[Spatio-temporal Evolution of Drought and Its Impact on Key Resources in the Important Ecological Functional Area: A Case Study in the Yellow River Basin].

This study explored the characteristics of spatial and temporal changes in drought in the Yellow River Basin from 2001 to 2020 based on TVPDI, surface runoff, vegetation net primary productivity, and grain yield data. Further, the effects of drought on water resources, grain resources, and vegetation resources were also analyzed using data spatialization methods, slope trend analysis, and Pearson correlation analysis. The results showed that:① The spatial distribution of drought in the Yellow River basin was stepped from southeast to northwest, and 60.6 % of the basin was in drought. The overall trend of drought in the basin was decreasing annually, and 94 % of the basin was gradually changing from drought to wet conditions, and the trend of drought from spring to winter decreased first and then increased. ② From the spatial and temporal changes in important resources in the basin, 53 % of the key surface runoff areas showed an increasing trend and were mainly located in the southwest of the basin; the net primary productivity (NPP) of vegetation and grain yield of food resources also showed an increasing trend. ③ Drought and the three types of resources showed significant spatial correlations, and the higher the degree of drought, the more significant the effects on surface runoff, vegetation productivity, and grain yield. However, the important resources in areas that had become wetter in recent years had not increased significantly, which indicated that the effects of drought on the three types of important resources had a time lag, and their lags had significant differences in spatial distribution and geographical differentiation patterns. This study has important theoretical implications for agricultural production, drought mitigation, and ecological conservation in the Yellow River Basin.

Characteristics of carbon budget based on energy carbon emissions and vegetation carbon absorption.

How to evaluate the change characteristics of energy carbon emissions (ECE) and vegetation carbon absorption (VCA) by scientific methods is particularly important for achieving carbon peak by 2030 and carbon neutrality by 2060. Based on provincial-level energy consumption data, nighttime light data, and population data, this study realized spatial simulation of energy carbon emissions and analyzed the change characteristics of energy carbon emissions (ECE) and vegetation carbon absorption (VCA) combined with the net primary productivity (NPP)of vegetation. Besides, the relationship between energy carbon emissions, vegetation carbon absorption, and economic development was also analyzed at an urban scale. The results showed that (1) the total ECE increased from 4.34 billion tons in 2000 to 14.43 billion tons in 2019, but the growth rate of ECE decreased from 15.9% during 2000-2010 to 3.1% during 2010-2019. The VCA capacity has been increasing year by year. In 2019, it could absorb 1.56 billion tons more carbon dioxide than in 2000 with an increase of 16.1%. (2) Through the identification of the increasing and decreasing regions of ECE and VCA, it was found that the continuous rise area of ECE accounts for 0.5% of the study area; the area of fluctuating rise accounted for 6.7% of the study area. The area of continuous decline of VCA accounted for 0.2% of the study area; the area of fluctuating decline accounted for 49.6% of the study area. (3) The eastern China accounted for 42% of ECE and 17% of VCA with 11.4% of land, while the western region accounted for 26% of ECE and 55% of VCA with 66.6% of land, which indicated that there were significant differences in the characteristics of carbon budget between the eastern China and the western region. (4) The carbon pressure index (CPI) of most cities was on the rise, but the carbon efficiency index (CEI) was also on the rise, and cities were developing towards the model of low energy consumption and high output value. In a word, the growth rate of ECE is slowing down, and the VCA capacity is increasing. In the process of promoting carbon neutrality, we should be aware of the different resource endowments of different regions, realize the actual role of each region in carbon neutrality and economic development, and allocate carbon neutrality tasks differently.

A comprehensive drought index based on spatial principal component analysis and its application in northern China.

