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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]

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]

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]

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]

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]

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]

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]