A multi-resolution global land cover dataset through multisource data aggregation

Recent developments of 30 m global land characterization datasets(e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover mapping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC(Finer Resolution Observation and Monitoring-Global Land Cover) and FROM-GLC-seg(Segmentation), with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area(NL-ISA) and MODIS urban extent(MODIS-urban), to produce an improved 30 m global land cover map—FROM-GLC-agg(Aggregation). It was post-processed using additional coarse resolution datasets(i.e., MCD12Q1, GlobCover2009, MOD44 W etc.) to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion aggregation approaches were employed to create a multi-resolution hierarchy(i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km) of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map(at 30 m) and the three maps subsequently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required.     

Global desert variation under climatic impact during 1982-2020

Deserts are important landscapes on the earth and their variations have impacts on global climate through feedback processes.However,there is a limited understanding of the climatic controls on the spatial and temporal variations of global deserts.Here,we use climate reanalysis datasets,global land use/land cover(LULC)products and the CMIP6(Coupled Model Intercomparison Project)model outputs to calculate the changing of global deserts during 1982-2020,and estimate future spatial trends of global...     

A 30 meter land cover mapping of China with an efficient clustering algorithm CBEST

Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised classification approaches. This article used a fast clustering method—Clustering by Eigen Space Transformation(CBEST) to produce a land cover map for China. Firstly, 508 Landsat TM scenes were collected and processed. Then, TM images were clustered by combining CBEST and K-means in each pre-defined ecological zone(50 in total for China). Finally, the obtained clusters were visually interpreted as land cover types to complete a land cover map. Accuracy evaluation using 2159 test samples indicates an overall accuracy of 71.7% and a Kappa coefficient of 0.64. Comparisons with two global land cover products(i.e., Finer Resolution Observation and Monitoring of Global Land Cover(FROM-GLC) and GlobCover 2009) also indicate that our land cover result using CBEST is superior in both land cover area estimation and visual effect for different land cover types.     

Land use effects on climate in China as simulated by a regional climate model

A regional climate model (RegCM3) nested within ERA40 re-analyzed data is used to investigate the climate effects of land use change over China. Two 15-year simulations (1987―2001), one with current land use and the other with potential vegetation cover without human intervention, are conducted for a domain encompassing China. The climate impacts of land use change are assessed from the difference between the two simulations. Results show that the current land use (modified by anthropogenic ac- tivities) influences local climate as simulated by the model through the reinforcement of the monsoon circulation in both the winter and summer seasons and through changes of the surface energy budget. In winter, land use change leads to reduced precipitation and decreased surface air temperature south of the Yangtze River, and increased precipitation north of the Yangtze River. Land use change signifi- cantly affects summer climate in southern China, yielding increased precipitation over the region, de- creased temperature along the Yangtze River and increased temperature in the South China area (south-end of China). In summer, a reduction of precipitation over northern China and a temperature rise over Northwest China are also simulated. Both daily maximum and minimum temperatures are affected in the simulations. In general, the current land use in China leads to enhanced mean annual precipitation and decreased annual temperature over south China along with decreased precipitation over North China.     

Suitability mapping of global wetland areas and validation with remotely sensed data

With increasing urbanization and agricultural expansion, large tracts of wetlands have been either disturbed or converted to other uses. To protect wetlands, accurate distribution maps are needed. However, because of the dramatic diversity of wetlands and difficulties in field work, wetland mapping on a large spatial scale is very difficult to do. Until recently there were only a few high resolution global wetland distribution datasets developed for wetland protection and restoration. In this paper, we used hydrologic and climatic variables in combination with Compound Topographic Index(CTI) data in modeling the average annual water table depth at 30 arc-second grids over the continental areas of the world except for Antarctica. The water table depth data were modeled without considering influences of anthropogenic activities. We adopted a relationship between potential wetland distribution and water table depth to develop the global wetland suitability distribution dataset. The modeling results showed that the total area of global wetland reached 3.316×107 km2. Remote-sensing-based validation based on a compilation of wetland areas from multiple sources indicates that the overall accuracy of our product is 83.7%. This result can be used as the basis for mapping the actual global wetland distribution. Because the modeling process did not account for the impact of anthropogenic water management such as irrigation and reservoir construction over suitable wetland areas, our result represents the upper bound of wetland areas when compared with some other global wetland datasets. Our method requires relatively fewer datasets and has a higher accuracy than a recently developed global wetland dataset.     

Development of a daily soil moisture product for the period of2002–2011 in Chinese mainland

Soil moisture is an essential climate variable(ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year(2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Chinese mainland was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System(AMSR-E) brightness temperature(TB) data into a land surface model(LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau.The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons(spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center.     