In the background of the greenhouse effect, drought events occurred more frequently. How to monitor drought events scientifically and efficiently is very urgent at present. In this study, we employed the Vegetation Water Supply Index (VSWI), Temperature Vegetation Drought Index (TVDI), and Crop Water Stress Index (CWSI) as individual variables to construct a composite drought index (CDI) using spatial principal component analysis (SPCA). The validity of CDI was assessed using gross primary productivity (GPP), soil moisture (SM), Standardized Precipitation Evapotranspiration Index (SPEI), and Vegetation Condition Index (VCI). CDI was subsequently used for drought monitoring in northern China from 2011 to 2020. The results showed that (1) at a 99% confidence level, the Pearson correlation coefficients between CDI and GPP was 0.72, while the value between CDI and SM was 0.69, which indicated the relationship between SM, GPP, and CDI was significant. (2) We compared CDI with other variables such as Standardized Precipitation Evapotranspiration Index (SPEI) and Crop Drought Index (CDI) and found that the monitoring result of CDI was more sensitive, which indicated that the proposed CDI had a better effect in local drought monitoring. (3) The results of CDI showed that the drought status in the northern region during 2011-2020 lasted from March to October, and the high severe drought period generally occurs in March-May and September-October, with low severe drought in June-August.

Optimal allocation for land in an arid inland basin in northwest China: framework and application based on CLUE-S and MCR models.

Reasonable planning of the limited land resources can promote the coordinated development of social economic and ecological protection. It is very important to optimize the rational distribution of land resources in the arid inland river basin because of the scarce land. In this paper, the GIS technologies of spatial analysis, conversion of land use, and its effects at small regional extent (CLUE-S) and minimum cumulative resistance (MCR) model were used to optimize the land allocation. The ecological security pattern (ESP) was constructed through using MCR model, which included ecological source and resistance surface. The dynamics of land use and spatial optimizing allocation of Shiyang River Basin in 2025 and 2030 was simulated under three different optimization scenarios including farmland protection scenario (FPS), free development scenario (FDS), and ecological security pattern scenario (ESPS). It was found that under ESPS, farmland was reduced, but woodland, grassland, and water body were increased significantly. Under FPS, land for construction was controlled effectively, a large part of homestead was converted into farmland, and the potential of unused land was developed vigorously. Furthermore, the current FDS and macro policy guidance should be comprehensively considered. The ESPS was more suitable for the scientific development of Shiyang River Basin on a long view. The combination of CLUE-S and MCR can effectively improve the optimization methods under ecological process and ecological resistance of landscape elements.

[Changes in Land Use Carbon Emissions and Coordinated Zoning in China].

Carbon emissions from land use changes have become one of the main sources of regional carbon emissions. In order to explore its changes, based on the MCD12Q-LUCC data of MODIS from 2001 to 2019 using the carbon emission coefficient method, clustering, and outlier analysis method, the spatial characteristics of land use carbon emissions in various provinces in China in the past 19 years were discussed from the perspectives of carbon emission economy contributive coefficient, carbon ecological support coefficient, and their coupling and coordination relationship. The results showed that:① from 2000 to 2019, the national land use carbon emissions increased significantly; however, after 2011, the growth rate of carbon emissions became flat, whereas the growth of carbon sinks was relatively slow, and the gap between the two was still large. ② Clustering and outlier analysis showed that during the study period, the high-value agglomeration centers of land use carbon emissions in various provinces and cities across the country shifted from Guangdong, Jiangsu, and other provinces to Hebei, Shanxi, Inner Mongolia, and other provinces, and the agglomeration status became increasingly obvious. ③ The economy contributive coefficient of carbon emissions in all provinces and cities across the country had the spatial characteristics of being high in the south and low in the north, and the ecological support coefficient gradually developed from high in the west to low in the east, followed by that in the north, and the coupling coordination between the two showed a downward trend. ④ Based on the economy contributive of carbon emissions and carbon ecological support, this study divided the provinces into four categories:low-carbon maintenance area, economic development area, carbon sink development area, and comprehensive optimization area. We also put forward our own development suggestions, striving to achieve carbon neutrality and low-carbon sustainable development.

A new drought index and its application based on geographically weighted regression (GWR) model and multi-source remote sensing data.

