Provincial Scale Research Articles

Assessing the applicability of Fusion Landsat-MODIS data for mapping agricultural land use - A case study in An Giang Province

This study aimed to evaluate the applicability of using time-series data of spatiotemporal fusion Landsat-MODIS imagery for mapping agricultural land use in An Giang province, Vietnam. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was adopted for fusion techniques to integrate the relatively high spatial resolution of Landsat (30 meters) and frequently revisit time of MODIS (MOD09Q1, 8-days). The Maximum Likelihood Classifier (MLC) was then used to classify the land cover categories based on variations of NDVI (Normalized Difference Vegetation Index) time-series over the observation period. The overall accuracy is about 84.9%, and a kappa coefficient of K=0.7, which revealed the effectiveness of using Fusion Landsat-MODIS NDVI data in land cover classification at the provincial scale. The current of the agricultural land use was finally mapped, including seven categories, namely built-up areas (10.49%), double rice crops (4.8%), triple rice crops (68.24%), perennial tree/orchards (4.08%), annual crops (7%), water surfaces (3.07%), and forest (2.32%). The results indicate that the agricultural land use cover can be detected in detail using Fusion Landsat-MODIS imagery. The classification is dramatically higher compared to the map classified by a conventional method of solely Landsat 8 image analysis (overall accuracy of 67.3% and Kappa coefficient K=0.35). The research outcomes will support the detailed information for managers in evaluating the impact of climate change on the rice cropping system toward sustainable agriculture development.

More Reliable Baseline Estimates of Soil Organic Carbon Content Using Reinforced Density of Legacy Soil Profiles at a Provincial Scale

More Reliable Baseline Estimates of Soil Organic Carbon Content Using Reinforced Density of Legacy Soil Profiles at a Provincial Scale

Evaluating the Ability of NOAA-20 Monthly Composite Data for Socioeconomic Indicators Estimation and Urban Area Extraction

The new visible infrared imaging radiometer suite (VIIRS) onboard the National Oceanic and Atmospheric Administration-20 satellite (NOAA-20) is capable of imaging the Earth during both daytime and nighttime. The NOAA-20 VIIRS’ day/night band (DNB) enables a new generation of nighttime imaging applications. However, few studies investigated the ability of NOAA-20 DNB nighttime light data in modeling socioeconomic indicators [such as the gross domestic product (GDP) and electric power consumption (EPC)] and extracting urban areas. In this article, we first used a simple linear regression model to investigate the potential of NOAA-20 nighttime light data for estimating GDP and EPC at multiple scales; we then extracted urban areas from NOAA-20 nighttime light data by using support vector machines. Taking mainland China as the study area, we found that the correlation coefficient of determination <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> between NOAA-20 nighttime light data and GDP/EPC at both provincial and prefectural scales are higher than 0.7. By comparing the results with NPP-VIIRS nighttime light data, similar <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values were obtained at both two scales, indicating that NOAA-20 nighttime light data and NPP-VIIRS data are comparable in estimating socioeconomic indicators. Moreover, NOAA-20 also shows a similar detection ability with NPP-VIIRS in extracting urban areas. This article demonstrated that NOAA-20 and NPP-VIIRS are comparable in economic statistics estimation and urban area extraction. The NOAA-20 nighttime light data can be a useful data source for enlightening more applications in the fields of socioeconomic and urban studies.

