Loading...
 
         Office Online
         Download
More>>  
         Links
More>>  
  • Table of Content
       , Volume 30 Issue 3 Previous Issue    Next Issue
    For Selected: View Abstracts Toggle Thumbnails
    Application of earth observation system of video satellite
    Yiqin YUAN, Guojin HE, Wei JIANG, Guizhou WANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 1-8.   DOI: 10.6046/gtzyyg.2018.03.01
    Abstract   HTML ( 217 )   PDF (3845KB) ( 1275 )

    Remote sensing technology is developing rapidly at present,and human beings are entering a new era of earth observation characterized by high temporal resolution,high spectral resolution and high spatial resolution step by step. The appearance of video satellite brings a new favorable opportunity for real-time observation of remote sensing,which corresponds to the needs of future remote sensing real-time commercial development. This paper summarizes the development status and trend of video satellite both in China and abroad. Then the paper introduces the image-forming principle and characteristics of video satellite,and makes a comparison between the roll-broom imaging mode of video satellite and the push-broom imaging mode of traditional satellite. This paper proposes the application of future video satellite from four important aspects, i.e., business intelligence real-time monitoring,the whole process of natural disasters and dynamic monitoring,environment dynamic monitoring and military security.

    Figures and Tables | References | Related Articles | Metrics
    An overview of urban land use research based on GIS
    Jinlong DU, Jiwei ZHU, Jiancang XIE, Zenghui MA
    Remote Sensing for Land & Resources. 2018, 30 (3): 9-17.   DOI: 10.6046/gtzyyg.2018.03.02
    Abstract   HTML ( 21 )   PDF (778KB) ( 658 )

    Combined with research status of urban land use both in China and abroad, this paper expounds the status and problems of GIS in urban land use research and puts forward some corresponding improvement methods, with the purpose of providing scientific basis for the rational use of urban land. Methods employed include documentary data analysis and comparative analysis. The results indicate that the application of GIS in the study of urban land use is mainly the function of its powerful spatial analysis, model analysis and so on. The application of GIS in the study of urban land use is reviewed from five aspects, i.e., urban land use change, evaluation and planning, expansion and evolution, structure and optimization. The current research focuses and shortcomings are analyzed at the same time, i.e., the development trend of GIS technology and the scientific problems faced by urban land use research, the two complementing and promoting each other. At present, based on summarizing relevant theories of various disciplines and combining with the support of GIS technology, it is necessary to carry out research on the correlation between urban functions and urban land use and form a systematic urban land use theory system. Further study on the functional land use mechanism of different types of cities in small and medium-sized cities and underdeveloped areas, promote the integration of GIS technology and urban land use model library, and more effectively guide the application of GIS in urban land use research.

    Figures and Tables | References | Related Articles | Metrics
    An improved ICM algorithm for remote sensing image segmentation
    Jun YANG, Jianjie PEI
    Remote Sensing for Land & Resources. 2018, 30 (3): 18-25.   DOI: 10.6046/gtzyyg.2018.03.03
    Abstract   HTML ( 11 )   PDF (4392KB) ( 683 )

    The traditional iterated conditional model(ICM)algorithm, when applied to remote sensing image segmentation, is easy to show discrete patches and isolated points. In view of this phenomenon, an improved ICM remote sensing segmentation algorithm is proposed which is based on Markov random field(MRF). First, the robust bilateral filter(BF)which is efficient in preserving edges and denoising was merged and used for the preprocessing of the remote sensing image, and then the Otsu algorithm was applied to obtaining the initial clusters. The algorithm could overcome some problems that occurred in the traditional K-means algorithm such as the inability in determining the number of clusters, difficulty in controlling algorithm complexities, and appearance of overlapping in the segmented regions. Next, the MRF was used to describe the pixel spatial correlation forming ICM remote sensing image segmentation algorithm with contextual information. By using remote sensing image data validation, the approach proposed in this paper realizes more reliable segmentation results in comparison with the traditional ICM algorithm.

