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| 1 | Analysis of sea surface temperature fronts in the Taiwan Strait and its adjacent area using an advanced edge detection method显示文摘A morphology-based edge detection method has been used to study sea surface temperature (SST) fronts in the Taiwan Strait and its adjacent area. The method is based on mathematical morphology with multi-dimensional and multi-structural elements. Using six years’ SST data from September 2002 to August 2008, we distinguished the large SST front like Kuroshio Front as well as the smaller ones: namely Taiwan Bank Front, Zhe-Min Coastal Front and Zhang-Yun Ridge Front. The seasonal and monthly variations of these fronts were also studied. Generally, the SST fronts are stronger in winter but weaker in summer. And the fronts are at their active stage during the period from January to May but at their declining stage during the period from July to October. | PI QingLing1,2,3 & HU JianYu1,2 1 State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, China 2 Department of Oceanography, Xiamen University, Xiamen 361005, China 3 China Communications Construction Company First Harbor Consultants CO., LTD., Tianjin 300222, China | 2010 | Science China Earth Sciences2010，53，7： | 29 |
| 2 | 中国2010-2015年土地利用变化的时空格局与新特征(英文)显示文摘Land use/cover change is an important theme on the impacts of human activities on the earth systems and global environmental change. National land-use changes of China during 2010–2015 were acquired by the digital interpretation method using the high-resolution remotely sensed images, e.g. the Landsat 8 OLI, GF-2 remote sensing images. The spatiotemporal characteristics of land-use changes across China during 2010–2015 were revealed by the indexes of dynamic degree model, annual land-use changes ratio etc. The results indicated that the built-up land increased by 24.6×10~3 km^2 while the cropland decreased by 4.9×10~3 km^2, and the total area of woodland and grassland decreased by 16.4×10~3 km^2. The spatial pattern of land-use changes in China during 2010–2015 was concordant with that of the period 2000–2010. Specially, new characteristics of land-use changes emerged in different regions of China in 2010–2015. The built-up land in eastern China expanded continually, and the total area of cropland decreased, both at decreasing rates. The rates of built-up land expansion and cropland shrinkage were accelerated in central China. The rates of built-up land expansion and cropland growth increased in western China, while the decreasing rate of woodland and grassland accelerated. In northeastern China, built-up land expansion slowed continually, and cropland area increased slightly accompanied by the conversions between paddy land and dry land. Besides, woodland and grassland area decreased in northeastern China. The characteristics of land-use changes in eastern China were essentially consistent with the spatial govern and control requirements of the optimal development zones and key development zones according to the Major Function-oriented Zones Planning implemented during the 12 th Five-Year Plan(2011–2015). It was a serious challenge for the central government of China to effectively protect the reasonable layout of land use types dominated with the key ecological function zones and agricultural production zones in centraland western China. Furthermore, the local governments should take effective measures to strengthen the management of territorial development in future. | 宁佳 刘纪远 匡文慧 徐新良 张树文 颜长珍 李仁东 吴世新 胡云锋 杜国明 迟文峰 潘涛 宁静 | 2018 | Journal of Geographical Sciences2018，28，5： | 30 |
| 3 | Study of spatial distribution of sandy desertification in North China in recent 10 years显示文摘Sandy desertification is a land degradation characterized by wind erosion, mainly resulted from the excessive human activities in arid, semiarid and part of sub-humid regions in North China. It is one of main kinds of desertification/land degradation as well as water-soil erosion and salinization in China. Rapid and continuous spread of sandy desertification during last 50 years has created a major environmental and socio-economic problem in North China. Remote sensing monitored results in 2000 showed that the sandy desertified land area has been 38.57×104 km2. The area of potential to slightly sandy desertified land is 13.93×104 km2, moderately land 9.977×104 km2, severely land 7.909×104 km2 and very severely land 6.756×104km2. Sandy desertification mainly occurs in the semi-arid mixed farming-grazing zone and its northern rangeland zone, semi-arid dryland rainfed cropping zone and arid oasis-desert margin zone. The average annually developmental rate of sandy desertified land increased from 2,100tion in North China is 'overall deterioration, while local rehabilitation'. Already achieved rehabilitation results and monitoring assessment show that about 60% of desertified land in North China can be restored under the conditions of rational land-use ways and intensity. | WANG Tao, WU Wei, XUE Xian, SUN Qingwei & CHEN GuangtingKey Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China Department of Environment Engineering, Peking University, Beijing 100871, China | 2004 | Science China Earth Sciences2004，47，z1： | 28 |