中国航空碳排放及其效率时空演化特征分析

PDF HTML阅读 XML下载 导出引用 引用提醒 中国航空碳排放及其效率时空演化特征分析 DOI: 10.5846/stxb202102250519 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金（42071266）；第三批河北省青年拔尖人才项目；河北省自然科学基金（D2021205003） Spatio-temporal evolution of carbon emission and its efficiency in Chinese aviation Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:航空碳排放不仅影响空气质量且可造成温室效应。中国正处于从民航大国向民航强国迈进的关键时期，提高航空碳排放效率是行之有效的航空碳减排手段。运用可拓展随机性环境影响评估模型（STIRPAT）对中国2004-2019年航空碳排放总量的时空演变特征进行分析，以探明不同尺度区域航空碳排放的空间差异与空间关联表现；运用基于非期望产出的超效率松弛变量模型（SBM）和标准差椭圆分析法（SDE）对中国航空碳排放效率的时空分布与格局演化过程进行判定，以分析各省域航空碳排放效率的差异，并给出有效的航空碳减排方略。研究发现：2004-2019年，中国航空碳排放总量持续增长，航空碳排放增长率和航空碳排放强度均呈波动下降趋势；四大经济区航空碳排放总量分布总体表现为"东部 > 西部 > 中部 > 东北"的格局，东部仍是中国航空碳排放的主要区域；高碳排放区较分散，还未形成省域之间连片的碳排放高值区。2004-2019年，中国航空碳排放效率总体呈现"M"型波动上升趋势，各省域航空碳排放效率均不同程度的提高，但主要以低效率区、中效率区为主；各省域之间的航空碳排放效率差异性经历了逐渐减小到逐步增大的过程，但总体航空碳排放效率空间分布格局以南-北方向为主导。从全国、区域、省域3个尺度研究航空碳排放及其效率的时空演化特征，可辨析航空碳排放区域排放特征，有效探索区域航空碳减排的差异发展策略；对提高中国民航产业可持续发展，促进民航经济的绿色、低碳、高效发展以及推进各区域的差异化减排进程有理论指导意义。 Abstract:Aviation carbon emissions not only affect air quality but also cause greenhouse effect. China is in the critical period of transforming from a big country to a strong country in civil aviation. Improving the efficiency of aviation carbon emission is an effective means of aviation carbon emission reduction. This paper uses the Stochastic Impacts by Regression on Population, Affluence and Technology model (STIRPAT) to analyze the spatial and temporal evolution characteristics of total aviation carbon emissions in China from 2004 to 2019, to explore the spatial differences and correlation of aviation carbon emissions at different scales; The ultra-efficiency Slack Based Measure model (SBM) based on non-expected output and Standard Deviation Ellipse analysis (SDE) were used to analyze the spatial and temporal distribution and pattern evolution process of the aviation carbon emission efficiency in China, to calculate their differences in various provinces, and give effective aviation carbon reduction strategy. The research found that China's total aviation carbon emissions continued to grow from 2004 to 2019. Both of the growth rate and the intensity of aviation carbon emission showed a decreasing trend. The overall distribution of aviation carbon emissions in the four economic zones shows a pattern of "eastern China is the largest, northern China is the smallest, and western China is larger than central China". The eastern area is still the main region of aviation carbon emissions in China. The high-value regions of aviation carbon emissions are relatively scattered, and no continuous high-value regions have been formed among provinces. From 2004 to 2019, China's aviation carbon emission efficiency generally showed a "M" shaped fluctuation upward trend. Aviation carbon emission efficiency of different provinces has been improved to various levels, but mainly in low efficiency areas and middle efficiency areas. The difference of aviation carbon emission efficiency among provinces and regions has experienced a process of gradually decreasing to gradually increasing. However, the spatial distribution pattern of aviation carbon emission efficiency is dominated by south to north direction. From the national, regional, and provincial scale to study the spatial and temporal evolution characteristics of aviation carbon emission and its efficiency, we can identify the regional aviation carbon emissions characteristics, and effectively explore the differential development strategies of regional aviation carbon emission reduction. The improvement of aviation carbon emission efficiency has theoretical guiding significance for improving the sustainable development of China's civil aviation industry, promoting the green, low-carbon and efficient development of civil aviation economy, and promoting the differentiated emission reduction process of various regions. 参考文献 相似文献 引证文献

An assessment of the urban water footprint and blue water scarcity: A case study for Van (Turkey).