    Figures and Tables | References | Related Articles | Metrics
    Precision validation of multi-sources land cover products derived from remote sensing
    Hongli SONG, Xiaonan ZHANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 26-32.   DOI: 10.6046/gtzyyg.2018.03.04
    Abstract   HTML ( 7 )   PDF (2814KB) ( 561 )

    Global land cover maps (GLC) are essential input data for many scientific studies, so assessment of their category accuracy and category confusion is very important for some specific applications. In this paper, the authors chose China as the study region and FROM, MODIS, GLOBCOVER and ESACCI as land cover data for validation. The authors first aggregated the four GLC and referenced data provided by some international organizations into eight categories, and then validated four products through the category consistency and confusion matrix in national scale. The relative comparison between FROM, MODIS, ESACCI and GLOBCOVER shows that the four land cover products have the similar category constituent. Forest, grassland, cropland and bare land are the major land cover categories, whereas shrub, build up and water/wetland are relatively rare. Through comparing one by one between referenced data and land cover products, the authors constructed the confusion matrix, and the validated results demonstrate that FROM and MODIS have the best overall agreement with referenced data at national scale; for example, FROM’s overall accuracy is 0.69, and MODIS is 0.67, and ESACCI’s overall value is 0.65. Conversely, GLOBCOVER has the worst overall accuracy, with the value being only 0.55. Forest, cropland, built up land and bare land all have the better category accuracy, so each of them would be as input data for national forest inventory, food security and urban expansion, but shrub's category accuracy is low in four global land cover products, with confusion mainly occurring with forest, grass and cropland . The study results not only provide some scientific reference for selecting the input data for ecological environment modeling, land cover change analysis, natural resource survey, but also provide a reasonable advice for the research direction in future land cover mapping projects.

    Figures and Tables | References | Related Articles | Metrics
    Extracting road networks from high-resolution remote sensing images using multi features and methods
    Runsheng LI, Fanzhi CAO, Wen CAO, Shuxiang WANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 33-39.   DOI: 10.6046/gtzyyg.2018.03.05
    Abstract   HTML ( 13 )   PDF (4242KB) ( 508 )

    Roads on the high-resolution remote sensing images perform the stripe homogeneous region with ribbon-like shape and approximate width. According to these features, this paper presents a simple yet effective method of delineating road networks from high-resolution remote sensing images, which combines multi features and methods. The proposed method consists of three main steps. First, the mean shift algorithm is utilized to detect the modes of density of image points in spectral-spatial space which contain potential road center points and then detected mode points are classified into different classes by mean shift-based clustering on the basis of spectral information. Next, the combination of Gabor filtering and tensor encoding is used to identify the road class and to extract road center points. Lastly, road network is generated from detected road center points by means of tensor voting and connected component analysis. The experimental results demonstrate good performances of the proposed method in road network extraction, much better than the method proposed by Miao et al.

    Figures and Tables | References | Related Articles | Metrics
    Comparison and analysis of the interference identification methods for microwave measurements over snow land
    Ying WU, Sulin JIANG, Zhenhui WANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 40-47.   DOI: 10.6046/gtzyyg.2018.03.06
    Abstract   HTML ( 6 )   PDF (4928KB) ( 440 )

    The influence of radio-frequency interference (RFI) on spaceborne microwave radiometer measurements is increasingly prominent, which largely reduces the accuracy of geophysical parameter inversion from microwave observations. RFI over Antarctica land was detected and analyzed using spectral difference, normalized principal component analysis (NPCA) and double principal component analysis (DPCA) method based on AMSR-E (the advanced microwave scanning radiometer - earth observing system) Leval 2A measurements during July 1-7, 2011. It is found that, over snow or ice-covered land, the RFI signals are difficult to be detected by spectral difference method, while NPCA method works but for costal areas. However, the DPCA method works well over the Atlantic land. Furthermore. It is also found that stronger RFI signals are detected widely over the Antarctica land at low frequency channels of AMSR-E, and most of the strong RFI signals are collocated with research stations. In general, the RFI is stronger at horizontal polarization channels than those at vertical polarization channels, but in some parts, RFI signals at 10.65 GHz for vertical polarization are stronger than those for horizontal polarization.