| 4 | Principles and methods for the validation of quantitative remote sensing products显示文摘We first discuss the relativity of 'true value and homogeneity' for quantitative remote sensing products (QRSPs), and then propose the definitions of 'eigenaccuracy' and 'eigenhomogeneity' under practical conditions. The eigenaccuracy and eigenhomogeneity for land surface crucial parameters such as albedo, leaf area index (LAI), and surface temperature are analyzed based on a series of experiments. Secondly, we point out the differences and similarities between the scale-free phenomena of the QRSPs and the measurements of the coastline length (1-dimensional) and the curved surface area (2-dimensional). An information fractal algorithm for the QRSPs is presented. In a case study for the LAI, when the fractal dimension is 2.16, the ratio of the LAI retrieval values obtained respectively from remote sensing data of 30 m and 6 km pixel resolution can actually reach as high as 2.86 for the same 6 km pixel using the same retrieval model. Finally, we propose an operational validation method 'one test and two matches' and multipoint observation when the real situation does not allow carrying out scanning measurement without gap and overlap on the ground surface. | RenHua Zhang Jing Tian ZhaoLiang Li HongBo Su ShaoHui Chen XinZhai Tang | 2010 | Science China Earth Sciences2010，53，5： | 27 |
| 5 | The oasis expansion and eco-environment change over the last 50 years in Manas River Valley, Xinjiang显示文摘The oasis expansion and economic development of the Manas River Valley is one of the most successful examples in Xinjiang. In this paper, the oasis spatial distribution pattern and dynamic change were examined using imageries of Landsat MSS, TM and ETM, land use and topographic maps in six different periods (such as 1949, 1962, 1976, 1989, 1999 and 2001) over the last 50 years in the valley. The oasis expansion process could be divided into two stages according to the annual rate of oasis area increase, the fast oasization stage (from 1949 to 1976) when the oasis area ex-panded from 156.385 km2 in 1949 to 3,639.491 km2 in 1976 because of rapidly increased population and quickly enlarged farmland area; and the urbanization stage (from 1976 to 2001) when the ex-pansion ratio of farmland slowed down, and the urbanization process quickened, the total oasis area reached 5042.440 km2 in 2001. With the continuous expansion of oasis and farmland, a large quantity of river water was drawn into irrigation ditch and plain lakes, so only a small quantity of river water could flow into lakes, as a result, the Manas Lake dried up, salization and basification problems happened in the low-lying oasis region. The natural swamp around the lake was shrunk greatly and biodiversity decreased significantly. The driving force analysis reveals that human activities, such as reclamation and population growth, played a major role in the oasis expansion and ecological dete-rioration in the Manas River Valley. So further efforts should be made to improve the efficiency of water resource utility and adjust layout of the regional agricultural and animal husbandry to keep the sustainable development of oasis economic belt of the northern slope of Tianshan Mts. | CHENG Weiming ZHOU Chenghu LIU Haijiang ZHANG Yang JIANG Yan ZHANG Yichi YAO Yonghui | 2006 | Science China Earth Sciences2006，49，2： | 24 |
| 6 | OpenRS-Cloud:A remote sensing image processing platform based on cloud computing environment显示文摘This paper explores the use of cloud computing for remote sensing image processing.The main contribution of our work is to develop a remote sensing image processing platform based on cloud computing technology(OpenRS-Cloud).This paper focuses on enabling methodical investigations into the development pattern,computational model,data management and service model exploring this novel distributed computing model.The experimental INSAR processing flow is implemented to verify the efficiency and feasibility of OpenRS-Cloud platform.The results show that cloud computing is well suited for computationally-intensive and data-intensive remote sensing services. | GUO Wei,GONG JianYa,JIANG WanShou,LIU Yi & SHE Bing State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430074,China | 2010 | Science China(Technological Sciences)2010，53，S1： | 24 |
