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In line with the United Nations Sustainable Development Goal (SDG) 6, the main goal of the Special Issue on "Remote sensing for water resources and environmental management" was to solicit papers from a diverse range of scientists around the world on the use of cutting-edge remote sensing technologies to assess and monitor freshwater quality, quantity, availability, and management to ensure water security. Special consideration was given to scientific manuscripts that covered, but were not limited to, the development of geospatial techniques and remote sensing applications for detecting, quantifying, and monitoring freshwater water resources, identifying potential threats to water resources and agriculture, as well as other themes related to water resources and environmental management at various spatial scales. The Special Issue attracted over thirteen peer-reviewed scientific articles, with the majority of manuscripts originating from China. Most of the studies made use of satellite datasets, ranging from coarse spatial resolution data, such as the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO), to medium spatial resolution data, such as the Landsat series, ERA5, Modern-Era Retrospective Analysis for Research and Application Land version 2 reanalysis product (MERRA2), CLSM and NOAH ET, and MODIS (Moderate Resolution Imaging Spectroradiometer). Google Earth Engine (GEE) data, together with big data processing techniques, such as the remote sensing-based energy balance model (ALEXI/DisALEXI approach) and the STARFM data fusion technique, were used for analyzing geospatial datasets. Overall, this Special Issue demonstrated significant knowledge gaps in various big data image processing techniques and improved computing processes in assessing and monitoring water resources and the environment at various spatial and temporal scales. [ABSTRACT FROM AUTHOR]

This paper presents an integrated study on the effects of human activity, climate change and crustal movement on the changes of the middle reaches of the Tarim River in China. Remote sensing images and rainfall data from 38 stations from 1970 to 2021 were used for the research. The precise point positioning (PPP) approach was applied to ascertain the crustal movement of the study area using 256 Global Positioning System (GPS) station data of the recent 20 years. The results show that in the past 50 years the studied reaches of the river has moved north at maximum 2940 m or 57.9 m on average, and human activity may have played a dominant role in this change though extreme events of climate may have also taken a part in it. However, before the Anthropocene, its northeast migration is likely associated with crustal movement as the basin bottom inclines to northeast. [ABSTRACT FROM AUTHOR]

As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) satellites can provide over 40 years of global remote sensing observations, which can be used to retrieve long-term aerosol optical depth (AOD). This is of great significance to the study of global climate change. In this paper, we proposed an algorithm to jointly calculate AOD and land surface properties from AVHRR observations. With assumptions that AOD doesn't vary in adjacent space and earth surface property doesn't vary in two days, the algorithm considered non-Lambertian surface reflection based on the shape of bidirectional reflectance distribution function (BRDF shape) and obtained AOD and surface property by optimal estimation (OE) method. The algorithm has been applied to NOAA-7, 9, 11, 14, 16, 18, and 19 satellites and AVHRR-retrieved AOD with 5 × 10 km over China (15°–60° N, 70°–140°E) has been obtained from 1982 to 2016. Comparisons of AVHRR-retrieved AOD against AErosol RObotic NETwork (AERONET) (in and around China) and China Aerosol Remote Sensing Network (CARSNET) AOD show good consistency with 62.62% points within the uncertainty of Δτ = ± (0.05 + 0.25τ) and root-mean-square error (RMSE) of 0.26. Further comparison of the monthly mean AOD of multiple AOD datasets in the 'Beijing', 'Dalanzadgad', 'NCU_Taiwan' and 'Kanpur' stations shows that the results of the algorithm are stable. The yearly averaged AOD data also has similar agreements with MERRA-2 (The Modern-Era Retrospective analysis for Research and Applications, Version 2) and AVHRRDB data (AVHRR 'Deep Blue' aerosol data set). The multi-year mean correlation coefficient is 0.70 and 0.61 and the percentages within the uncertainty are 80.01% and 67.29% compared with MERRA-2 AOD and AVHRRDB AOD respectively. [ABSTRACT FROM AUTHOR]