    Figures and Tables | References | Related Articles | Metrics
    Multi-angle remote sensing image classification based on artificial bee colony algorithm
    Xuefeng YANG, Mao YE, Donglei MAO
    Remote Sensing for Land & Resources. 2018, 30 (3): 48-54.   DOI: 10.6046/gtzyyg.2018.03.07
    Abstract   HTML ( 6 )   PDF (1216KB) ( 763 )

    Artificial bee colony(ABC)algorithm is widely used in optimization field, but the study of the applications of the remote sensing image classification is inadequate. Through the use of ABC algorithm,the classification system was constructed on the basis of rules. The multi-dimensional data sets consisting of the multi-angle remote sensing observation data originating from the middle and lower reaches of Tarim River were investigated so as to generate the decision rules. A comparison with the classification results of the maximum likelihood method(MLC), C4.5 decision tree and support vector machine(SVM) shows that classification accuracy of ABC is higher than that of MLC and C4.5 overall, but lower than that of SVM. At the same time, through the frequency analysis of the classification attributes in the rules, it is proved that ABC can effectively discover the relationship between the results of the multi-angle data observation and different land cover types.

    Figures and Tables | References | Related Articles | Metrics
    Research on airborne remote sensing emergency flight organization strategy in natural disaster
    Kai CHEN, Chengfa FANG, Ru LI
    Remote Sensing for Land & Resources. 2018, 30 (3): 55-59.   DOI: 10.6046/gtzyyg.2018.03.08
    Abstract   HTML ( 4 )   PDF (1068KB) ( 475 )

    In view of the situation that airborne remote sensing (RS) has the problem of low efficiency and disorder organization in natural disasters emergency work, the authors analyzed the organizational elements of airborne RS emergency flight and, in combination with the current situation of airborne remote sensing profession in China, put forward the flight organization mode of the regional collaboration, and established emergency merit-based model based on analytic hierarchy process(AHP). The mode considers five indexes, i.e., flight time, airplane performance, operating area, remote sensing equipment, data transfer and process capability. Practice shows the feasibility and efficiency of the regional collaboration mode and merit-based model.

    Figures and Tables | References | Related Articles | Metrics
    A pixel transform-based land cover change detection approach: A case study of Beijing City
    Bing YU, Jiyan WANG, Yong SU, Dongsheng XIAO, Fuzhen LIU
    Remote Sensing for Land & Resources. 2018, 30 (3): 60-67.   DOI: 10.6046/gtzyyg.2018.03.09
    Abstract   HTML ( 7 )   PDF (4181KB) ( 732 )

    Pixel overlay and comparative methods have been widely used to detect land use/ cover change. In view of such a situation, the authors propose a pixel transform-based change detection method for land cover data in this study. This method is an extended method of pixel overlay analysis, and it supports change detection of diverse land cover types synchronously for different time phases. According to the re-definition of the type code and through map overlay analysis and zone statistical analysis for different phases of land cover maps, the authors quantified every cover changes and displayed the changes spatial distribution. Taking two phases data of Beijing in 2000 and 2010 as a study case, the authors applied this detection method for different categories of land cover with different ranges. The results show more accuracy land cover classes change, and the practicability and applicability of the extended change detection method are accordingly verified.