| 7 | Chinese HJ-1A/B satellites and data characteristics显示文摘From the viewpoint of environmental remote-sensing applications,this article explains the overall technical characteristics of the Chinese HJ-1A and HJ-1B satellites.It also investigates the spectral characteristics and potential applications of charge-coupled devices,and the infrared and hyperspectral data obtained by the satellites.Examples of applications,such as the remote-sensing monitoring of algal bloom in Taihu Lake,straw burning in southern China,and aerosol optical depth in the area around Bohai sea are presented.These examples illustrate the application characteristics of the HJ-1A and HJ-1B satellite data. | WANG Qiao1,WU ChuanQing1,LI Qing1 & LI JunSheng2 1 Satellite Environment Center,Ministry of Environmental Protection,Beijing 100029,China 2 Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing 100190,China | 2010 | Science China Earth Sciences2010，53，S1： | 17 |
| 8 | Study on detection of coastal water environment of China by ocean color remote sensing显示文摘Coastal water environment is essentially enhanced by ocean color which is basically decided by substances concentration in water such as chlorophyll, suspended material and yellow substance. It is very difficult, even not possible, to detect water color by expensive ship routing, because of its temporal and spatial variety of feature and scales in the very complicated dynamical system of coastal water. With the development of satellite technique in the last 20 a, space sensors can be applied to detect ocean color by measuring the spectra of water leaving radiance.It is proven that ocean color remote sensing is a powerful tool for understanding the process of oceanic biology and physics. Since the 1980s, great attention has been paid to the advanced remote sensing technique in China, especially to development of satellite programs for the coastal water environment. On 7 September 1988, China launched her first polar orbit satellite FY-1A for meteorological and oceanographic application (water color and temperature) and the second satellite FY-1B two years later. In May 1999, China launched her second generation environment satellite FY-1C with higher sensitivies, more channels and stable operation. The special ocean color satellite HY-1 is planned to be in the orbit in 2001, whose main purpose is to detect the coastal water environment of China seas. China is also developing a very advantageous sensor termed as Chinese moderate imaging spectra radiometer (CMODIS) with 91 channels, which will be a good candidate of the third generation satellite FY-3 in 2003. The technical system of ocean color remote sensing was developed by the Second Institute of Oceanography (SIO), State Oceanic Administration (SOA) in 1997. The system included data receiving, processing, distribution, calibration, validation and application units. The Hangzhou Station of SIO, SOA has the capability to receive FY-1 and AVHRR data since 1989. It was also a SeaWiFS scientific research station authorized by NASA,USA to free receive SeaWiFS data from 16 September 1997. In the recent years, the local algorithms of atmospheric correction and inversion of ocean color have been developed for FY-1C and SeaWiFS, to improve the accuracy of the measurement from satellites efficiently. The satellite data are being applied to monitor coastal water environment, such as the spatial distribution of chlorophyll, suspended material and yellow substance, red tide detection and coastal current study. The results show that the ocean color remote sensing has latent capacity in the detection of coastal water environment.In consideration of the update technique progress of ocean color remote sensing and its more important role in the detection of coastal water in the 2000s, some suggestions are set forth, which would be beneficial to the design of a cheaper but practical coastal water detection system for marine environment preservation. | Pan Delu 1,2 , Mao Tianming 1, Li Shujing 1,Huang Haiqing 11 .LaboratoryofOceanDynamicProcessesandSatelliteOceanographyofStateOceanicAdministration ,Hangzhou310 0 12 ,China 2 .LaboratoryofSubmarineGeosciencesofStateOceanicAdministration ,Hangzhou 3 | 2001 | Acta Oceanologica Sinica2001，20，1： | 16 |
| 9 | An operational two-layer remote sensing model to estimate surface flux in regional scale: Physical background显示文摘Based on the improved interaction mechanism of two-layer model, this paper proposed Pixel Component Arranging and Comparing Algorithm (PCACA) and theoretically positioning algorithm, estimated the true temperature of mixed pixel in four extreme points in combination with the measurements of dry and wet points in calibration fields and improved the reliability of positioning dry and wet line. A new two-layer energy-separation algorithm was proposed,which was simple and direct without resistance network parameters for each pixel. We also proposed a new thought about the effect of advection. The albedo of mixed pixel was also separated with PCACA. In combination with two-layer energy-separation algorithm, the net radiation of mixed pixel was separated to overcome the uncertainty of conventional energy-separation algorithm using Beer's Law. Through the validation of retrieval result, this method is proved to be feasible and operational. At the same time, the uncertainty of this algorithm was objectively analyzed. | ZHANG Renhua SUN Xiaomin WANG Weimin XU Jinping ZHU Zhilin TIAN Jing | 2005 | Science China Earth Sciences2005，48，z1： | 16 |