Drought is the most widespread natural disaster in the world. How to monitor regional drought scientifically and accurately has become a hot topic for many scholars. In this paper, Geographically Integrated Dryness Index (GIDI) was integrated from an assortment source including Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), Vegetation Condition Index (VCI), and Standardized Precipitation Evapotranspiration Index (SPEI) (as the dependent variable) based on geographically weighted regression method. Besides, the comprehensive drought situation and changing trends in China from 2001 to 2019 were also examined. The results showed that (1) GIDI has excellent performance in monitoring medium- and long-term droughts and the monitoring results shows 2003, 2016, and 2019 were relatively wet years, while 2007, 2009, and 2011 were major drought years, and spring and March were the most frequent droughts season and month, respectively, and (2) except for the middle and upper reaches of the Yellow River and Northeastern China, which have a tendency to become wet, other places have a tendency to fluctuating dry. This study took advantage of simple and efficient methods to integrate existing indices to obtain a new index for monitoring a wider range of droughts, taking into account the physical mechanism of drought formation and the time scale of drought development, so it can scientifically evaluate the spatial and temporal distribution characteristics of drought and changes.

[Eco-environmental effects and spatiotemporal evolution characteristics of land use change: A case study of Hexi Corridor, Northwest China.] / åœŸåœ°åˆ©ç”¨å˜åŒ–çš„ç”Ÿæ€çŽ¯å¢ƒæ•ˆåº”åŠå ¶æ—¶ç©ºæ¼”å˜ç‰¹å¾­­ä»¥æ²³è¥¿èµ°å»Šä¸ºä¾‹.

Based on the land use data of Hexi Corridor region from 1980 to 2020, we calculated the ecological environment quality index and analyzed the spatial and temporal evolution characteristics, change frequency, patterns, circles of the long time series land use type changes and its ecological environment quality, using the spatial analysis method of ArcGIS. The results showed that unused land was the main land use type in the study area during 1980-2020. The area of construction land, forest land, grassland, and water changed more, and the transition among land use types was obvious. The trends of deterioration and improvement of ecological environment quality in the study area occurred simultaneously and offset each other under certain conditions. The ecological environment quality index evolved in a 'U' shape, first decreasing and then increasing, with little change in overall ecological environment quality fluctuations. The spatial clustering of ecological quality was obvious, which was higher in the southeast and lower in the northwest, without high frequency and large change. The ecological quality in the southeast quadrant of the study area was the worst, followed by the southwest and northwest quadrants, while the ecological quality in the northeast quadrant was the best. The area of the continuously decline zone in ecological environment quality type conversion was larger than that of the continuously rising zone, indicating that ecological environmental protection in the Hexi Corridor had been effective during the study period. The hot spots of ecological quality change were mainly distributed in the central and southwestern part of the Hexi Corridor, and the cold spots were mainly distributed in the northwestern part.

Reconstruction and application of the temperature-vegetation-precipitation drought index in mainland China based on remote sensing datasets and a spatial distance model.

