Uncertainties in classification system conversion and an analysis of inconsistencies in global land cover products

In this study, using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC (vegetation, wetlands and others only), we studied spatial and areal inconsistencies in the three most recent multi-resource land cover products in a complex mountain-oasis-desert system and quantitatively discussed the uncertainties in classification system conversion. This is the first study to compare these products based on terrain and to quantitatively study the uncertainties in classification system conversion. The inconsistencies and uncertainties decreased from high to low levels of aggregation (IGBP-17 to TC) and from mountain to desert areas, indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. The overall areal inconsistency in the comparison of the FROM-GLC and GlobCover 2009 datasets is the smallest among the three pairs, but the smallest overall spatial inconsistency was observed between the FROM-GLC and MODISLC. The GlobCover 2009 had the largest conversion uncertainties due to mosaic land cover definition, with values up to 23.9%, 9.68% and 0.11% in mountainous, oasis and desert areas, respectively. The FROM-GLC had the smallest inconsistency, with values less than 4.58%, 1.89% and 1.2% in corresponding areas. Because the FROM-GLC dataset uses a hierarchical classification scheme with explicit attribution from the second level to the first, this system is suggested for producers of map land cover products in the future

Protect the giant ibis through the pandemic

The giant ibis (Thaumatibis gigantea), Cambodia’s national bird, is edging toward extinction. The ibis’s historical range stretched across Southeast Asia, but only 194 critically endangered individuals remain, constrained to the northeastern region of Cambodia. The small population suffers from habitat loss and disturbance caused by human activities, and tensions between humans and wildlife have escalated during the coronavirus disease 2019 (COVID-19) pandemic. In April, 3 giant ibises and more than 100 other birds were poached in Cambodia’s Chhep Wildlife Sanctuary. To save the giant ibis, conservation efforts must continue, even during the pandemic

Responses of seasonal indicators to extreme droughts in southwest China

Significant impact of extreme droughts on human society and ecosystem has occurred in many places of the world, for example, Southwest China (SWC). Considerable research concentrated on analyzing causes and effects of droughts in SWC, but few studies have examined seasonal indicators, such as variations of surface water and vegetation phenology. With the ongoing satellite missions, more and more earth observation data become available to environmental studies. Exploring the responses of seasonal indicators from satellite data to drought is helpful for the future drought forecast and management. This study analyzed the seasonal responses of surface water and vegetation phenology to drought in SWC using the multi-source data including Seasonal Water Area (SWA), Permanent Water Area (PWA), Start of Season (SOS), End of Season (EOS), Length of Season (LOS), precipitation, temperature, solar radiation, evapotranspiration, the Palmer Drought Severity Index (PDSI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and data from water conservancy construction. The results showed that SWA and LOS effectively revealed the development and recovery of droughts. There were two obvious drought periods from 2000 to 2017. In the first period (from August 2003 to June 2007), SWA decreased by 11.81% and LOS shortened by 5 days. They reduced by 21.04% and 9 days respectively in the second period (from September 2009 to June 2014), which indicated that there are more severe droughts in the second period. The SOS during two drought periods delayed by 3~6 days in spring, while the EOS advanced 1~3 days in autumn. All of PDSI, SWA and LOS could reflect the period of droughts in SWC, but the LOS and PDSI were very sensitive to the meteorological events, such as precipitation and temperature, while the SWA performed a more stable reaction to drought and could be a good indicator for the drought periodicity. This made it possible for using SWA in drought forecast because of the strong correlation between SWA and drought. Our results improved the understanding of seasonal responses to extreme droughts in SWC, which will be helpful to the drought monitoring and mitigation for different seasons in this ecologically fragile region