Lidar is an active remote sensing instrument, and it has been widely used in the detection of atmospheric environmental parameters and meteorological parameters. In recent years, climate change has been widely concerned by the public, and the corresponding atmospheric detection technology has also been developed rapidly. Atmospheric Lidar has been developed rapidly in China, and has achieved good research achievements. The research progress and development status of Lidar for atmospheric detection in recent years are introduced and summarized in this invited paper. The advantages and disadvantages of all kinds of atmospheric detection Lidars and their applications in different detection objects are comprehensively introduced in this article. Finally, the bottlenecks of Lidar technology are summarized, and the development trend of Lidar is also prospected. [ABSTRACT FROM AUTHOR]

Drought has become a problem that is universally faced by global terrestrial ecosystems. Northeast China is dominated by a temperate monsoon climate and located in an area sensitive to global climate changes, and one of the main impacts of climate changes in Northeast China is manifested as drought in growing seasons. The drought area has a gradual increase trend, and drought has become the main agro-meteorological disaster in this region which is also the main maize planting area in China. Drought normalization seriously restricts the stable development of maize production in Northeast China. So in this paper, we took spring maize in Liaoning Province as an example and made clear the drought variation characteristics in different growth stages by using the data of MODIS, FY-3A, relative soil moisture and growth stages and the methods of RS, GIS and statistical analysis. Then we analyzed the correlation between multi-time scale remote sensing indexes and relative soil moisture in different soil depth, and established the remote sensing monitoring index set and models of relative soil moisture for each growth stage and soil depth. The accuracy of the monitoring models was verified and the application research of monitoring the drought of spring maize in Liaoning Province was studied. The results showed that: From 1993 to 2012, drought occurred in each growth stage of spring maize in Liaoning Province and the highly frequent drought occurred in the period from 1999 to 2002. The drought grade in each year was mainly light drought, and the drought was the most serious at milk stage, followed by heading stage. There was no significant correlation between the monitoring indexes and relative soil moisture at sowing and emergence stage, but there was a significant or extremely significant correlation between them at three-leaf and maturity stage. The monitoring index LSWI (land surface water index) had a strong ability to monitor relative soil moisture, followed by WI (water index). Multi-index coordination could improve the monitoring ability of relative soil moisture by remote sensing means, and the monitoring ability at 10-day scale was generally higher than that at 5-day scale and 20-day scale. Based on the monitoring models of soil relative humidity, the drought condition of partial growth stages and soil depth from 2001 to 2004 was monitored. The overall monitoring accuracy was 73.32%, in which the monitoring accuracy of jointing and three-leaf stage was more than 85%. The dynamic monitoring of drought grades in different growth stages in 2000 was realized. The monitoring results were consistent with the agro-meteorological observation records in terms of the growth stages and space. This study would be very significant to improve the capacity of disaster prevention and mitigation by monitoring spring maize accurately and synchronously on a large range. [ABSTRACT FROM AUTHOR]

• A deep learning algorithm is used to build a comprehensive drought monitoring model. • Multi-source remote sensing data is processed as input data. • The comprehensive drought model has good applicability in the monitoring of meteorological drought and agricultural drought. • The model successfully monitored a drought process in Henan Province, China. • This study provides a new method for the comprehensive assessment of regional drought. Drought is a popular scientific issue in global climate change research. Accurate monitoring of drought has important implications for the sustainable development of regional agriculture in the context of increasingly complex global climate change. Deep learning is a widely used technique in the field of artificial intelligence. However, ongoing on drought monitoring using deep learning is relatively scarce. In this paper, the various hazard factors in drought development were comprehensively considered based on satellite data including Moderate Resolution Imaging Spectroradiometer (MODIS) and tropical rainfall measuring mission (TRMM) as multi-source remote sensing data. By using the deep learning technique, a comprehensive drought monitoring model was constructed and tested in Henan Province of China as an example. The results showed that the comprehensive drought model has good applicability in the monitoring of meteorological drought and agricultural drought. There was a significant positive correlation between the drought indicators of the model output and the comprehensive meteorological drought index (CI) measured at the site scale. The consistency rate of the drought grade of the two models was 85.6% and 79.8% for the training set and the test set, respectively. The correlation coefficient between the drought index of the model and the standard precipitation evapotranspiration index (SPEI) was between 0.772 and 0.910 (P < 0.01), which indicated a strong level of significance. The correlation coefficient between the drought index of the model and the soil relative moisture at a 10 cm depth was greater than 0.550 (P < 0.01), and there was a good correlation between them. This study provides a new method for the comprehensive assessment of regional drought. [ABSTRACT FROM AUTHOR]