In recent years, remote sensing drought monitoring indices have been gradually developed and have been widely used for global or regional drought monitoring due to their strong drought-monitoring capabilities and easy implementation advantages. However, some defects of remote sensing drought indices stand to be improved due to certain errors in the inversion of surface characteristics by remote sensing datasets. The temperature-vegetation-precipitation drought index (TVPDI) was taken as the research object, and the leaf area index (LAI), the difference between the land surface temperature (LST) and monthly average temperature, and Global Precipitation Measurement (GPM) precipitation data were selected instead of the normalized difference vegetation index (NDVI), LST and tropical rainfall measuring mission (TRMM) data to improve TVPDI. The improved remote sensing drought index was named the improved temperature-vegetation-precipitation drought index (iTVPDI). The drought-monitoring accuracy of iTVPDI was verified by the gross primary productivity (GPP), soil moisture, and crop yield per unit. The drought-monitoring ability of iTVPDI was verified with traditional drought indices, including the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index (PDSI), temperature-vegetation drought index (TVDI), drought severity index (DSI) and crop water stress index (CWSI). The drought-monitoring accuracy of iTVPDI was verified by selecting sample areas. iTVPDI was applied to monitor drought in mainland China over the 2001-2020 period and obtained four main results. First, the correlation analyses of iTVPDI and TVPDI with GPP, crop yield per unit area, and soil moisture showed that iTVPDI had a stronger monitoring ability in Northeast, North, and Southwest China; the R2 value obtained with soil moisture was 0.62 (p < 0.05), and this value was higher than that of TVPDI. Then, the correlation analyses of iTVPDI and TVPDI with SPI, SPEI, PDSI, CWSI, DSI and TVDI showed that the correlation coefficients of iTVPDI and TVPDI with these six indicators were basically consistent, which indicated that the drought-monitoring capability of iTVPDI was consistent with that of TVPDI. In local areas such as the Qinghai-Tibet Plateau in China, the monitoring ability of iTVPDI was stronger than that of TVPDI. Third, through the sample area analysis, iTVPDI was found to moderate the NDVI-characterized vegetation factors in TVPDI in low-vegetation-cover areas affected by soil disturbances and in high-vegetation-cover areas affected by oversaturation. Finally, the results obtained from the application of iTVPDI in mainland China showed that during the warm-dry to warm-wet climate transition between 2001 and 2021, in 2010 and 2018, and in other special drought years, iTVPDI had the best response.

Assessment of Spatio-Temporal Changes for Ecosystem Health: A Case Study of Hexi Corridor, Northwest China.

Ecosystem health (EH) is important for ensuring sustainable development, and the main goal of environmental protection and governance, especially for ecological fragile areas. Scientific assessment of EH can improve decision-making ability and inform sustainable development. In this paper, the effects of natural and social environment were integrated to reflect the characteristics of EH based on a comprehensive assessment system including ecosystem vigor (EV), ecosystem organization (EO), ecosystem resilience (ER), and the ratio of supply to demand of ecosystem services (ESDR) from the perspectives of ecological integrity and human demand for ecosystem services (ES). The Entire-Array-Polygon (EAP) method was applied to calculate an ecosystem health index (EHI) and analyze spatio-temporal change from 2000 to 2020 in Hexi Corridor (HC), Northwest China. The results showed that: (1) The spatial distribution of EV, EO, ER, and ESDR was generally consistent, with a low spatial distribution in the northwest and high in the southeast, the values showed an overall increasing trend from 2000 to 2020. (2) The spatial distribution of EHI was high in the northwest and central regions, and low in the southwest, reflected a moderate health level. The proportion of area with well and relatively well health was increasing, which indicated that EH showed an improving trend. (3) The significantly decrease areas of EHI were mainly located in urban areas, and the increases areas were mainly located outside of urban areas. The distribution of the EH condition has obvious orientation characteristics. The results of the study provide theoretical and practical implications for regional ecological conservation and management.

Monitoring drought dynamics in China using Optimized Meteorological Drought Index (OMDI) based on remote sensing data sets.