The uncertainty analysis of the MODIS GPP product in global maize croplands

Gross primary productivity (GPP) is very important in the global carbon cycle. Currently, the newly released estimates of 8-day GPP at 500 m spatial resolution (Collection 6) are provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Science Team for the global land surface via the improved light use efficiency (LUE) model. However, few studies have evaluated its performance. In this study, the MODIS GPP products (GPPMOD) were compared with the observed GPP (GPPEC) values from site-level eddy covariance measurements over seven maize flux sites in different areas around the world. The results indicate that the annual GPPMOD was underestimated by 6%‒58% across sites. Nevertheless, after incorporating the parameters of the calibrated LUE, the measurements of meteorological variables and the reconstructed Fractional Photosynthetic Active Radiation (FPAR) into the GPPMOD algorithm in steps, the accuracies of GPPMOD estimates were improved greatly, albeit to varying degrees. The differences between the GPPMOD and the GPPEC were primarily due to the magnitude of LUE and FPAR. The underestimate of maize cropland LUE was a widespread problem which exerted the largest impact on the GPPMOD algorithm. In American and European sites, the performance of the FPAR exhibited distinct differences in capturing vegetation GPP during the growing season due to the canopy heterogeneity. In addition, at the DE-Kli site, the GPPMOD abruptly produced extreme low values during the growing season because of the contaminated FPAR from a continuous rainy season. After correcting the noise of the FPAR, the accuracy of the GPPMOD was improved by approximately 14%. Therefore, it is crucial to further improve the accuracy of global GPPMOD, especially for the maize crop ecosystem, to maintain food security and better understand global carbon cycle

Lake area changes and their influence on factors in arid and semi-arid regions along the Silk Road

In the context of global warming, the changes in major lakes and their responses to the influence factors in arid and semi-arid regions along the Silk Road are especially important for the sustainable development of local water resources. In this study, the areas of 24 lakes were extracted using MODIS NDVI data, and their spatial-temporal characteristics were analyzed. In addition, the relationship between lake areas and the influence factors, including air temperature, precipitation, evapotranspiration, land use and land cover change (LULCC) and population density in the watersheds, were investigated. The results indicated that the areas of most lakes shrank, and the total area decreased by 22,189.7 km2 from 2001 to 2016, except for those of the lakes located on the Qinghai-Tibetan Plateau. The air temperature was the most important factor for all the lakes and increased at a rate of 0.113 °C/a during the past 16 years. LULCC and the increasing population density markedly influenced the lakes located in the middle to western parts of this study area. Therefore, our results connecting lake area changes in the study region highlight the great challenge of water resources and the urgency of implementation of the green policy in the One Belt and One Road Initiative through international collaboration

Supplement of the radiance-based method to validate satellite-derived land surface temperature products over heterogeneous land surfaces

Land surface temperature (LST) retrieved from satellite remote sensing data has become a key parameter in research on global environmental change; therefore, the acquisition of accurate satellite-derived LST information is crucial for the diagnosis and analysis of global change. However, it is relatively difficult to obtain the true value of a pixel due to the scale mismatch between in situ measurements and satellite-based observations, especially for commonly heterogeneous and nonisothermal land areas, which greatly increases the difficulty in estimating pixel-representative LST values from in situ measurements for validation of satellite-based LST products. In this study, a supplemented radiance-based (SR-based) validation method was developed to evaluate the latest moderate resolution imaging spectroradiometer (MODIS) Collection 6 Level 2 daily LST/land surface emissivity (LSE) products over a heterogeneous and nonisothermal region of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project, West China. In the SR-based framework, pixel-representative LST values are simulated by the MODTRAN model from the corresponding in situ measurements, such as LSE and atmospheric profile measurements, to evaluate the MODIS LST products. The validation results show that the MODIS daytime LST products from the Aqua satellite (MYD11_L2) have a greater accuracy than those from the Terra satellite (MOD11_L2). Analyses of the effect factors indicate a strong correlation between the errors in the MOD11_L2 LST product and the corresponding difference in the MODIS brightness temperature between bands 31 and 32. Although the requirement of synchronous or quasisynchronous in situ measurements for the validated LST products may limit the applicability of the SR-based method, it is still an effective and simple method for validating satellite-derived LST products over mixed pixels. Our method is an indispensable supplement for the validation methods of satellite-derived LST products, and it can be applied in West China and other areas with heterogeneous land surfaces