Extreme heat events have serious effects on human daily life. Accurately capturing the dynamic variance of extreme high-temperature distributions in a timely manner is the basis for analyzing the potential impacts of extreme heat, thereby informing risk prevention strategies. This paper demonstrates the potential application of multiple source remote sensing data in mapping and monitoring the extreme heat events that occurred on Aug. 8, 2013 in Jiangsu Province, China. In combination with MODIS products, the thermal sharpening (TsHARP) method and a binary linear model are compared to downscale the original daytime FengYun 2F (FY-2F) land surface temperature (LST) imagery, with a temporal resolution of 60 min, from 5 km to 1 km. Using the meteorological measurement data from Nanjing station as the reference, the research then estimates the instantaneous air temperature by using an iterative computation based on the Surface Energy Balance Algorithm for Land (SEBAL), which is used to analyze the spatio-temporal air temperature variance. The results show that the root mean square error (RMSE) of the LST downscaled from the binary linear model is 1.30°C compared to the synchronous MODIS LST, and on this basis the estimated air temperature has the RMSE of 1.78°C. The spatial and temporal distribution of air temperature variance at each geographical location from 06:30 to 18:30 can be accurately determined, and indicates that the high temperature gradually increases and expands from the city center. For the spatial distribution, the air temperature and the defined scorching temperature proportion index increase from northern to middle, to southern part of Jiangsu, and are slightly lower in the eastern area near the Yellow Sea. In terms of temporal characteristics, the percentage of area with air temperature above 37°C in each city increase with time after 10:30 and reach the peak value at 14:30 or 15:30. Then, they decrease gradually, and the rising and falling trends become smaller from the southern cities to the northern regions. Moreover, there is a distinct positive relationship between the percentage of area above 37°C and the population density. The above results show that the spatio-temporal distributions of heat waves and their influencing factors can be determined by combining multiple sources of remotely sensed image data. [ABSTRACT FROM AUTHOR]

Land use and land cover changes (LUCC) are thought to be amongst the most important impacts exerted by humans on climate. However, relatively little research has been carried out so far on the effects of LUCC on extreme climate change other than on regional temperatures and precipitation. In this paper, we apply a regional weather research and forecasting (WRF) climate model using LUCC data from Heilongjiang Province, that was collected between the 1900s and 2010s, to explore how changes in forest cover influence extreme temperature indexes. Our selection of extreme high, low, and daily temperature indexes for analysis in this study enables the calculation of a five-year numerical integration trail with changing forest space. Results indicate that the total forested area of Heilongjiang Province decreased by 28% between the 1900s and 2010s. This decrease is most marked in the western, southwestern, and northeastern parts of the province. Our results also reveal a remarkable correlation between change in forested area and extreme high and low temperature indexes. Further analysis enabled us to determine that the key factor explaining increases in extreme high temperature indexes (i.e., calculated using the number of warm days, warm nights, as well as tropical nights, and summer days) is decreasing forest area; data also showed that this factor caused a decrease in extreme low temperature indexes (i.e., calculated using the number of cold days and cold nights, as well as frost days, and ice days) and an increase in the maximum value of daily minimum temperature. Spatial data demonstrated that there is a significant correlation between forest-to-farmland conversion and extreme temperature indexes throughout most of our study period. Spatial data demonstrated that there is a significant correlation between forest-to-farmland conversion and extreme temperature indexes throughout most of our study period. Positive correlations are also present between decreasing forest area, the more frequent occurrence of extreme high temperature events, and a rise in the maximum value of daily minimum temperature. At the same time, we found clear negative correlations between decreasing forest area and less frequent occurrence of extreme low temperature events. [ABSTRACT FROM AUTHOR]

