climate change is critical for enabling agricultural adaptation measures. Pre‐season temperature alone leads to well‐understood changes in crop phenology. Nevertheless, the modulation effect of concurrent precipitation extremes on the response to temperature extremes has been largely under‐addressed. Her...

Incorporating seasonality into livestock spatial distribution is of great significance for studying the complex system interaction between climate, vegetation, water, and herder activities, associated with livestock. the Qinghai-tibet Plateau (QtP) has the world’s most elevated pastoral area and is a hot spot for global environmental change. This s...

China is the world’s second-largest maize producer, contributing 23% to global production and playing a crucial role in stabilizing the global maize supply. Therefore, accurately mapping the maize distribution in China is of great significance for regional and global food security and international cereals trade. However, it still lacks a long-term...

Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. However, there is no high-resolution map of rice covering all of China. This study developed a new rice-mapping method by combining optical and synthetic aperture radar (SAR) images in cloudy areas based on the time-weighted dynamic ti...

Understanding the impact of climate change on year-to-year variation of crop yield is critical to global food stability and security. While crop model emulators are believed to be lightweight tools to replaces the models per se, few emulators have been developed to capture such interannual variation of crop yield in response to climate variability....

Machine learning algorithms are a frequently used crop classification method and have been applied to identify the distribution of various crops over regional and national scales. Previous studies have underscored that the number of training samples strongly influences the classification accuracy of machine learning algorithms, resulting in extensi...

Understanding the heterogeneous preferences of individuals for disaster insurance attributes is critical for product improvement and policy design. In an era of global environmental change, the Qinghai-Tibet Plateau is a hotspot of natural hazards. Improving the capability of rural housing disaster insurance to foster local residents’ disaster resi...

Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. However, there is no high-resolution map of rice covering all of China. This study developed a new rice mapping method by combining optical and synthetic aperture radar (SAR) images in cloudy areas based on the time-weighted dynamic ti...

Introduction: Using satellite data to identify the planting area of summer crops is difficult because of their similar phenological characteristics. Methods: This study developed a new method for differentiating maize from other summer crops based on the revised time-weighted dynamic time warping (TWDTW) method, a phenology-based classification met...

Accurate mapping of crop types globally is essential for maintaining food security. In recent years, with the continued launch of the earth observation (EO) satellites, the freely accessible EO data with the high spatial–temporal resolution has made it possible to achieve crop type mapping at a finer scale. However, the difficulty of crop type mapp...

The COVID-19 pandemic has brought huge challenges to sustainable urban and community development. Although some recovery signals and patterns have been uncovered, the intra-city recovery process remains underexploited. This study proposes a comprehensive approach to quantify COVID-19 recovery leveraging fine-grained human mobility records. Taking W...

As the second largest producer of maize, China contributes 23% of global maize production and plays an important role in guaranteeing maize markets stability. In spite of its importance, there is no 30 m spatial resolution distribution map of maize for all of China. This study used a time-weighted dynamic time warping method to identify planting ar...

Understanding the changes in the frequency and intensity of compound agroclimatic extremes is important for studying the resilience of the food system under anthropogenic warming. However, the spatiotemporal variation of compound agroclimatic extremes for specific crops, and the performance of the Coupled Model Intercomparison Project Phase 6 (CMIP...

Spatially explicit crop yield datasets with continuous long-term series are essential for understanding the spatiotemporal variation of crop yield and the impact of climate change on it. There are several spatial disaggregation methods to generate gridded yield maps, but these either use an oversimplified approach with only a couple of ancillary da...

COVID-19 pandemic has brought huge obstacles to sustainable cities and communities. Roads to build back from this disaster are attracting global attention. Although some recovery signals are being currently uncovered, detailed intra-city observations, especially with a complete process, are still limited. Herein, we propose a comprehensive framewor...

Risk of crop yield under climate change refers to the potential changes in crop yield (mean yield, interannual yield variability, and lower extreme yield) caused by climate change.