| 10 | Impact of China’s Air Pollution Prevention and Control Action Plan on PM2.5 chemical composition over eastern China显示文摘China promulgated the Air Pollution Prevention and Control Action Plan(the Action Plan)in 2013 and developed stringent control measures to mitigate fine particulate matter(PM2.5) pollution.Here,we investigated the PM2.5 chemical composition changes over eastern China associated with the Action Plan during 2013-2017 using satellite-based PM2.5 chemical composition data derived using CMAQ simulations and satellite inputs.The PM2.5 concentrations decreased considerably during this time as a result of the reductions in all chemical species in PM2.5.The population-weighted mean concentrations over eastern China decreased from 11.1 to 6.7μgm-3 for SO42-,13.8-13.1μgm-3 for NO3-,7.4-5.8μgm-3 for NH4+,9.9-8.4μgm-3 for OM,4.6-3.8μg m-3 for BC and 12.9-9.6μg m-3 for other species in PM2.5.SO42-had the largest reduction of 40%,while NO3-had the lowest reduction of 5%,resulting in a greater fraction of NO3-and a smaller fraction of SO42-in PM2.5.Among the three key regions,Beijing-Tianjin-Hebei had the largest reduction in PM2.5 and its chemical compositions.The decrease in SO42-concentrations was in line with the reduction of SO2 emissions,and the major driver of the SO2 emission reductions was the industrial sector.The decrease in NO3 concentrations was limited because the decrease in SO2 emissions and the stable NH3 emissions facilitated the formation of NO3-from HNO3,which partially offset the reduction in NOx emissions driven by the power sector.To mitigate PM2.5 pollution more effectively,future efforts are needed to reduce NH3 emissions. | Guannan GENG Qingyang XIAO Yixuan ZHENG Dan TONG Yuxuan ZHANG Xiaoye ZHANG Qiang ZHANG Kebin HE Yang LIU | 2019 | Science China Earth Sciences2019，62，12： | 16 |
| 11 | Geographical characteristics of China’s wetlands derived from remotely sensed data显示文摘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 to 9 ha. The aim of our first round of mapping was only targeted at the boundary delineation of any type of wetland except those wetlands that are under agricultural use (i.e., paddy fields), which has already been well mapped by others. Our interpretation results indicate that a total of 359478 km2 of wetlands are of non-agricultural use. Among our preliminarily mapped wetland, 339353 km2 are inland wetland, 2786 km2 are non-agricultural artificial wetland, and 17609 km2 are coastal wetland. Because low-tide is rarely captured in satellite images, an under-estimation of coastal wetland is inevitable. We conducted some statistics based on our mapped wetlands and compared them with those previously obtained from a number of sources including a land cover/land use map made with satellite images during the late 1990s and early 2000s, a marshland map developed in approximately the same period, survey data of coastal wetland in early 1980s, and area data for approximately 400 larger patches of marshland in China compiled in 1996. Because some inconsistencies exist in the guidelines of those different wetland surveys, difference in area is expected. Some further comparison indicates that the wetland distributions derived from the preliminary wetland map are reasonable and more objective than other sources. The mapping process also indicated that the method adopted by us was efficient and cost-effective. We also found that in order to ensure comparability of the wetland maps developed at different times, a set of standard guidelines on the wetland categories to be mapped, and the mapping methods to be used must be well conceived, developed and effectively employed. We carried out some initial geographical analysis on the distribution of wetlands. | NIU ZhenGuo GONG Peng CHENG Xiao GUO JianHong WANG Lin HUANG HuaBing SHEN ShaoQing WU YunZhao WANG XiaoFeng WANG XianWei YING Qing LIANG Lu ZHANG LiNa WANG Lei YAO Qian YANG ZhenZhong GUO ZiQi DAI YongJiu | 2009 | Science China Earth Sciences2009，52，6： | 15 |