Continuous land cover change monitoring in the remote sensing big data era

<正>Since the late 20th century,global change issues have attracted lots of attention.As a key component of global changes,land cover and land use information has been increasingly important for improved understanding of global environmental changes and feedbacks between social and environmental systems(Verburg et al.,2015).A set of national and global scale land cover/use products with higher spatial and temporal resolutions have been developed to fill this gap.In China,existing efforts include China’s National     

Improvement of snow depth retrieval for FY3B-MWRI in China

The primary objective of this work is to develop an operational snow depth retrieval algorithm for the FengYun3B Microwave Radiation Imager(FY3B-MWRI)in China.Based on 7-year(2002–2009)observations of brightness temperature by the Advanced Microwave Scanning Radiometer-EOS(AMSR-E)and snow depth from Chinese meteorological stations,we develop a semi-empirical snow depth retrieval algorithm.When its land cover fraction is larger than 85%,we regard a pixel as pure at the satellite passive microwave remote-sensing scale.A 1-km resolution land use/land cover(LULC)map from the Data Center for Resources and Environmental Sciences,Chinese Academy of Sciences,is used to determine fractions of four main land cover types(grass,farmland,bare soil,and forest).Land cover sensitivity snow depth retrieval algorithms are initially developed using AMSR-E brightness temperature data.Each grid-cell snow depth was estimated as the sum of snow depths from each land cover algorithm weighted by percentages of land cover types within each grid cell.Through evaluation of this algorithm using station measurements from 2006,the root mean square error(RMSE)of snow depth retrieval is about 5.6 cm.In forest regions,snow depth is underestimated relative to ground observation,because stem volume and canopy closure are ignored in current algorithms.In addition,comparison between snow cover derived from AMSR-E and FY3B-MWRI with Moderate-resolution Imaging Spectroradiometer(MODIS)snow cover products(MYD10C1)in January 2010 showed that algorithm accuracy in snow cover monitoring can reach 84%.Finally,we compared snow water equivalence(SWE)derived using FY3B-MWRI with AMSR-E SWE products in the Northern Hemisphere.The results show that AMSR-E overestimated SWE in China,which agrees with other validations.     

Seasonal variation of soil respiration under different land use/land cover in arid region

Through combining the soil respiration with the main environmental factors under the planting shelterbelt (Populus woodland) and the natural desert vegetation (Tamarix ramosissima Phragmites communis community and Haloxylon ammodendron community) in the western Junngar Basin, the difference in soil respiration under different land use/land cover types and the responses of soil respiration to temperature and soil moisture were analyzed. Results showed that the rate of soil respiration increased with temperature. During the daytime, the maximum soil respiration rate occurred at 18:00 for the Populus woodland, 12:00 for T. ramosissima Ph. communis community, and 14:00 for H. ammodendron community, while the minimum rate all occurred at 8:00. The soil respiration, with the maximum rate in June and July and then declining from August, exhibited a similar trend to the near-surface temperature from May to October. During the growing season, the mean soil respiration rates and seasonal variation differed among the land use/land cover types, and followed the order of Populus woodland >T. ramosissima Ph. communis community > H. ammodendron community. The difference in the soil respiration rate among different land use/land cover types was significant. The soil respiration of Pouplus woodland was significantly correlated with the near-surface temperature and soil temperature at 10 cm depth (P < 0.01) in an exponential manner. The soil respiration of T. ramosissima Ph. communis and H. ammodendron communities were all linearly correlated with the near-surface temperature and soil surface temperature (P < 0.01). Based on the near-surface tempera-ture, the calculated Q10 of Populus woodland, T. ramosissima Ph. communis community and H. ammodendron community were 1.48, 1.59 and 1.63, respectively. The integrated soil respiration of the three land use/land cover types showed a significant correlation with the soil moisture at 0―5 cm, 5― 15 cm and 0―15 cm depths (P < 0.01). The quadratic model could best describe the relationship between soil respiration and soil moisture at 0―5 cm depth (P < 0.01).     

First comprehensive fine-resolution global land cover map in the world from China—Comments on global land cover map at 30-m resolution

<正>Land cover maps are of fundamental importance in studies of the complex interactions between human activities and global change.Mapping land cover using remote sensing is a traditional but still very active field.In the past 45 years,nearly 30000 papers about land cover mapping were published worldwide,including approximately 10000 papers     

Evaluating the accuracy of Chinese pasture data in global historical land use datasets