Satellite-based models have tremendous potential for monitoring crop production because satellite data can provide temporally and spatially continuous crop growth information at large scale. This study used a satellite-based vegetation production model (i.e., eddy covariance light use efficiency, EC-LUE) to estimate national winter wheat gross prim...

Although China is the largest producer of rice, accounting for about 25% of global production, there are no high-resolution maps of paddy rice covering the entire country. Using time-weighted dynamic time warping (TWDTW), this study developed a pixel- and phenology-based method to identify planting areas of double-season paddy rice in China, by com...

China is one of the most storm surge-prone countries in the world. Estimation of the inundation caused by the probable maximum storm surge (PMSS) is an important facet in the design of key structures (such as coastal nuclear plants) and provides a scientific basis for the planning of storm surge mitigation schemes. In this study, we propose a metho...

Crop rotations, the farming practice of growing crops in sequential seasons, occupy a core position in agriculture management, showing a key influence on food security and agro-ecosystem sustainability. Despite the improvement in accuracy of identifying mono-agricultural crop distribution, crop rotation patterns remain poorly mapped. In this study,...

China is among the countries most severely affected by storm surge disasters, with substantial economic losses and human casualties inflicted on its coastal areas. Computing inundation from storm surges for various typical return periods (TRPs) can serve as the scientific basis for preparing evacuation maps kin the case of storm surge disasters, co...

Oxygen (O 2 ) is the most abundant molecule in the atmosphere after nitrogen. Previous studies have documented that oxygen concentration remains nearly constant (20.946%) at all altitudes. Here we show for the first time that oxygen concentration varies significantly from earlier consensus and shows strong spatial and seasonal differences. Field ob...

More than a year after its appearance and still rampant around the world, the COVID-19 pandemic has highlighted tragically how poorly the world is prepared to handle systemic risks in an increasingly hyper-connected global social-ecological system. The absence or clear inadequacy of global governance arrangements and mechanisms is painfully distinc...

The oxygen concentration in near-surface air, which has been previously documented to be nearly constant (~20.946%), varies due to photosynthesis, respiration, and combustion processes, including combustion of fossil fuels. As the biggest and highest plateau in the world, the Qinghai-Tibet Plateau (QTP) hosts the largest high altitude population an...

Estimating flood impacts on daily activities is vital to disaster risk reduction and urban resilience. Human mobility on complex road networks has caused citizens, especially automobile commuters, to suffer from remarkable impacts on rainy days. However, quantitative studies of these harms have been limited. In this paper, we develop a new approach...

There has been increasing interest in understanding climate change impacts on crop yield stability, including interannual yield variability and lower yield extremes, in addition to mean yield. In this study, we evaluated these impacts on wheat yield and investigated the contribution of changes in climate mean and variability, and their interaction,...

In this article, we recall the United Nations’ 30-year journey in disaster risk reduction strategy and framework, review the latest progress and key scientific and technological questions related to the United Nations disaster risk reduction initiatives, and summarize the framework and contents of disaster risk science research. The object of disas...

A bias-corrected dataset containing daily meteorological data over the Qinghai-Tibet Plateau has been generated using a trend-preserving bias correction, the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) approach, with a high-quality gridded meteorological dataset based on ground observations (CN05.1). The dataset contains daily bia...

Quantitative vulnerability relationships describing the susceptibility of socioeconomic losses in response to climate change are critical for natural disaster loss modeling and risk assessment. Modeling such vulnerability requires methods capable of handling complicated multi-factor, non-linear, and interactive relationships. Here, we compared the...

Satellite-based models are important tools for monitoring regional and global crop yields, because remotely sensed data is able to offer temporally and spatially continuous crop growth information over large areas. However, tracking inter-annual variability in crop yields remains a major challenge. Taking this challenge, a light use efficiency mode...

Crop phenology changes are important indicators of climate change. Climate change impacts on crop phenology are generally investigated through statistical analysis of the relationship between growth period length and growth period mean temperature. However, growth periods may be either earlier or later in a given year; hence, changes in mean temper...