Timely and accurate monitoring of the onset and evolution of drought in China are important to reduce losses from drought. The Integrated Surface Drought Index (ISDI) which originally established in mideast China shows a large potential for real-time regional drought monitoring. However, ISDI is still at the developmental stage, and the applicability of the index requires further examination especially for China with vast area, climatic conditions, complex topography, and land cover. Furthermore, ISDI model depends on the historical training data corresponding to the study area. ISDI application in China must be remodeled using the historical training data over China. In this paper, we remodeled ISDI over China based on previous work and evaluated its capability for near real-time drought monitoring. Using the Palmer Drought Severity Index (PDSI) as a dependent variable, ISDI integrates climate-based drought indices, satellite-based Vegetation Index (VI) and land surface temperature (LST) with other biophysical and elevation data to produce a 1-km regional drought condition map at 16-day intervals. Strong relationships were determined between the calculated ISDI and PDSI for spring, summer and autumn, and all of the correlation coefficients exceeded 0.8. The initial ISDI results demonstrated a good performance for monitoring droughts in southwestern China from 2009 to 2010, high temperatures and droughts in southern China in 2013, and floods in northeastern China in 2013. The higher spatial resolution and near real-time capability of ISDI can provide important inputs for drought management and mitigation in China. [ABSTRACT FROM AUTHOR]

Surface water provides a basic resource for life and is vital for maintaining climate stability, hydrological cycles, and natural ecosystems. Lakes, which are an important part of surface water, play a crucial role in sustaining the hydrological balance and maintaining a healthy environment. The onset of climate change and anthropogenic disturbance on lakes and the environment, however, have drastically changed the morphological characteristics of lakes, leading to undesirable negative effects on the ecological environment. In recent years, many lakes around the world are undergoing phenomenal changes due to climate change and human activities. These changes have greatly affected the availability of freshwater resources, leading to a series of regional ecological and environmental problems, which constrain the regional sustainable development. Changes in lake parameters often indicate environmental change. Therefore, it is of great practical significance to extract lake water information to reflect the water quantity changes in the lake, understand its implications, and come up with timely solutions. This paper summarizes the existing research methods of lake water estimation in China and abroad and draws the following conclusions: (1) In the study of lake water volume estimation, it can be roughly divided into with topographic data and without topographic data. The most representative methods are the estimation methods based on topographic parameters and the Triangle Irregular Network (TIN) model method. In the actual research process, most of the scarce data that are difficult to obtain are lake topographic data, prompting researchers to constantly put forward new methods; (2) From the perspective of research methods, estimation of lake water volume can be divided into remote sensing-based and non-remote sensing-based research. With the continuous improvement of scientific and technological levels, current geographical researchers tend to use remote sensing to monitor lake water volume; (3) Although researchers have proposed a series of models for lake water volume estimation for the long-time process. However, many models are based on the ideal static estimation process, which poses challenges for researchers to make a long-term dynamic estimation of lake storage capacity in the future. At the same time, the accuracy of the model can be a problem that researchers need to work out solutions in the future. Finally, combined with the current development of remote sensing technology, the application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. • Lake water volume estimation, it can roughly be divided into with topographic data and without topographic data. • Estimation of lake water volume can be divided into remote sensing-based and non-remote sensing research. • The application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. [ABSTRACT FROM AUTHOR]

This paper examines the topographic and geometric controls on glacier changes in area and equilibrium-line altitude (ELA) in the central Tien Shan, China, since the Little Ice Age (LIA). We delineate the extents of 487 modern glaciers and their corresponding maximum LIA glacial advances using satellite imagery in Google Earth, and analyze the relationships between the magnitude of glacier changes and a set of local topographic/geometric factors including glacier area, slope, aspect, shape, hypsometry and mean elevation. Our results show that: (1) glacier area decreased from 460.2km² during the LIA to 265.6km² in the 2000s (a loss of 42.3%), with an average ELA increase of ~100 m; (2) relative area changes of glaciers are strongly affected by two of these local factors (glacier area and mean elevation); and (3) ELA change does not show a strong relationship with local factors, suggesting that it may be controlled mainly by climatic factors. This study provides important insights into the local controls on glacier changes at the centennial timescale, which are of critical importance to assess future glacier changes in this arid and semi-arid region. [ABSTRACT FROM AUTHOR]