| 12 | Object-oriented land cover classification using HJ-1 remote sensing imagery显示文摘The object-oriented information extraction technique was used to improve classification accuracy,and addressed the problem that HJ-1 CCD remote sensing images have only four spectral bands with moderate spatial resolution.We used two key techniques:the selection of optimum image segmentation scale and the development of an appropriate object-oriented information extraction strategy.With the principle of minimizing merge cost of merging neighboring pixels/objects,we used spatial autocorrelation index Moran's I and the variance index to select the optimum segmentation scale.The Nearest Neighborhood(NN) classifier based on sampling and a knowledge-based fuzzy classifier were used in the object-oriented information extraction strategy.In this classification step,feature optimization was used to improve information extraction accuracy using reduced data dimension.These two techniques were applied to land cover information extraction for Shanghai city using a HJ-1 CCD image.Results indicate that the information extraction accuracy of the object-oriented method was much higher than that of the pixel-based method. | SUN ZhongPing1,SHEN WenMing1,WEI Bin1,LIU XiaoMan1,SU Wei2,ZHANG Chao2 & YANG JianYu2 1 Satellite Environment Center,Ministry of Environmental Protection,Beijing 100094,China 2 College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China | 2010 | Science China Earth Sciences2010，53，S1： | 15 |
| 13 | Hybrid first and second order attention Unet for building segmentation in remote sensing images显示文摘Recently,building segmentation(BS)has drawn significant attention in remote sensing applications.Convolutional neural networks(CNNs)have become the mainstream analysis approach in this field owing to their powerful representative ability.However,owing to the variation in building appearance,designing an effective CNN architecture for BS still remains a challenging task.Most of CNN-based BS methods mainly focus on deep or wide network architectures,neglecting the correlation among intermediate features.To address this problem,in this paper we propose a hybrid first and second order attention network(HFSA)that explores both the global mean and the inner-product among different channels to adaptively rescale intermediate features.As a result,the HFSA can not only make full use of first order feature statistics,but also incorporate the second order feature statistics,which leads to more representative feature.We conduct a series of comprehensive experiments on three widely used aerial building segmentation data sets and one satellite building segmentation data set.The experimental results show that our newly developed model achieves better segmentation performance over state-of-the-art models in terms of both quantitative and qualitative results. | Nanjun HE Leyuan FANG Antonio PLAZA | 2020 | Science China(Information Sciences)2020，63，4： | 15 |
| 14 | Salient Object Detection from Multi-spectral Remote Sensing Images with Deep Residual Network显示文摘alient object detection aims at identifying the visually interesting object regions that are consistent with human perception. Multispectral remote sensing images provide rich radiometric information in revealing the physical properties of the observed objects, which leads to great potential to perform salient object detection for remote sensing images. Conventional salient object detection methods often employ handcrafted features to predict saliency by evaluating the pixel-wise or superpixel-wise contrast. With the recent use of deep learning framework, in particular, fully convolutional neural networks, there has been profound progress in visual saliency detection. However, this success has not been extended to multispectral remote sensing images, and existing multispectral salient object detection methods are still mainly based on handcrafted features, essentially due to the difficulties in image acquisition and labeling. In this paper, we propose a novel deep residual network based on a top-down model, which is trained in an end-to-end manner to tackle the above issues in multispectral salient object detection. Our model effectively exploits the saliency cues at different levels of the deep residual network. To overcome the limited availability of remote sensing images in training of our deep residual network, we also introduce a new spectral image reconstruction model that can generate multispectral images from RGB images. Our extensive experimental results using both multispectral and RGB salient object detection datasets demonstrate a significant performance improvement of more than 10% improvement compared with the state-of-the-art methods. | Yuchao DAI Jing ZHANG Mingyi HE Fatih PORIKLI Bowen LIU | 2019 | Journal of Geodesy and Geoinformation Science2019，2，2： | 14 |