Today, most of the world's population faces water scarcity, while global warming, urbanization, industrialization and population increases continue to increase the severity of the pressure on water resources. Management of water resources plays a key role in the sustainability of agricultural production. The water footprint (WF) is different in comparison to other water statistics because it takes direct and indirect water consumption into account, and helps in the management of water resources. Within this context, the WF of Van province, which is Turkey's most easterly located arid region, was calculated from 2004 to 2019. The study area covers lake Van, which is Turkey's largest lake, and the Van basin with an area of 23.334 km2 and a population of 1.136.757 (2019). In the calculations, crop (WFcrop), livestock (WFlivestock), and domestic and industrial water footprints (WFdomestic+industrial) were evaluated separately, and blue and green water footprints (WFblue and WFgreen) were analyzed in detail. According to the results, the average WF of Van province was found to be 8.73 billion m3 year-1. Throughout the province, 87.6% of the WF is composed of WFcrop, 4.9% is WFlivestock and 7.5% is WFdomestic+industrial. Of the WFcrop, 62.5% depends on WFblue, i.e., freshwater. Most of the WFlivestock consisted of dairy cattle (49%) and sheep (38%). The average WFdomestic+industrial for 2004 to 2019 was 0.64 billion m3 year-1. The average per capita water footprint of Van province was found to be 889.9 m3 year-1 capita-1. In addition, the province is classified as severe water scarcity (257%). This study is one of the first province-based calculations of WF in Turkey and is the first study to bring a different aspect to published literature by including residual soil moisture from the winter months. As a result of this study, the WFblue of the WFcrop is above the worldwide average and should be reduced by changing the crop pattern or synchronizing the planting and harvest dates of the crops to a period that benefits from precipitation. In addition, this study is expected to contribute to new studies for calculating the provincial scale WF and will have positive effects on agricultural planning, water allocation and the sustainability of water resources.

Understanding the water-related risks under climate conditions in Vietnam using CMIP6 models

Completely located in the tropics, water resources availability in Vietnam is plenty but not limitless, especially in associated with unexpected climate conditions. So, the study attempts to provide fully insight into water-related risks in present and near-future using an ensemble of CMIP6 models in combination with the methods of risk and GIS-based analysis on a provincial scale of Vietnam. The results show a dominant of floods and cyclone hazards, followed by droughts, landslides and seawater intrusion observed in present. Meanwhile, under climate change scenario of SSP3-7.0 in near-future (2021-2040), an expected decreasing in precipitation by -13.6% for provinces in the north of Vietnam is illustrated. Most importantly, in spring and summer, maximum temperature can increase faster than those in autumn, winter and annual. Dealing with water-related risks, it is expected that there are 6 out of 63 provinces at very high risk level.

Multi-Objective Spatial Suitability Evaluation and Conflict Optimization Considering Productivity, Sustainability, and Livability in Southwestern Mountainous Areas of China

Space is the fundamental carrier for production, living, and ecological activities, and optimizing the spatial pattern is of vital importance to promote regional sustainable development. To achieve this goal, the core issues are to identify the risks of resource and environmental constraints of development and to realize the rational distribution of human living space. Based on the integration of multisource heterogeneous data, taking Yunnan Province, a typical mountainous area in China, as an example, this research proposes a multi-object suitability evaluation method based on 50 × 50 m grid data at the provincial scale. We build a spatial conflict analysis model to identify production–living–ecological space (PLES) and propose governance suggestions for different functional areas. The results show that (1) areas suitable for ecology make up the greatest proportion of Yunnan Province, but areas with living and ecological functions show obvious spatial complementarity; (2) areas suitable for production are restricted by steep slope, geological hazards and fragmented pattern; (3) areas suitable for living is rare, and they are mainly concentrated in the plains of central Yunnan; and (4) twenty-seven percent of area has potential spatial conflicts, among which 4.38% of the area is all suitable for production–living–ecological. The production–living advantage areas are concentrated in the central Yunnan UA (Urban agglomeration), which has a high spatial overlap. These results are expected to provide valuable insights to support comprehensive multifunctional spatial utilization and sustainable development in mountainous areas.