Timely and accurate monitoring of the spatiotemporal changes in drought is very important for the reduction in the social losses caused by drought. The Optimized Meteorological Drought Index (OMDI), originally established in southwestern China, showed great potential for drought monitoring over large regions on a large scale. However, the applicability of the index requires further evaluation, especially when used throughout China, which has a different agricultural divisions, variable climatic conditions, complex terrain and diverse land cover. In addition, the OMDI model relies on training data to construct local parameters for the model. On a large scale, it is of great significance to use multisource remote sensing data sets to construct OMDI model parameters. In this paper, the constrained optimization method was used to establish weights for the MODIS-derived Vegetation Conditional Index (VCI), TRMM-derived Precipitation Condition Index (PCI), and GLDAS-derived Soil Moisture Condition Index (SMCI) and calculate the OMDI based on the Standard Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and weather stations. The accuracy of the OMDI model was evaluated by using the correlation coefficient. Moreover, the spatiotemporal changes in drought were also analyzed through trend analysis, Mann-Kendall (MK) statistics and the Hurst index on the monthly and annual scales. The results showed that (1) the highest positive correlation between the OMDI and the SPI was SPI-1, which was higher than that for any other month interval, such as 3 months, 6 months, 9 months and 12 months of the SPI. The results indicated that the OMDI was suitable to monitor meteorological drought. (2) In the nine agricultural subareas in China, the degree of drought in the Yangtze River (DYR) area had the most severe evolution and change frequency. This region was very sensitive to drought in the past two decades. (3) The area with OMDI variation coefficient less than 0.1 accounted for 94%, indicating that the degree of drought fluctuates little; The linear tendency rate is 0.0004, and the area greater than 0 reaches 66.44%, indicating that the drought is developing in a lightning trend. (4) The Hurst index value is mostly higher than 0.5 (the area ratio is 56.31%), and the area of "Positive-Consistent" and "Negative- Opposite" accounted for 54.02%, indicating that more than half of China's area drought changes will show a trend of mitigation in the future.

Drought monitoring in arid and semi-arid region based on multi-satellite datasets in northwest, China.

Drought is a complex natural disaster affected by multiple climate factors and underlying surface. In recent years, drought monitoring indices of remote sensing have been widely applied to monitor drought in a certain region or global. However, some remote sensing drought monitoring indices do not consider the drought-causing factors enough to reflect the comprehensive drought situation of a region fully. In this paper, a new remote sensing drought monitoring index, called Remote Sensing Drought Evaluation Index (RSDEI), was constructed by combining Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI), and Soil Moisture Condition Index (SMCI) using the spatial principal component analysis (SPCA) method. The reasonableness of RSDEI was test and verified using Net Primary Productivity (NPP), Standardized Precipitation Evapotranspiration Index (SPEI), and unit area crop yield. The RSDEI was also applied to the drought condition monitoring of the northwest arid and semi-arid region from 2001 to 2019.The result demonstrated that the results showed that the RSDEI had a high correlation coefficient with SPEI-12 (R=0.85, p<0.01). It is concluded that the correlation coefficient between RSDEI and NPP is 0.74 at 95% confidence level, which indicates that RSDEI and NPP have a strong correlation. Then, the correlation between RSDEI and crop yield per unit area is 0.89. The results of RSDEI showed that the drought in northwest China started in May and lasted in September from 2001 to 2019. The lowest value of RSDEI appeared in May, which inflected the significant difference of drought level in different month in northwest China. The result of CV (coefficient of variation) showed that the drought variation in the study area had a stable low fluctuation condition as a whole, in the northwest and northeast of study area, which indicated that the changes of drought were different in the past 19 years. The Hurst exponent analysis showed that the area with the positive evolution of Hurst index (0.5

Comparative evaluation of drought indices for monitoring drought based on remote sensing data.

Many indices are used to monitor drought events. However, different indices have different data requirements and applications. Hence, evaluating their applicability will help to characterize drought events and refine the development of effective drought indices. We constructed different drought indices based on multisource remote sensing data and comprehensively evaluated and compared their applicability for drought monitoring throughout China. The characteristics of drought events in 2009 and 2011 were compared using various drought indices. The different time scales of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) were used to evaluate remote sensing drought indices in different regions. Single drought indices, including the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, the Precipitation Condition Index (PCI) derived from Tropical Rainfall Measurement Mission (TRMM) data, and the TCI and Soil Moisture Condition Index (SMCI) derived from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) data, as well as combined drought indices, including the Microwave Integrated Drought Index (MIDI), Optimized Vegetation Drought Index (OVDI), Optimized Meteorological Drought Index (OMDI), Scale Drought Conditions Index (SDCI), and Synthesized Drought Index (SDI), were analyzed and compared to evaluate their applicability. The results showed that different drought indices have specific characteristics under different land use types in China. The VCI and TCI can better monitor long-term drought conditions, but they have a weak correlation with the in situ drought index in forestland and grassland areas. The correlation of SPI-1 with the PCI is higher than that with other single indices, which indicates that the PCI is a good short-term drought index. The SMCI has a better correlation with the short-term in situ drought index, but it is not conducive to drought monitoring in areas such as densely forested land and grassland. The correlations of the in situ drought index with the combined drought indices (the MIDI, OVDI, OMDI, SDCI, and SDI) are better than those with the single drought indices.