Waste management, informal recycling, environmental pollution and public health

With rapid population growth, especially in low-income and middle-income countries, the generation of waste is increasing at an unprecedented rate. For example, annual global waste arising from waste electrical and electronic equipment alone will have increased from 33.8 to 49.8 million tonnes between 2010 and 2018. Despite incineration and other waste treatment techniques, landfill still dominates waste disposal in low-income and middle-income countries. There is usually insufficient funding for adequate waste management in these countries and uptake of more advanced waste treatment technologies is poor. Without proper management, many landfills represent serious hazards as typified by the landslide in Shenzhen, China on 20 December 2015. In addition to formal waste recycling systems, approximately 15 million people around the world are involved in informal waste recycling, mainly for plastics, metals, glass and paper. This review examines emerging public health challenges, in particular within low-income and middle-income countries, associated with the informal sector. While informal recyclers contribute to waste recycling and reuse, the relatively primitive techniques they employ, combined with improper management of secondary pollutants, exacerbate environmental pollution of air, soil and water. Even worse, insufficient occupational health measures expose informal waste workers to a range of pollutants, injuries, respiratory and dermatological problems, infections and other serious health issues that contribute to low life expectancy. Integration of the informal sector with its formal counterparts could improve waste management while addressing these serious health and livelihood issues. Progress in this direction has already been made notably in several Latin American countries where integrating the informal and formal sectors has had a positive influence on both waste management and poverty alleviation

Increased extreme precipitation in Chinese deserts from 1960 to 2018

Extreme precipitation over drylands, especially deserts, has been often observed. The precipitation changes in Chinese deserts have been rarely studied. Here, we use a daily grid precipitation dataset generated via weather station data (0.25° horizontal grid spacing) to investigate the spatial and temporal changes in extreme precipitation in Chinese deserts. The extreme precipitation based on the changes in the total precipitation (PRCPTOT) and the annual‐maximum daily precipitation (Rx1day) in the Chinese desert exhibits markedly increasing trends and presents a spatial distribution of wetting in the western deserts and drying in the eastern deserts. The increase in extreme precipitation could minimize wind erosion and intensify dune stabilization in the western Chinese deserts

Protect and regulate China's oyster resources

China has at least 30 oyster species, all of which provide valuable ecosystem services. Oysters’ filter feeding habit reduces suspended particles and nutrients. One hectare of oyster reef can clean a volume of water equivalent to nearly 15 Olympic swimming pools daily. Oysters’ excrement can stimulate denitrification by removing nitrogenous organic matter, helping to mitigate eutrophication. Natural oyster reefs provide habitat for many species, enhancing biodiversity and increasing fisheries. Oyster reefs can reduce impacts of waves caused by hurricanes and typhoons, stabilizing shorelines. Despite their ecological importance, 85% of oyster reefs globally have been degraded since the 19th century by overharvesting, coastal development, water pollution, and disease. China’s oyster reefs, especially those in Tianjin and Jiangsu, have been seriously damaged during recent decades. Urgent action by Chinese authorities is required to protect these crucial species

Identification of polycentric cities in China based on NPP-VIIRS nighttime light data

Nighttime light data play an important role in the research on cities, while the urban centers over a large spatial scale are still far from clearly understood. Aiming at the current challenges in monitoring the spatial structure of cities using nighttime light data, this paper proposes a new method for identifying urban centers for massive cities at the large spatial scale based on the brightness information captured by the Suomi National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) sensor. Based on the method for extracting the peak point based on digital elevation model (DEM) data in terrain analysis, the maximum neighborhood and di_erence algorithms were applied to the NPP-VIIRS data to extract the pixels with the peak nighttime light intensity to identify the potential locations of urban centers. The results show 7239 urban centers in 2200 cities in China in 2017, with an average of 3.3 urban centers per city. Approximately 68% of the cities had significant polycentric structures. The developed method in this paper is useful for identifying the urban centers and can provide the reference to the city planning and construction