    Figures and Tables | References | Related Articles | Metrics
    Error analysis of soil moisture based on Triple Collocation method
    Kai WU, Hong SHU, Lei NIE, Zhenhang JIAO
    Remote Sensing for Land & Resources. 2018, 30 (3): 68-75.   DOI: 10.6046/gtzyyg.2018.03.10
    Abstract   HTML ( 10 )   PDF (3460KB) ( 861 )

    As one of the important driving parameters in hydrologic cycle, soil moisture has remarkable effect on weather variations. The development of remote sensing technology makes large-area and dynamic soil moisture observation possible, but the accurate estimation of error in remote sensing soil moisture data remains to be further studied. Based on TC method, the authors used ERA-Interim reanalysis soil moisture data and soil moisture derived from ASCAT and AMSR-E in the study area (15°N~55°N,73°E~135°E) to estimate error variance and SNR (Signal Noise Ratio) of these three soil moisture data, and also employed MODIS land cover data to analyze the error characteristics of these three soil moisture data. Study results are as follows: vegetation cover has an influence on TC method to estimate error variance and SNR of remote sensing soil moisture data; From the perspective of error variance estimation, ERA soil moisture has the highest precision, AMSR-E possesses the second place, and ASCAT is the lowest; From the perspective of SNR, ASCAT soil moisture has the highest SNR, ERA’s SNR is higher than AMSR-E and lower than ASCAT, and AMSR-E has the lowest SNR. Mostly, TC result is distributed in grasslands, croplands and barren or sparsely vegetated area through analyzing TC result related to MODIS land cover data, and TC result corresponds to objective reality.

    Figures and Tables | References | Related Articles | Metrics
    Road extraction by incremental Markov random field segmentation from high spatial resolution remote sensing images
    Ye LYU, Xiangyun HU
    Remote Sensing for Land & Resources. 2018, 30 (3): 76-82.   DOI: 10.6046/gtzyyg.2018.03.11
    Abstract   HTML ( 10 )   PDF (4312KB) ( 656 )

    Remote sensing technology has been the most effective and efficient method for extracting information from the earth surface. Roads in the high spatial resolution remote sensing images are areas with very complex road features. None road objects, such as cars, lanes and pedestrians, will change road appearance greatly, which makes road extraction difficult. The authors take advantage of Gaussian mixture model and Markov random field, which adapts to interference, to evaluate foreground and background models and label their pixels. As roads go through the remote sensing images, the areas far from the roads are useless for road extraction, and hence local incremental segmentation method takes effect. The experiments show that methods used in this paper are fairly effective.

    Figures and Tables | References | Related Articles | Metrics
    Estimating latent heat flux over farmland from Landsat images using the improved METRIC model
    Jian YU, Yunjun YAO, Shaohua ZHAO, Kun JIA, Xiaotong ZHANG, Xiang ZHAO, Liang SUN
    Remote Sensing for Land & Resources. 2018, 30 (3): 83-88.   DOI: 10.6046/gtzyyg.2018.03.12
    Abstract   HTML ( 7 )   PDF (3325KB) ( 664 )

    Estimation of latent heat flux based on thermal infrared remote sensing is of great significance in agricultural drought and water resources management. This paper examined the applicability of using METRIC model to estimate latent heat flux over farmland from Landsat images. Land surface temperature (Ts) required for estimation of the flux was computed from Landsat thermal infrared data by the mono-window algorithm. Meanwhile, an improved METRIC algorithm based on surface roughness was proposed to estimate the latent heat flux of farmland by improving the surface roughness parameters. The result of the algorithm was verified by the flux observation data from two observation stations of Huailai and Miyun in the Haihe River basin. The results show that the square of correlation coefficient (R 2) between simulated and observed values is 0.97, which is better than the conventional METRIC model (R 2 = 0.89). The improved algorithm has higher estimation accuracy of latent heat flux. In addition, the spatial distribution of latent heat flux also shows that the spatial pattern of the improved model is more reasonable. However, due to the limitation of data acquisition, only two stations in Beijing have been used to validate the algorithm, and hence further verification in other areas is needed.