Global historical land use datasets are widely used in global environmental change studies; however, uncertainties in the included pasture data have not been evaluated. In this study, using trend, relative difference ratio(RDR), and spatial comparisons, we evaluated the accuracy of China pasture data in the HYDE(versions 3.1 and 3.2), SAGE, and PJ datasets using historical document-based reconstructions, including the land use datasets for China covering 1935–1997(hereafter Ge-dataset)and Northeast China covering the 1700 s–2000(hereafter Ye-dataset), and the satellite-based China's Land-Use/cover Datasets(CLUDs) for 1980–2015. Four important results were obtained.(1) China pasture area in the HYDE, SAGE, and PJ datasets and grassland area in the Ge-dataset, Ye-dataset, and CLUDs show both disparate trends and large differences in absolute values.(2)Spatially, 50.9%, 52.8%, and 63.0% pasture/grassland grids in 2000 had RDRs greater than 60% between HYDE3.1, HYDE3.2,and SAGE datasets, and CLUDs, respectively. The percentage of grids with RDRs less than 20% were 24.9%, 26.7%, and 16.0%,respectively.(3) Based on HYDE3.2, the spatial distribution of pasture in Northeast China over the last 300 year has expanded,which is in contrast to the results from the Ye-dataset, which shows the spatial distribution of grassland shrinking because of human reclamation activities.(4) The large contrasts between the global datasets and Chinese native datasets are due to differences in pasture/grassland definitions, land use practices, and spatial reconstruction methods.     

Spatiotemporal variations of vegetation cover on the Chinese Loess Plateau(1981―2006):Impacts of climate changes and human activities

Spatiotemporal variations of Chinese Loess Plateau vegetation cover during 1981-2006 have been investigated using GIMMS and SPOT VGT NDVI data and the cause of vegetation cover changes has been analyzed, considering the climate changes and human activities. Vegetation cover changes on the Loess Plateau have experienced four stages as follows: (1) vegetation cover showed a continued increasing phase during 1981―1989; (2) vegetation cover changes came into a relative steady phase with small fluctuations during 1990―1998; (3) vegetation cover declined rapidly during 1999―2001; and (4) vegetation cover increased rapidly during 2002―2006. The vegetation cover changes of the Loess Plateau show a notable spatial difference. The vegetation cover has obviously increased in the Inner Mongolia and Ningxia plain along the Yellow River and the ecological rehabilitated region of Ordos Plateau, however the vegetation cover evidently decreased in the hilly and gully areas of Loess Plateau, Liupan Mountains region and the northern hillside of Qinling Mountains. The response of NDVI to climate changes varied with different vegetation types. NDVI of sandy land vegetation, grassland and cultivated land show a significant increasing trend, but forest shows a decreasing trend. The results obtained in this study show that the spatiotemporal variations of vegetation cover are the outcome of climate changes and human activities. Temperature is a control factor of the seasonal change of vegetation growth. The increased temperature makes soil drier and unfavors vegetation growth in summer, but it favors vegetation growth in spring and autumn because of a longer growing period. There is a significant correlation between vegetation cover and precipitation and thus, the change in precipitation is an important factor for vegetation variation. The improved agricultural production has resulted in an increase of NDVI in the farmland, and the implementation of large-scale vegetation construction has led to some beneficial effect in ecology.     

GlobeLand30: Operational global land cover mapping and big-data analysis

正Information regarding Land cover and change (LCC) over time is essential for a variety of Societal Benefits Areas(SBA), such as environmental change analysis, geographical condition monitoring, urban and rural management, earth surface process modeling, and sustainable development.Since the middle of 1990s, the international scientific communities have devoted tremendous efforts to Global Land Cover (GLC) mapping, and developed a number of coarser resolution (ranging from 300-m to 1 km) data products. As     

Application of the Linearity Method to Processing and Analyzing of Precursory Data

In this paper,the spatial linearity method is applied to synthetical processing of precursory data from different stations and different disciplines.The new characteristic value(a)obtained can describe the whole precursory field.The authors present the formulas for calculating spatial linearity.Furthermore,the spatial linearity method is applied to processing of geoelectrical resistivity and groundwater level data from 1970 to 1994 in North China.The results show that the new characteristic value(a)could detect the anomaly 1 year before moderately strong earthquakes.     

The application of the high-frequency electromagnetic sounding method in the exploration of underground thermal water

High-frequency electromagnetic sounding is an electromagnetic exploration method using the natural high-frequency electromagnetic field as a field source. It has higher resolution and greater depth penetration than the direct current method and is especially fit for geothermal energy exploration and low- and mid-level groundwater detection. We introduce a successful application of high-frequency electromagnetic sounding for evaluating geothermal water resources. The high frequency electromagnetic system （MT-USA with a frequency range from 10 KHz to 1 Hz） is first applied to sample field data from China. A remote reference station is used to assure sampled data quality. We then perform 2D inversion image processing with the electrical method data. The results basically indicate the spatial distribution of underground geothermal water and provide favorable clues to finding the sources of the subsurface geothermal water in this area.     