| 15 | Modeling gross primary production of a temperate grassland ecosystem in Inner Mongolia, China, using MODIS imagery and climate data显示文摘Carbon fluxes in temperate grassland ecosystems are characterized by large inter-annual variations due to fluctuations in precipitation and land water availability. Since an eddy flux tower has been in operation in the Xilin Gol grassland, which belongs to typical temperate grassland in North China, in this study, observed eddy covariance flux data were used to critically evaluate the biophysical per- formance of different remote sensing vegetation indices in relation to carbon fluxes. Furthermore, vegetation photosynthesis model (VPM) was introduced to estimate gross primary production (GPP) of the grassland ecosystem for assessing its dependability. As defined by the input variables of VPM, Moderate Resolution Imaging Spectroradimeter (MODIS) and standard data product MOD09A1 were downloaded for calculating enhanced vegetation index (EVI) and land surface water index (LSWI). Measured air temperature (Ta) and photosynthetically active radiation (PAR) data were also included for model simulating. Field CO2 flux data, during the period from May, 2003 to September, 2005, were used to estimate the 'observed' GPP (GPPobs) for validation. The seasonal dynamics of GPP predicted from VPM (GPPVPM) was compared quite well (R2=0.903, N=111, p<0.0001) with the observed GPP. The ag- gregate GPPVPM for the study period was 641.5 g C·m?2, representing a ~6% over-estimation, compared with GPPobs. Additionally, GPP predicted from other two typical production efficiency model (PEM) represents either higher overestimation or lower underestimation to GPPobs. Results of this study demonstrate that VPM has potential for estimating site-level or regional grassland GPP, and might be an effective tool for scaling-up carbon fluxes. | WU WeiXing WANG ShaoQiang XIAO XiangMing YU GuiRui FU YuLing HAO YanBin | 2008 | Science China Earth Sciences2008，51，10： | 13 |
| 16 | Mapping global impervious surface area and green space within urban environments显示文摘The mapping of impervious surface area(ISA) and urban green space(UGS) is essential for improving the urban environmental quality toward ecological, livable, and sustainable goals. Currently, accurate ISA and UGS products are lacking in urban areas at the global scale. This study established regression models that estimated the fraction of ISA/UGS in global 30 cities for validation using MODIS NDVI and DMSP/OLS nighttime light imageries. A global dataset of ISA and UGS fraction with a spatial resolution of 250 m×250 m was developed using the regression model, with a mean relative error of 0.19 for its ISA. The results showed the global urban area of 76.29×10~4 km^2, which was primarily distributed in central Europe, eastern Asia,and central and eastern North America. The urban land area in North America, Europe, and Asia was 66.3×10~4 km^2, accounting for 86.91% of the world’s urban area;the urban land area of the top 50 countries accounted for 59.32% of the total urban land area in the world. The global ISA of 45.26×10~4 km^2 was mainly distributed in central and southern North America, eastern Asia, and Europe, as well as coastal regions around the world. The proportion of ISA situated in built-up areas on the continental scale followed the order of Africa(>70%)>South America>Oceania>Asia(>60%)>North America>Europe(>50%), and these areas were mostly in southeastern North America, southwestern Europe, and eastern and western Asia. North America, Europe, and Asia accounted for 89.44% of the world’s total UGS. The cities of developed countries in Europe and North America exposed a dramatic mosaic of ISA and UGS composites in urban construction. Therefore, the proportion of UGS is relatively high in those cities. However, in developing and underdeveloped countries, the proportion of UGS in built-up areas is relatively low, and urban environments need to be improved for livability. | Wenhui KUANG | 2019 | Science China Earth Sciences2019，62，10： | 12 |
| 17 | 基于Hurst指数的1982–2013年蒙古高原植被动态变化趋势及其影响因素分析(英文)显示文摘This study analyzed the spatial and temporal variations in the Normalized Difference Vegetation Index(NDVI) on the Mongolian Plateau from 1982–2013 using Global Inventory Modeling and Mapping Studies(GIMMS) NDVI3 g data and explored the effects of climate factors and human activities on vegetation. The results indicate that NDVI has slight upward trend in the Mongolian Plateau over the last 32 years. The area in which NDVI increased was much larger than that in which it decreased. Increased NDVI was primarily distributed in the southern part of the plateau, especially in the agro-pastoral ecotone of Inner Mongolia. Improvement in the vegetative cover is predicted for a larger area compared to that in which degradation is predicted based on Hurst exponent analysis. The NDVI-indicated vegetation growth in the Mongolian Plateau is a combined result of climate variations and human activities. Specifically, the precipitation has been the dominant factor and the recent human effort in protecting the ecological environments has left readily detectable imprints in the NDVI data series. | 佟斯琴 张继权 包玉海 来全 连晓 丽娜 包勇斌 | 2018 | Journal of Geographical Sciences2018，28，5： | 11 |