    Figures and Tables | References | Related Articles | Metrics
    Extraction of hydrothermal alteration mineral groups of porphyry copper deposits using Landsat8 OLI data
    Ziyi WANG, Tingbin ZHANG, Guihua YI, Kanghui ZHONG, Xiaojuan BIE, Jibin WANG, Jiaojiao SUN
    Remote Sensing for Land & Resources. 2018, 30 (3): 89-95.   DOI: 10.6046/gtzyyg.2018.03.13
    Abstract   HTML ( 9 )   PDF (2047KB) ( 687 )

    The enhancing of NIR band and SWIR2 band of OLI data makes the spectra become the diagnostic spectra of ferric iron minerals, Al-OH and Mg-OH alteration minerals. The authors used the mixture tuned matched filtering (MTMF) mapping method to extract ferric iron, Al-OH and Mg-OH alteration minerals in Tiegelong prospective block of the Duolong porphyry Cu-Au ore concentration area. Compared with the results of mineral mapping from Hyperion data, the three mineral mapping types extracted from Landsat8 OLI are reliable. At the same time, the spatial distribution pattern of alteration minerals agrees with the hydrothermal alteration zone of typical porphyry copper deposits. The remote sensing alteration zones from interior to exterior of the Tiegelong porphyry Cu ore block are phyllic+argillic zone (Al-OH minerals) and propylitic zone (Mg-OH minerals), and the ferric iron minerals are between the arephyllic+argillic and propylitic zones.

    Figures and Tables | References | Related Articles | Metrics
    Research on automatic extraction method for coastal aquaculture area using Landsat8 data
    Yitian WU, Fu CHEN, Yong MA, Jianbo LIU, Xinpeng LI
    Remote Sensing for Land & Resources. 2018, 30 (3): 96-105.   DOI: 10.6046/gtzyyg.2018.03.14
    Abstract   HTML ( 10 )   PDF (7763KB) ( 671 )

    During coastal resource monitoring, it is an effective way to extract aquaculture region using remote sensing data, whereas the water color in coastal region is complexly influenced by the distribution difference of chlorophyll-a and total suspended sediment concentration. And it would be difficult to accurately extract the aquaculture region with complex background using traditional methods. In view of the above problem, the authors proposed an algorithm for automatic coastal aquaculture area extraction combined with spectral and spatial information of aquaculture. Firstly, orthogonal subspace projection-weighted constrained energy minization method (OWCEM) was used to enhance the information of coastal aquaculture area. Secondly, by using the spatial texture information of the coastal aquaculture area, standard deviation adaptive segmentation (SDAS) method was used to automatically extract the cultivation area. In order to verify the accuracy of the proposed algorithm, the authors selected Sanggou Bay in Shandong and Sanduao Bay in Fujian as test regions and conducted the area extraction using Landsat8 data. The experimental results show that the proposed method can rapidly and accurately identify the distribution of coastal aquaculture area in complex background color and can reach about 93% accuracy rate with a low missing rate. The method could provide a new and effective means for automatic extraction of offshore aquaculture area.

    Figures and Tables | References | Related Articles | Metrics
    A method based on harmonic model for generating synthetic GF-1 images
    Jian LIAO, Xingfa GU, Yulin ZHAN, Yazhou ZHANG, Xinyu REN, Shuaiyi SHI
    Remote Sensing for Land & Resources. 2018, 30 (3): 106-112.   DOI: 10.6046/gtzyyg.2018.03.15
    Abstract   HTML ( 10 )   PDF (6670KB) ( 529 )

    Remote sensing technology has been applied more widely and deeply with its development and, meanwhile, it has been asked for obtaining higher and higher spatial and temporal resolution. However, it is very difficult to overcome the contradiction between spatial resolution and temporal resolution of remote sensing images. Considering the influence of cloud, frog, snow and shadow, obtaining clear image with high spatial and high temporal resolution is impractical. To solve this problem, the authors proposed a method based on harmonic model for generating synthetic GF-1 images, which can take advantage of all available clear history images of GF-1 satellites to simulate the surface reflectance data at any specified date, so that obtaining time serial satellite images at any temporal frequency theoretically and overcoming the limits of methods based on fusion models for synthesizing satellite images become possible. Synthetic GF-1 images generated based on the harmonic model which will firstly establish a model parameterized by Julia date for every pixel of every band using all clear GF-1 time serial images since GF-1 satellite was launched and then the synthetic image at the specified day with the models would be generated. Finally, to illustrate the availability of harmonic model based method, the authors applied visual assessment and quantitative assessment. The synthetic images generated by this method were very visually similar to the real images and provide good result in quantitative assessment. Most difference of pixel values between synthetic image and real image ranged -0.03~0.03, and the root mean square error (RMSE) between synthetic image and real image ranged 0.02~0.05. The method based on harmonic model showed relatively high accuracy and stability, and effectively improved the temporal resolution of GF-1 images and could be applied in real production environment.