Understanding risk using quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment (PRA) model for livestock snow disasters in the Qinghai–Tibetan Plateau (QTP) region and derives risk a...

We evaluate the performance of area yield crop insurance (AYCI) and farm yield crop insurance (FYCI) using farm‐level yield data from China, focusing on their effects on farmers' welfare, and their cost‐effectiveness in terms of government subsidy. Given a subsidy rate sufficient to generate a politically acceptable participation level, the price a...

This data set contains a small sample data of livestock snow disasters in the Qinghai-Tibetan Plateau, including historical loss, snow hazard measures, during disaster temperature and wind speed, and pre-disaster summer vegetation condition. This data set can be used to test/verify the method used in the method in the corresponding article publishe...

Diagnosing all components of risk is essential in earthquake loss attribution science, but quantitative estimates on how sensitive the earthquake-induced direct economic losses (DELs) are to changes in hazard, exposure and vulnerability is rarely known. Here the relationship between earthquake DELs and earthquake magnitude (Ms), asset value exposur...

Studies have reported that economic development can contribute to reducing vulnerability to natural hazards. However, there exist considerable variations in the association between economic growth and vulnerability, especially at the sub-country scale. Based on climatic hazard impact (indicated by mortality and direct economic losses (DEL)) and eco...

Oxygen (O2) is essential for physiological activity in humans. On the Qinghai-Tibetan Plateau, with an average altitude of more than 4 km, hypoxia can seriously damage local residents’ health, especially the respiratory system. When an organism cannot fully compensate for insufficient physiological function caused by hypoxia, acute and chronic moun...

Understanding risk using a quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment model for livestock snow disasters in the Qinghai-Tibetan Plateau (QTP) region and derives risk asses...

Background: Many studies have reported an increased mortality risk from heat waves comparing with non-heat wave days. However, how much the mortality rate change with the heat intensity-vulnerability curve-is still unknown. Such unknown information makes the related managers impossible to assess scientifically life losses from heat waves, conseque...

Livestock snow disaster occurs widely in Central-to-Eastern Asian temperate and alpine grasslands. The effects of snow disaster on livestock involve a complex interaction between precipitation, vegetation, livestock, and herder communities. Quantifying the relationship among livestock mortality, snow hazard intensity, and seasonal environmental str...

The original publication was published without Acknowledgments section. The missing section is printed here.

The complexity of social-ecological systems (SES) is rooted in the outcomes of node activities connected by network topology. Thus far, in network dynamics research, the connectivity degree (CND), indicating how many nodes are connected to a given node, has been the dominant concept. However, connectivity focuses only on network topology, neglectin...

Purpose Understanding farmers’ preferences for crop insurance attributes is crucial in designing better insurance products and guiding government policies but such research is lacking, particularly in developing countries. The paper aims to discuss these issues. Design/methodology/approach This study uses a survey featuring a discrete choice exper...

Index-based agricultural insurance is of particular importance for vast, less heterogeneous and sparsely populated regions. This paper has designed an index-based livestock insurance for managing snow disaster risk for the pastoral regions of Eastern Inner Mongolia, China. Based on detailed information from field surveys, the designed insurance pla...

The contribution of factors including fuel type, fire-weather conditions, topography and human activity to fire regime attributes (e.g. fire occurrence, size distribution and severity) has been intensively discussed. The relative importance of those factors in explaining the burn probability (BP), which is critical in terms of fire risk management,...

Percentage of ignitions recorded by cause. *“Grave visits” means the Chinese tradition of burning paper or incense at grave sites. (TIF)

Historical monthly ignition frequency. (TIF)

Additional estimation results using generalized adding models in fitting fire frequency and size. (PDF)

The number of simulated ignitions. Simulated ignitions are shown as number of ignitions in 10,000 years. (TIF)

Cumulative distribution functions of historical fire size and simulated fire size. (TIF)

Minimal sample data set of the study. (Arcmap.shp file) (RAR)

Historical ignitions. (TIF)