The current state of the vitivinicultural sector in mainland China

China's vineyard surface area accounts for the second place in the world, its grape production the first place, and its wine consumption and imports the fifth place. The vitivinicultural sector is playing an increasingly important role in the world. At the same time, vitivinicultural sector has also played an important role in poverty reduction in rural areas of China.Based on the background of the world vitivinicultural sector, it is of great significance to analyze the characteristics of China's domestic vitivinicultural sector, especially the situation of the primary, secondary and tertiary industries, to help China continue to reduce poverty in the countryside, optimize the industrial structure, and promote the integration of the three industries. At the same time, it also provides a reference for the consumption and trade of grape products between China and the world. This paper collected the authoritative statistical data of vitivinicultural sector in the world and China for the past two decades, including global national data and China’s provincial data, and analyzed the development trend of grape industries in China from the perspectives of vineyard surface area, grape production, grape use, wine production, consumption and trade in an international context. For the first time, China’s POI information of grape-related enterprises in Baidu online map was retrieved, and the spatial and temporal distribution characteristics of domestic grape industries were analyzed by using ArcGIS software. It includes the comparative analysis of grape surface area and production in different provinces, the development analysis of grape-related primary, secondary and tertiary industries, the trend analysis of grape cultivation in different provinces, and the shift analysis of industrial spatial gravity center. The result not only shows the changes of grape producing areas in China, but also tries to explore the distribution and integration of the three industries at the provincial scale in different parts of China. The future development of grape industry in 31 provinces in mainland China was predicted.

Value and Quality in the Dialectics between Human and Urban Capital of the City Networks on the Land District Scale

This contribution proposes an inter-scalar and multi-polar analysis evaluation model of the territory of the Enna district, aimed at providing a robust axiological representation of the salient aspects of the general issue of internal areas, and therefore of the set of criticalities affecting them from the perspective of the human and urban capital they express. In the prospect of investigating the relations between urban and life quality—corresponding to the “city effect”—in the territorial context of each of the 20 municipalities of the Enna district, a hierarchical descriptive-valuation model was created, which coordinates a relevant amount of information units (data) and the corresponding attributes, indicators and indices that have been turned in aggregate value judgments attributed to each administrative land unit, from the perspectives of the criteria referred to as the main forms of the territorial capital. This is a multi-dimensional valuation model based on the Multi-Attribute Value Theory. Each survey and processing is mapped with different levels of detail at the scale of municipalities, census sections and cadastral land units. The outcome of this complex process of analysis and assessment provides multiple comparisons, revealing unexpected and sometimes counter-intuitive aspects in several municipalities, some of which are characterised by innovative prospects and opportunities for redevelopment of their historic centers. Correlations between information units at the different levels of the dendrogram have also indicated interesting trends and attitudes, whose comparisons can address territorial policies on both a local and provincial scale. Furthermore, the focus on the “cities network” is here assumed and proposed as the privileged point of observation of territory and the related aspects of the quality of life.

Spatiotemporal Variations in Meteorological Disasters and Vulnerability in China During 2001–2020

Based on the Yearbook of Meteorological Disasters in China, we analyzed the spatiotemporal variations in major meteorological disaster (MD) losses at the provincial scale during 2001–2020 to determine the spatiotemporal variations in MDs and vulnerability in China. Our results suggest that the impacts of MDs, including floods, droughts, hail and strong winds (HSs), low temperature and frosts (LTFs), and typhoons, have been substantial in China. MDs in China affect an average of 316.3 million people and 34.3 million hectares of crops each year, causing 1,739 deaths and costing 372.3 billion yuan in direct economic losses (DELs). Floods and droughts affected more of the population in China than the other MDs. Fatalities and DELs were mainly caused by floods, and the affected crop area was mainly impacted by drought. The national average MD losses decreased significantly, except for DELs. The trends in the affected population and crop area were mainly caused by droughts, and the trends in fatalities and DELs were dominated by floods. Floods and typhoons showed increasing influence in the last two decades relative to other disasters. The annual mean and long-term trends in MD losses exhibited regional heterogeneity and were subject to different dominant hazards in different regions. The disaster losses and their trends in southeastern China were mainly attributed to typhoons. The affected population, crop area, and DELs were all significantly and positively correlated with exposure. The vulnerability of the population, crops, and economy tended to decrease. Economic development reduced the vulnerability of the population and economy but showed no significant influence on the vulnerability of crops. Our findings suggest that more focus should be placed on the impacts of floods and typhoons and that socioeconomic development has an important influence on the vulnerability of the population and economy. These results provide a foundation for designing effective disaster prevention and mitigation measures.