    Figures and Tables | References | Related Articles | Metrics
    An analysis of spatial distribution and optimization of rural settlements:A case study of Niejia Village in Shitan Town,Hechuan District,Chongqing
    Yuanwen ZENG, Yi DI, Yan HU, Jing CHEN, Songjiang DUAN
    Remote Sensing for Land & Resources. 2018, 30 (3): 113-119.   DOI: 10.6046/gtzyyg.2018.03.16
    Abstract   HTML ( 6 )   PDF (3534KB) ( 1031 )

    The spatial distribution optimization of rural settlement, as one of the most important contents of Overall Planning of Land Use, plays an important role in the coordination and balance of urban and rural development. Based on the spatial analysis technique and landscape ecology theory, the authors studied the distribution characteristics and influencing factors of rural settlements in village regions with Niejia Village of Shitan County as a study case. ArcGIS was employed in this study to carry out quantitative and qualitative analysis so as to select the best location of the rural settlement layout in this village. The results can provide a reference for the new rural construction, village planning, and rural settlement optimal location selection of the general land use planning.

    Figures and Tables | References | Related Articles | Metrics
    Water vapor retrieval method based on MODIS thermal infrared band and projection pursuit model
    Yitong LIN, Junfei YE, Yongqian WANG, Shiquan ZHONG
    Remote Sensing for Land & Resources. 2018, 30 (3): 120-127.   DOI: 10.6046/gtzyyg.2018.03.17
    Abstract   HTML ( 6 )   PDF (3393KB) ( 538 )

    Precipitable water vapor retrieval methods using MODIS data are mainly based on near infrared and thermal infrared data. Compared with the thermal infrared methods, the near infrared methods have higher inversion accuracy. The near infrared water vapor retrieval method is only applicable to daytime; by contrast, the thermal infrared water vapor data can be obtained both day and night. Therefore, the thermal infrared data are more suitable for operational applications. It is of great significance to improve the accuracy of thermal infrared water vapor retrieval methods. By means of variable selection experiments and results comparing experiments, the precision of variable associations were tested with the optimal substitution variable associations selected, and the water vapour retrieval method based on projection pursuit model has been found. The inversion experiment over the 2015 summer water vapor in the South United States and July 2011 in Shanxi Province of China were carried out through projection pursuit model with inverse results validated by the the water vapor detection data(WGPS). According to the results obtained, in South United States, the root-mean-square error was 2.478 mm based on the water vapor retrieval model of brightness temperature and projection pursuit. In Shanxi province of China, the root-mean-square error was 1.408 mm. Compared with thermal infrared vapor product of MODIS, it had higher accuracy; compared with MODIS near infrared water vapor product, it had higher accuracy and temporal resolution. This method has the potential of business promotion.