Abstract: Previous studies show that the area of a moraine-dammed lake can provide a good indicator of the significance of its outburst. For a glacier-dammed lake however, because its area and depth fluctuates with the melting of its ice dam, it is difficult to predict the outburst of the glacier‐dammed lake by using its area alone. A characteristic of the surface of Lake Merzbacher is a large amount of floating ice therefore, a method is proposed in this article to extract the area of floating ice on the lake and the area of ice free water in the lake by using Environment and Disaster Monitoring Small Satellite images respectively. Furthermore, based on the area of floating ice extracted through the image information of Lake Merzbacher in 2009 and 2010, we determined the relationship between the ice area and the outburst of the lake, then formulated the Index for hazard of Glacier Lake Outburst Flood (IGLOF) of Lake Merzbacher, which cannot only predict the flood outburst, but also determine the specific outburst period after the lake drainage had occurred. This can be shown in a recalculation of the lake drainages in the years 2009 and 2010. Research results indicate that when IGLOF is less than 0.5 and the lake area is larger than 3km2, the outburst process is in early-warning period and GLOF will occur in the next 5–8days. Also, the successful outburst prediction of Lake Merzbacher in 2011 showed that the index described in this paper provides a quick methodology for forecasting and warning against Lake Merzbacher outburst floods. However，as our research was based on a short observation period (2009-2011) and also cannot be supplemented by other images, it will still be needed to be checked and validated by continuous observation and improvement in future. [Copyright &y& Elsevier]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate change on terrestrial wet and dry changes and the relationship between the two is of great significance to the sustainable development of terrestrial ecosystems. The farming-pastoral ecotone of northern China (FPENC) is an area that is sensitive to climate change, suffering from perennial drought and a clear aridification trend. Unlike previous single-factor, single-timescale studies, we identified aridification in the region based on a dataset established by remote sensing and ground-based monitoring stations from a combination of two perspectives: climate and soil. The results show that, in terms of climate, the period from 2000 to 2019 was the driest in the region during the last 120 years , and the summer drought was the most severe and shifted from a summer to spring drought; in terms of soil, the soil aridification trend in the region was severe, with 16.1% of the areas becoming significantly drier (P < 0.1) among the years and 41.6% in spring, respectively. Similar to climate change, soils exhibited recessive aridification due to the counterbalancing effect of the dry and wet seasons within the year. Then the coupling relationship between climate change and soil aridification was established in time and space. Moreover, the spatiotemporal response patterns of both were obtained. The results showed that the frequency of soil drought under meteorological drought conditions showed an increasing trend and that the sensitivity of soil drought occurrence increased. Among them, the effect of precipitation on relative soil moisture (RSM) was immediate, and the effect of prolonged warming on RSM is greater. The area of soil aridification that was caused by climatic aridification in spring accounted for 13.7% of the entire area. The regional aridification research mode proposed in this paper can provide ideas for subsequent studies. [Display omitted] • A comprehensive judgment mode of the regional aridification combining climate elements, soil moisture was established. • Over the last 20 years, the central part of the FPENC showed overall warming and wetting of the climate. • Over the last 20 years, the trend of the soil aridification in the central part of the FPENC remained severe. • The counterbalancing effect of the dry and wet seasons leads to recessive aridification. • The sensitivity of the occurrences of soil drought to the climate drought anomalies continuously became stronger. [ABSTRACT FROM AUTHOR]

Abstract: Aeolian sandy land in the Yarlung Zangbo River basin has attracted the attention of many researchers. However, its dynamics as well as its relevance to various factors has rarely been reported with integrated studies. In this paper, spatio-temporal dynamics of the aeolian sandy land in the basin was studied by interpreting Landsat images acquired from 1975, 1990, 2000, and 2008 with the help of geographic information system (GIS) technology. Spatially, the results showed a decreasing trend from west to east, which is from the Maquanhe wide valley in the headwater area to the middle and lower reaches of the river basin. Temporally, aeolian sandy lands in the basin showed a slow increasing trend, with an increase of 10.5% during the 1975–2008 period, spreading most quickly during the period of 1990–1999. The factors related to dynamics of aeolian sandy land were analyzed from the perspectives of two driving factors, climate changes and human activities. The climate-dominated natural factors are the internal driving forces for the development of aeolian sandy lands, and the human factors are the external driving forces responsible for the increase of the aeolian sandy land area. [Copyright &y& Elsevier]