Method on site-specific source apportionment of domestic soil pollution across China through public data mining: A case study on cadmium from non-ferrous industries

The lack of emission data of major Cd-emitting enterprises has long limited the source apportionment of soil cadmium (Cd). Non-ferrous metal enterprises (NMEs) contribute the most Cd emissions in China in recent years. We estimated the cumulative Cd emission of 8750 NMEs across China through public data collection and material balance methods for the first time. The results showed that the total Cd emissions were estimated at 133,177 tons, of which 78.68% contributed by zinc primary smelting and mining. The emission hotspots are mainly concentrated in the south of the Yangtze River, such as Nanling Mountain areas, Nanpan River Basin, and Jincheng River Basin, as well as a few parts of the North and Northwest China. Then a significant positive spatial correlation was furtherly detected between NMEs and soil Cd, except for secondary smelting enterprises. Moreover, the hotspots of soil Cd pollution caused by NMEs were identified across China. By promoting the accounting calibrator from annual emission intensity of regional (mainly provincial) scale to the cumulative emission of site-specific enterprise in its entire life cycle, this study realized the finer description of the spatial heterogeneity of Cd emission from non-ferrous industry on a large scale and make it possible to refine the reliability of follow-up site-specific source apportionment, by introducing the emission intensity instead of the enterprise sites density. Finally, a modified approach for the regional source apportionment of soil pollution was proposed to obtain a more realistic and precise drawing. The results pointed out key NMEs subcategories and the affected hotspots which require continuous strengthening of Cd-related rectification. This methodological framework is expected to contribute to the precise management and differential sources control of Cd pollution and can be further extended to other pollutants for the precise targeting of key industries and hotspots during source pollution control in the future.

Quantifying ecosystem service mismatches for land use planning: spatial-temporal characteristics and novel approach-a case study in Jiangsu Province, China.

Land use and land cover changes associated with urbanization have had a significant influence on ecosystem services (ESs), but previous studies have insufficiently focused on the relationships between ES supply and demand; these relationships are seldom considered in the science-policy frameworks of land use planning. In this study, a specific supply-demand indicator was constructed to measure ES supply and demand and their disparity across multiple scales in Jiangsu Province from 2000 to 2018. High spatial heterogeneity and mismatches of ES supply and demand were found in water yield, grain production, carbon sequestration, soil conservation, heat regulation, and recreation services. At provincial scale, the supplies of carbon sequestration and heat regulation services were smaller than their demands. At the 1-km2 grid scale, the ES supply and demand mismatches in urban areas were more serious than those in surrounding areas, especially for carbon sequestration and recreation services. Five ES supply-demand risk zones were identified based on the current status and trends of all ES supply and demand. Southern Jiangsu generally had high risks of ES mismatch, which should be reduced by strategic planning. Constructing the ES supply-demand indicator is a novel practice that assists in evaluating environmental issues and integrating them into further development decisions. This paper suggests that governments should reduce ES mismatches with reference to local conditions (economic development, industrial type, and ecological carrying capacity) and the actual situation of ES supply and demand.