| 18 | NIR-red spectral space based new method for soil moisture monitoring显示文摘Drought is a complex natural disaster that occurs frequently. Soil moisture has been the main issue in remote monitoring of drought events as the most direct and important variable describing the drought. Spatio-temporal distribution and variation of soil moisture evidently affect surface evapotranspiration, agricultural water demand, etc. In this paper, a new simple method for soil moisture monitoring is de- veloped using near-infrared versus red (NIR-red) spectral reflectance space. First, NIR-red spectral reflectance space is established using atmospheric and geometric corrected ETM+ data, which is manifested by a triangle shape, in which different surface covers have similar spatial distribution rules. Next, the model of soil moisture monitoring by remote sensing (SMMRS) is developed on the basis of the distribution characteristics of soil moisture in the NIR-red spectral reflectance space. Then, the SMMRS model is validated by comparison with field measured soil moisture data at different depths. The results showed that satellite estimated soil moisture by SMMRS is highly accordant with field measured data at 5 cm soil depth and average soil moisture at 0―20 cm soil depths, correlation coef- ficients are 0.80 and 0.87, respectively. This paper concludes that, being simple and effective, the SMMRS model has great potential to estimate surface moisture conditions. | GHULAN Abduwasit | 2007 | Science China Earth Sciences2007，50，2： | 11 |
| 19 | Longwall automation:trends,challenges and opportunities显示文摘This paper explores the ongoing development and implementation of longwall automation technology to achieve greater levels of underground coal mining performance. The primary driver behind the research and development effort is to increase the safety, productivity and efficiency of longwall mining operations to enhance the underlying mining business. A brief review of major longwall automation challenges is given followed by a review of the insights and benefits associated with the LASC longwall shearer automation solution. Areas of technical challenge in sensing, decision support, autonomy and human interaction are then highlighted, with specific attention given to remote operating centres, proximity detection and systems-level architectures in order to motivate further automation system development.The vision for a fully integrated coal mining ecosystem is discussed with the goal of delivering a highperformance, zero-exposure and environmentally coherent mining operations. | Jonathon C.Ralston Chad O.Hargrave Mark T.Dunn | 2017 | International Journal of Mining Science and Technology2017，27，5： | 11 |
| 20 | GIS-based landslide susceptibility mapping using numerical risk factor bivariate model and its ensemble with linear multivariate regression and boosted regression tree algorithms显示文摘In this study, a novel approach of the landslide numerical risk factor(LNRF) bivariate model was used in ensemble with linear multivariate regression(LMR) and boosted regression tree(BRT) models, coupled with radar remote sensing data and geographic information system(GIS), for landslide susceptibility mapping(LSM) in the Gorganroud watershed, Iran. Fifteen topographic, hydrological, geological and environmental conditioning factors and a landslide inventory(70%, or 298 landslides) were used in mapping. Phased array-type L-band synthetic aperture radar data were used to extract topographic parameters. Coefficients of tolerance and variance inflation factor were used to determine the coherence among conditioning factors. Data for the landslide inventory map were obtained from various resources, such as Iranian Landslide Working Party(ILWP), Forestry, Rangeland and Watershed Organisation(FRWO), extensive field surveys, interpretation of aerial photos and satellite images, and radar data. Of the total data, 30% were used to validate LSMs, using area under the curve(AUC), frequency ratio(FR) and seed cell area index(SCAI).Normalised difference vegetation index, land use/land cover and slope degree in BRT model elevation, rainfall and distance from stream were found to be important factors and were given the highest weightage in modelling. Validation results using AUC showed that the ensemble LNRF-BRT and LNRFLMR models(AUC = 0.912(91.2%) and 0.907(90.7%), respectively) had high predictive accuracy than the LNRF model alone(AUC = 0.855(85.5%)). The FR and SCAI analyses showed that all models divided the parameter classes with high precision. Overall, our novel approach of combining multivariate and machine learning methods with bivariate models, radar remote sensing data and GIS proved to be a powerful tool for landslide susceptibility mapping. | Alireza ARABAMERI Biswajeet PRADHAN Khalil REZAE Masoud SOHRABI Zahra KALANTARI | 2019 | Journal of Mountain Science2019，16，3： | 11 |
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