Abstract: Agricultural development under climatic variations has resulted in substantial loss of marshes in the West Songnen Plain in the past decades. In this paper, the shrinkage and fragmentation process of marshes and its possible causes in the West Songnen Plain from 1954 to 2008 were explored using historical topographic maps and remote sensing data. Results indicated that the West Songnen Plain underwent considerable shrinkage and fragmentation of marshes in that same period. Marshes occupied 6404km2 in 1954, but this area has decreased by 74% in the past 54 years. The average annual decrease rate of marshes was 88km2 per year. Meanwhile, the number of marsh patches decreased from 1411 to 514, and the mean patch size decreased from 454 to 320ha. Cropland and salinized wasteland were the two main land use types into which marshes were converted. During the same period, grassland decreased by 54%, cropland increased by 22%, and salinized wasteland expanded by 612%. A significant increase in air temperature and index of dryness was found in the study region, along with decreased precipitation, thereby affecting the marsh systems through the changing hydrological regimes. On the other hand, population, gross domestic product, and livestock number increased considerably as marshes shrank and became fragmented. Governmental policy changes played a key role in land use transformations in the study region. [Copyright &y& Elsevier]

This study aims to assess CO2 levels in China, based on the dry air column-averaged mixing ratios of CO2 measured by the Scanning Imaging Absorption spectrometer for Atmospheric CartograpHY (SCIAMACHY) instrument on board ENVISAT and emission inventories. A land cover and statistical data set, the Regional emission inventory in Asia (REAS), was also used in this study. The results show that the spatial variations of the CO2 concentration in the whole of China are obvious, and with clear seasonal fluctuation during 2003-2005. The monthly averaged variability of CO2 over China fluctuates, with the peak occurring in April to May and the trough occurring in August to October. The largest peak-to-trough amplitude was about 16 ppm in this period. The spatial and temporal variations of CO2 had a strong correlation with anthropogenic CO2 emissions and regional terrestrial ecosystem, as well as local meteorological conditions. This paper illustrates that satellite data are promising for obtaining a comprehensive understanding of the variations of atmospheric CO2 concentrations and of CO2 emissions to the atmosphere. [ABSTRACT FROM AUTHOR]

In this paper, we report the results and analysis of a recent field campaign in August 2007 investigating the impacts of emissions from transportation on air quality and community concentrations in Beijing, China. We conducted measurements in three different environments, on-road, roadside and ambient. The carbon monoxide, black carbon and ultrafine particle number emission factors for on-road light-duty vehicles are derived to be 95gkg−1-fuel, 0.3gkg−1-fuel and 1.8×1015 particleskg−1-fuel, respectively. The emission factors for on-road heavy-duty vehicles are 50gkg−1-fuel, 1.3gkg−1-fuel and 1.1×1016 particleskg−1-fuel, respectively. The carbon monoxide emission factors from this study agree with those derived from remote sensing and on-board vehicle emission testing systems in China. The on-road black carbon and particle number emission factors for Chinese vehicles are reported for the first time in the literature. Strong traffic impacts can be observed from the concentrations measured in these different environments. Most clear is a reflection of diesel truck traffic activity in black carbon concentrations. The comparison of the particle size distributions measured at the three environments suggests that the traffic is a major source of ultrafine particles. A four-day traffic control experiment conducted by the Beijing Government as a pilot to test the effectiveness of proposed controls was found to be effective in reducing extreme concentrations that occurred at both on-road and ambient environments. [Copyright &y& Elsevier]