Land cover changes based on plant successions: Deforestation,rehabilitation and degeneration of forest in the upper Dadu River watershed

The land use/cover classification system is the foundation for land use/cover change study. Remote sensing data were firstly used for land use and land cover classification in the United States in 1971 and the Anderson Classification System was proposed in 1976[1], which was put into use in mapping 1:250000 land use and land cover of the United States. A series of new land cover classification systems have been established in recent years through research projects such as FAO LCCS and Bi…     

Characterizing the dynamics of soil organic carbon in grasslands on the Qinghai-Tibetan Plateau

Carbon dynamics of grasslands on the Qinghai-Tibetan Plateau may play an important role in regional and global carbon cycles. The CENTURY model (Version 4.5) is used to examine temporal and spatial variations of soil organic carbon (SOC) in grasslands on the Plateau for the period from 1960 to 2002. The model successfully simulates the dynamics of aboveground carbon and soil surface SOC at the soil depth of 0-20 cm and the simulated results agree well to the measurements. Examination of SOC for eight typical grasslands shows different patterns of temporal variation in different ecosystems in 1960-2002. The extent of temporal variation increases with the increase of SOC of ecosystem. SOC increases first and decreases quickly then during the period from 1990 to 2000. Spatially, SOC density obtained for the equilibrium condition declines gradually from the southeast to the northwest on the plateau and showed a high heterogeneity in the eastern plateau. The results suggest that (i) SOC den-sity in the alpine grasslands shows remarkable response to climate change during the 42 years, and (ii) the net carbon exchange rate between the alpine grassland ecosystems and the atmosphere increases from 1990 to 2000 as compared with that before 1990.     

NanoSIMS analytical technique and its applications in earth sciences

Despite the significant improvement on spatial resolution,Nano SIMS still preserves relatively high mass resolution,sensitivity,and analytical precision.It has become an important analytical platform to determine chemical compositions of solid materials,and has been widely used in space,earth,life,and materials sciences,etc.By using a Cs+ion beam with a size as small as 50nm scanning over sample surfaces,we are able to obtain high spatial resolution images of up to 7 species simultaneously.When utilizing Faraday cup,high analytical precision of 0.3‰–0.5‰(1SD)for C,O and S isotopic analysis can be achieved.Although this precision level is still lower than that of conventional SIMS,it already meets the major requirements of Earth Sciences.In 2011,the first Nano SIMS of China(Cameca Nano SIMS 50L)was installed at Institute of Geology and Geophysics,Chinese Academy of Sciences.Based on the working mechanism and analytical modes of the instrument,this paper will systematically introduce the analytical methods established with the Nano SIMS and their potential applications in earth sciences.These methods include trace element distribution images in mineral zoning,high spatial resolution(2–5?m)Pb-Pb and U-Pb dating,water content and H isotopic analysis for silicate glass and apatite,C isotopic analysis for diamond and graphite,O isotopic analysis for carbonate,S isotopic analysis for sulfides.In addition,the specific requirements for sample preparation will also be introduced in order to facilitate domestic earth scientists’use.     

Geographical characteristics of China’s wetlands derived from remotely sensed data

In this paper, we report the first wetland mapping of the entire China using Landsat enhanced thematic mapper plus (ETM+) data. These data were obtained from the Global Land Cover Facility at the University of Maryland spanning from 1999 to 2002. A total of 597 scenes of Landsat images were georeferenced and mosaiced. Manual image interpretation of satellite images was aided with elevation data, soil data, land cover/land use data and Google Earth. The minimum mapping unit is 10 pixel × 10 pixel, equivalent...     

Effects of future land use change on the regional climate in China

Land use and land cover change(LUCC)is one of the important human forcing on climate.However,it is difficult to infer how LUCC will affect climate in the future from the effects of previous LUCC on regional climates in the past.Thus,based on the land cover data recommended by the Coupled Model Intercomparison Project Phase 5(CMIP5),a regional climate model(Reg CM4)was used to investigate the climate effects of future land use change over China.Two 15-year simulations(2036–2050),one with the current land use data and the other with future land cover scenario(2050)were conducted.It is noted that future LUCC in China is mainly characterized by the transition from the grassland to the forest.Results suggest that the magnitudes and ranges of the changes in temperature and precipitation caused by future LUCC show evident seasonality,which are more prominent in summer and autumn.Significant response of climate to future LUCC mainly happens in Northeast China,North China,the Hetao Area,Eastern Qinghai-Tibetan Plateau and South China.Further investigation shows that future LUCC can also produce significant impacts on the atmospheric circulation.LUCC results in abnormal southwesterly wind over extensive areas from the Indian peninsula to the coasts of the South China Sea and South China through the Bay of Bengal.Furthermore,Indian tropical southwest monsoons and South Sea southwest monsoons will both be strong,and the abnormal water vapor convergence from the South China Sea and the Indian Ocean will result in more precipitation in South China.