Remote sensing and GIS application for monitoring drought vulnerability in Indonesia: a review

Agricultural drought is one of the hydrometeorological disasters that cause significant losses because it affects food stocks. In addition, agricultural droughts, impact the physical and socio-economic development of the community. Remote sensing technology is used to monitor agricultural droughts spatially and temporally for minimizing losses. This study reviewed the literatures related to remote sensing and GIS for monitoring drought vulnerability in Indonesia. The study was conducted on an island-scale on Java Island, a provincial-scale in East Java and Bali, and a district-scale in Indramayu and Kebumen. The dominant method was the drought index, which involves variable land surface temperature (LST), vegetation index, land cover, wetness index, and rainfall. Each study has a strong point and a weak point. Low-resolution satellite imagery has been used to assess drought vulnerability. At the island scale, it provides an overview of drought conditions, while at the provincial scale, it focuses on paddy fields and has little detailed information. In-situ measurements at the district scale detect meteorological drought accurately, but there were limitations in the mapping unit's detailed information. Drought mapping using GIS and remote sensing at the district scale has detailed spatial information on climate and physiographic aspects, but it needs temporal data monitoring.

Spatiotemporal dynamic differences of energy-related CO2 emissions and the related driven factors in six regions of China during two decades.

Carbon neutrality lays out a grand blueprint for carbon emission reduction and climate governance in China. How to reduce energy consumption is the key to achieving this goal. The economic development and energy consumption show a very large gap at the provincial level, and this paper divides China into six regions (North, Northeast, East, Mid-South, Southwest, and Northwest) and analyzes the dynamic changes and reveals the driving factors that have affected CO2 emission changes from 1997 to 2017. Then, the driving forces including energy intensity, energy structure, energy efficiency, economic activity, and population scale were discussed employing the logarithmic mean Divisia index (LMDI) based on provincial panel data. The results show that CO2 emissions from energy consumption show an upward trend, from 4145 Mt in 1997 to 13,250 Mt in 2017, with an annual average growth rate of 1.06%; coal consumption is the main source of CO2 emission. The regions with the highest proportion of CO2 emissions are the East and North, which account for 50% of total emissions. China’s CO2 emissions from energy consumption, coal consumption, and output have shown significant spatial autocorrelation at the provincial scale. According to coal consumption, energy consumption CO2 emissions are divided into three stages: phase I (1997–2002), the increase in CO2 emissions in six regions was attributed to significant and positive impacts of energy intensity, economic activity, and population scale, the effects of which exceeded those of the energy structure and energy efficiency; phase II (2003–2012), the economic activity effect on CO2 emissions was highest in the East region, followed by the North and Mid-South regions; phase III (2013–2017), the East, Mid-South, and Southwest regions of China were dominated by the positive effects of energy intensity, economic activity, and population scale. The major driver of CO2 emissions is economic activity; the energy efficiency effect is an important inhibitory factor. Regional economic development and energy consumption in China are unbalanced; we conclude that differentiated emission reduction measures should be of particular concern for policymakers.

Dendrochronological Provenance Patterns. Network Analysis of Tree-Ring Material Reveals Spatial and Economic Relations of Roman Timber in the Continental North-Western Provinces

Over the last decades, Roman wood in various shapes and sizes has been excavated in the region of the continental north-western provinces of the Roman empire. However, it is often unclear whether wood has been transported. Most dendrochronological provenance studies rely on simple comparisons between tree-ring series based on a single similarity measure. In addition, most fail to consider the complex system of relations that is the result of the variables that influence tree-ring patterns. Network analysis is a solution to this problem, because it allows to both visualize and analyze the complex (provenance) relations of tree-ring series as a whole. A network makes it impossible to ignore existing (statistical) relations between tree-ring series. Although networks can be build using any (combination of) similarity measure(s), in this study a combination of the Synchronous Growth Changes (SGC), its related probability of exceedance (<em>p</em>), correlation (<em>r</em>) and overlap define the edges. This paper focusses on networks with site chronologies as nodes, although networks can also be constructed using individual tree-ring series or a combination with site chronologies. A combination of these can also help to refine the (archaeological) interpretation. The location of any tree-ring series in a network reflects its provenance. Material that is placed closer together in the network has similar growth patterns and is generally from the same region. Therefore, network communities reflect wood that has a similar provenance. If tree-ring material was found on different spatial locations, but in close proximity in the network, this indicates that wood has been moved. To determine which wood has been transported, a combination of archaeological and spatial arguments is used. The method is sound, simple and gives insight in the complexity of all tree-ring relations in a simple diagram. The resulting patterns show that most wood was obtained in the region where it was used, but that transport of wood in the Roman period did take place. Three scales are defined to describe the Roman wood economy: local, provincial and imperial. While transport of wood over long distances is attested for both military and civilian sites (provincial and imperial scale), it seems that wood that was transported beyond the provincial borders was only used in civilian sites (imperial scale). The combination of network science, dendrochronology and archaeology is a powerful method to understand patterns in the Roman timber economy.