Recent climatic changes have affected terrestrial net primary productivity (NPP). This paper presents an investigation of the impact of climatic changes on Chinese terrestrial vegetation NPP by analyzing 18 years' (1982 to 1999) climatic data and satellite observations of vegetation activity. Results indicate that climatic changes in China have eased some critical climatic constraint on plant growth. (1) From 1982 to 1999, modeled NPP increased by 1.42% · a-1 in water-limited regions of Northwest China, 1.46% · a-1 in temperature-limited regions of Northeast China and Tibet Plateau, and 0.99% · a-1 in radiation-limited regions of South China and East China. (2) NPP increased by 24.2%, i.e. 0.76 petagram of carbon (Pg C) over 18 years in China. Changes in climate (with constant vegetation) directly contributed nearly 11.5% (0.36 Pg C). Changes in vegetation (with constant climate) contributed 12.4% (0.40 Pg C), possibly as a result of climate-vegetation feedbacks, changes in land use, and growth stimulation from other mechanisms. (3) Globally, NPP declined during all three major El Niño events (1982 to 1983, 1987 to 1988, and 1997 to 1998) between 1982 and 2000, but Chinese vegetation productivity responded differently to them because of the monsoon dynamics. In the first three events (1982 to 1983, 1987 to 1988, and 1992), Chinese vegetation NPP declined, while in the later two events (1993, 1997 to 1998) increasing obviously. [ABSTRACT FROM AUTHOR]

Northern China has been long threatened by aeolian desertification. In recent years, all levels of the Chinese government have performed a series of ecological protection and sand control projects. To grasp the implementation effects of these projects and adjust policies in time, it is necessary to understand the process of aeolian desertification quickly and accurately. Remote sensing technologies play an irreplaceable role in aeolian desertification monitoring. In this study, the Zhenglan Banner, which is in the hinterland of the Hunshandake Sandy Land, was considered as the research area. Based on unmanned aerial vehicle (UAV) images, ground survey data, and Landsat images called in Google Earth Engine (GEE), the aeolian desertified land (ADL) in 2000, 2004, 2010, 2015, and 2019 was extracted using spectral mixture analysis. A desertification index (DI) was constructed to evaluate the spatial and temporal dynamics of the ADL in the Zhenglan Banner. Finally, a residual analysis explored the driving forces of aeolian desertification. The results showed that (1) the ADL area in the Zhenglan Banner has been trending downwards over the past 20 years but rebounded from 2004 to 2010; (2) over the past 20 years, the area of slightly, moderately, and severely desertified land has decreased at annual rates of 0.4%, 2.7%, and 3.4%, respectively; (3) human activities had significantly positive and negative impacts on the aeolian desertification trend for 20.0% and 21.0% of the study area, respectively, but not for the rest. This paper explored new techniques for rapid aeolian desertification monitoring and is of great significance for controlling and managing aeolian desertification in this region. [ABSTRACT FROM AUTHOR]

In the acceleration of industrialization and urbanization, brownfield is an important resource for land regeneration and restoration targeting to recover its ecosystem function. Landfills, as a type of brownfield distributed in the highly populated areas, occupy massive land resources. The ecological restoration of landfills becomes an engineering approach to achieve multiple effects of society, environment, and economy. This paper aims to monitor and assess the restoration microclimatic effects of landfills restoration in China with remote sensing data and techniques. We selected representative landfill restoration projects, including Nanhaizi Park in Beijing, Nanhu Park in Tangshan, and Tianziling Park in Hangzhou, as the study cases. Using the Landsat imagery, the scenes of the pre-restoration, mid-restoration, and post-restoration were retrieved, and the surface energy balance equation was applied to calculate normalized difference vegetation index (NDVI), land surface temperature (T s), and evapotranspiration (ET), representing vegetation conditions and hydro-heat microclimate conditions. The study areas are divided into four subzones and extracted the calculated values for statistics and comparison. We defined an indicator of restoration intensity (RI) using the different subzones to the outer contour distance radius and restoration phases to evaluate the spatial-temporal restoration degrees. The spatial pattern dynamics was displayed in the urbanization context in the cases of Beijing and Tangshan. We examined and quantified the relations between RI and the key indicators, NDVI, T s , and ET. The overall results revealed that with higher restoration intensity, NDVI and ET became higher, and T s became lower. It suggested that the ecological restoration on the landfills brought better vegetation, cooling, and humidification effects for the microclimatic environment. Our research has the implications for monitoring and assessing the climatic effects of ecological restoration in the brownfield regeneration in a macroscopic and ecosystem perspective. Unlabelled Image • With satellite dataset, we developed a way to monitor vegetation and microclimatic changes in the restored landfills. • The indicator to quantify the ecological restoration intensity was invented with spatial distance and restoration phase. • Overall, with higher restoration intensity, vegetation and evapotranspiration improved, and surface temperature declined. [ABSTRACT FROM AUTHOR]