Assessing environmental interference in northern China using a spatial distance model: From the perspective of geographic detection.

The rapid development of society and the expansion of human activities have resulted in interference with the natural environment. Assessing the environmental interference (EI) caused by human activities is highly important for socio-economic sustainable development. In this study, the spatial distance model (SDM) and resource endowment index (REI)-human activity index (HAI) ratio model were developed to calculate the environmental interference index (EII) in northern China (NC). The current spatial distribution and patterns of EII in NC were analyzed based on geographic information system (GIS) technology. In addition, the factors that influence the level of EI were examined through a geographical detector method. The results showed that the EII value in the eastern region was significantly higher than that in the western region and that differences in EI were spatial heterogeneity. The spatial distribution of EI was analyzed at the provincial, municipal and county scales, respectively. It was found that its distribution was closely related to urban development. The spatial distribution of EI displayed longitudinal zonality. East of 104.987°E, there were many large cities, such as Beijing, Tianjin, Qingdao and Zhengzhou, with high population densities and developed economies. Thus, these areas had high EI values. To the west of 104.987°E, such as in the Qinghai, Gansu, Xinjiang and Inner Mongolia regions, the EI values were generally low, with low environmental quality and fewer human activities. The level of EI in the Huang-Huai-Hai Plain region was higher than that in other areas, displaying obvious spatial dependence. Moreover, the distribution of EI exhibited high-high and low-low aggregation patterns, which accounted for 24.06% and 27.35% of the total study area, respectively. Specifically, in NC, the EI caused by human activities displayed obvious regional characteristics. In addition, the factors that influence EI were determined through a geographical detector model. The land use intensity was the direct factor related to changes in and the levels of EI, and the cover and growth of vegetation were the most important factors associated with mitigating human interference. The assessment results can provide a reference for the formulation of environmental governance and related policies.

Spatiotemporal evolution of environment based on integrated remote sensing indexes in arid inland river basin in Northwest China.

Arid inland river basin has been regarded as environmental vulnerable and an important protective area in northwest China. Shiyang River Basin (SRB) is one of the most typical areas in arid inland rivers basin in China. The environmental quality evaluation of different periods is significant for environmental control and management of SRB. In this paper, the normalized differential vegetation index (NDVI), wetness index (WI), albedo, index-based built-up index (IBI), salinization index (SI), and land surface temperature (LST) were obtained through Landsat TM and OLI images in 1995, 2000, 2005, 2010, and 2016. Besides, three methods including spatial principal component analysis (SPCA), analytic hierarchy process (AHP), and remote-sensing spatial distance model (RSSDM) were compared to select a reasonable method for environmental evaluation. The AHP method was determined as the final method for objectively evaluating spatiotemporal changes of environment from 1995 to 2016 in SRB. The results showed that the environment deteriorated in 1995-2000 and improved in 2000-2016. The effect of environmental governance was significant in 2010-2016 because of the longtime environmental management between multiple departments. The results indicated that the environmental quality of SRB was generally improved from 1995 to 2016. We found that the improvement areas were mainly concentrated in the oasis and marginal areas, while environmental damage areas were mainly distributed in the urban regions. However, in most areas of the SRB, the environment was still below average level of China, and the roads of the environment management still had a long way to go. We found that spatiotemporal pattern analysis of the environment was of great importance for the formulation of plans for development of this basin and environmental protection measures.