Gross economic-ecological product accounting of Fuzhou City, China.

The gross economic-ecological product (GEEP) accounting is crucial to promote the construction of ecological civilization, and practice the ideas of "lucid waters and lush mountains are invaluable assets". GEEP accounting had been conducted at national and provincial scales, but not at urban scale. According to the economic and ecological development, the GEEP accounting framework was built in Fuzhou City. The GEEP value of Fuzhou City in 2015 and 2018 was calculated and the spatiotemporal variation was analyzed. The results showed that the GEEP value of Fuzhou City was 1208.568 billion yuan in 2015. Among which, the value of GDP and ecological regulation, and the cost of environmental degradation and ecological damage were 577.742, 636.420, 3.095 and 2.500 billion yuan, respectively. Minqing County had the highest GEEP, with a value of 170.022 billion yuan, which accounted for 14.1% of that in Fuzhou City. The lowered values were found in Fuqing City, Minhou County and Yongtai County, accounting for 12.2%, 12.1% and 10.4%, respectively. In 2018, the GEEP of Fuzhou City increased to 1445.399 billion yuan, with an increase rate of 19.6%, mainly due to the GDP increase (up by 47.4% from 2015). The highest proportions of GEEP were observed in Minqing County and Gulou District (12.0%), followed by Fuqing and Minhou counties (11.0%). Compared with 2015, the increase trends were observed for the total value of GEEP, unit area and per capita of GEEP values in Fuzhou City. The cost of environmental and ecological degradation in Fuzhou decreased by 7.2% and 12.4%, respectively, indicating that the overall ecological environment of Fuzhou was improving. The accounting of GEEP in Fuzhou could effectively make up for the shortage of GDP assessment at the urban scale in China. It could provide an instrument for Fuzhou government to formulate rational ecological civilization assessment system and promote regional sustainable development.

Temporal and spatial variations in nitrogen use efficiency of crop production in China

The low value of nitrogen use efficiency (NUE) (around 30%) of crop production in China highlights the necessity to adopt reasonable N managements in national scale. After the implementation of ‘National Soil Testing and Formulated Fertilization’ program in 2005, many field experiments have reported an increase of NUE for crop productions in China. This has prompted discussion regarding the extent to which NUE in crop production has been improved. Here, we analyzed the temporal and spatial changes in NUE (crop N uptake/total N input) and cumulative synthetic and non-synthetic N fertilizer recovery efficiency of crop production in China during 1980–2014, and evaluated the relationship between NUE and economic growth (purchasing power parity, PPP) at national and provincial scale. The results showed that the overall NUE of crop production in China clearly increased from 35 to 42% during 2003–2014, and an increase in NUE was further evidenced by increases in cumulative recovery efficiency of both synthetic and non-synthetic N fertilizer. The relationship between NUE and PPP can be described by an environmental Kuznets curve at the national scale, with NUE first decreasing then increasing with PPP. However, this relationship exhibited large spatial variation: 1) In economically developed (e.g., Guangdong and Zhejiang) and undeveloped provinces (e.g., Yunnan and Guizhou), NUE generally decreased and then remained at low levels (20–35%) as PPP increased. 2) In major agricultural provinces with high (e.g., Shandong and Jiangsu) or intermediate levels (e.g., Hunan and Hebei) of economic development, a pronounced increasing trend in NUE with PPP was observed. These results highlight the necessity of developing region-oriented N management strategies to further increase the NUE of crop production in China, particularly in the economically developed and undeveloped provinces.

The spatiotemporal patterns and pathways of forest transition in China

AbstractChina experienced a shift from net forest losses to gains (forest transition) between 1976 and 1981. Such transition has increased timber volume in natural forests and expanded the provision of forests ecosystem services. However, the timing, magnitude, and impact of the forest transition varied at provincial scales due to heterogeneous socio‐economic and institutional conditions. The aim of this study is to quantify the impact of spatial drivers of forest transition in China through integrated comparative and spatial regression methods. This approach allows the documentation of feedbacks and interactions of theoretical pathways to forest transition at different geographical scales, which is of relevance for large‐scale land restoration efforts. Our analysis also accounts for changes in forest volumes, a parameter that is usually not studied in the forest transition literature. Here, we used key indicators of demographic, economic, agricultural, and urbanization processes coupled with forest area data to investigate factors influencing forest transitions at multiple geographic scales between 1973 and 2013. Stepwise and geographically weighted regression models were adapted to quantify the key drivers' integrated and distributed magnitude effects on forest transition patterns, respectively. We assessed changes across forest types (i.e., primary and secondary forests, plantation forests) and investigated pathways to forest transition at provincial scales. The results indicate that increasing demand for timber and other forest ecosystem services, rising gross domestic product and population, forest policy, and increasing employment in the industry and service sectors generated multiple pathways to forest transition. The impact of those drivers varied within provinces, and some transition pathways were more relevant than others at sub‐national scales. Despite the Country scale shift to net forest gains, the loss of natural forests continued in some provinces (e.g., Guangdong, Guangxi) until recent years. The loss of ecosystem services from mature forests offset some of the benefits of China's forest transition. Coordinated forest management strategies across political jurisdictions could speed up the path to net forest gains, reduce trade‐offs of forest transitions processes, and achieve sustainable afforestation processes. Such an effort could have significant contributions to the preservation and increase of key forest ecosystem services for the Country and the world.

High Resolution Air Pollutant Emissions from China's Road Transport at a Provincial Scale between 2015 and 2017

High Resolution Air Pollutant Emissions from China's Road Transport at a Provincial Scale between 2015 and 2017

Evaluating the performance of LBSM data to estimate the gross domestic product of China at multiple scales: A comparison with NPP-VIIRS nighttime light data

Regional economic development evaluation is essential for understanding social and environmental issues. Although the nighttime light (NTL) data have been proved to be effective in economic estimation, it cannot reflect the human activities that occur during the daytime. Recently, with the widespread use of smart mobile devices, the location based social media (LBSM) data are increasingly being used as a proxy for real-time human activities. However, little work was carried out to explore the potential of LBSM data in estimating economic development at different scales in China. This study filled this gap by evaluating the effectiveness of Tencent user density (TUD) data, a typical type of LBSM data in China, in Gross Domestic Product (GDP) modeling at the provincial, municipal, and county scales. In this study, we employed holiday and non-holiday TUD sample data to simulate the annual TUD data, and compared it with the new generation NTL data, NPP/VIIRS images. The results showed that although the simulated annual TUD data does not perform better than NPP/VIIRS-NTL data in provincial and municipal GDP estimation, it outperforms NPP/VIIRS-NTL data at the county scale. More importantly, the simulated annual TUD data are much more powerful and reliable than NPP/VIIRS-NTL data in underdeveloped areas with complex terrain, such as the Northwest and Southwest China, as well as in more developed areas with separation of work and housing, such as the North China and South China. This is mainly because TUD data can reduce the impact of natural factors such as terrain on data collection as well as reflect both daytime and nighttime human activities. This study confirmed that the LBSM-TUD data is a potential and promising data source for economic modeling in small scale areas of China, which will help to support China's regional economic evaluation.