    Figures and Tables | References | Related Articles | Metrics
    Processing analysis of Sentinel-2A data and application to arid valleys extraction
    Bin YANG, Dan LI, Guisheng GAO, Cai CHEN, Lei WANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 128-135.   DOI: 10.6046/gtzyyg.2018.03.18
    Abstract   HTML ( 9 )   PDF (5952KB) ( 1018 )

    As a new optical remote sensing satellite, Sentinel-2A has become a hot spot in optical remote sensing applications because it has wide bandwidth, multi-spectrum, high spatial-temporal resolution and free sharing. In this study, we chose Heishui River basin as the study area and selected Sentinel-2A satellite data from European Space Agency. The authors obtained aerosol optical data, water vapor data, scene classification data and biomass factor data through analysis of data arguments, organization form, product grade and data format by using the sen2cor processing module of SNAP. The distribution areas of arid valley in the study area were extracted by using the vegetation ecological index data and digital elevation model, combined with the expert decision classification method with the analyses of biophysical index data. The result shows that Sentinel-2A satellite data have good quality in that they enrich the application field of remote sensing technology greatly. L2A level data have more positive application value for the monitoring and evaluation of global ecological vegetation environment change.

    Figures and Tables | References | Related Articles | Metrics
    Application of local spatial autocorrelation indices to the delimitation of urban heat island
    Zhenlan JIANG, Zhenbin GONG, Hui PAN, Baoyu ZHANG, Tingfen WANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 136-142.   DOI: 10.6046/gtzyyg.2018.03.19
    Abstract   HTML ( 6 )   PDF (3953KB) ( 637 )

    In this paper, two spatial autocorrelation indices were used to delimit urban heat island in Fuzhou City in a statistical sense. The effectiveness and limitation of the two indices were then analyzed so as to find effective methods for quantitative study of urban heat island. At first, land surface temperature (LST) was retrieved on the basis of Landsat8 thermal infrared data of Fuzhou City by applying 6 methods that are frequently used. Then Local Moran’s I Index and Getis-Ord local G were used to delimit urban heat island in the study area. At last the different delimitation outcomes were compared with each other and were then compared with the outcomes obtained by other methods, including equal interval method, mean standard deviation method and regional average classification method. The findings are as follows: ① Both Local Moran’s I index and Getis-Ord local G accurately delimit urban heat island. By comparison, Getis-Ord local G is more accurate in heat island delimitation and is less dependent on methods of LST retrieval. It is more comparable with other heat island delimitation methods; ② The method applying Getis-Ord local G takes into account both surface temperature and spatial correlation of temperature, which makes the delimitation outcome statistically meaningful. With its threshold value free of human factors, the method is therefore more objective and more applicable in the quantitative study of urban heat island.

    Figures and Tables | References | Related Articles | Metrics
    Application of mine remote sensing monitoring to analysis of mine goaf stability
    Xianhua YANG, Jie HUANG, Li TIAN, Bei PENG, Lixiao XIAO, Xinlong SONG
    Remote Sensing for Land & Resources. 2018, 30 (3): 143-150.   DOI: 10.6046/gtzyyg.2018.03.20
    Abstract   HTML ( 8 )   PDF (6301KB) ( 572 )

    Focused on deformation trends of mine goaf areas, the remote sensing monitoring techniques were employed to interpret and compare the multi-temporal satellite images. According to images acquired in 2009, 2012 and 2015 respectively, land cover change information including mine goaf areas, mine digging points and other land use types in the Junlian coal mining area of Sichuan Province were acquired. By analyzing the correlation between the mining exploitation environment changes and mine goaf area change trends, the authors pointed out that the status alteration of coal mining can directly affect the mine goaf change trend. On the basis of the remote sensing monitoring results, stability analysis of mine goaf areas was conducted, the continuous and newly increased deformation information was calculated, and the categorized prediction maps of mine goaf deformation trends were presented, which can assist further specified measures for mining environment protection.

    Figures and Tables | References | Related Articles | Metrics
    Change detection for mine environment based on domestic high resolution satellite images
    Lijuan WANG, Xiao JIN, Hujun JIA, Yao TANG, Guochao MA
    Remote Sensing for Land & Resources. 2018, 30 (3): 151-158.   DOI: 10.6046/gtzyyg.2018.03.21
    Abstract   HTML ( 8 )   PDF (7885KB) ( 520 )

    With the development of mine monitoring technology towards the quantification and automation, the traditional remote sensing technology based on visual interpretation is not suitable for mine monitoring. In order to improve the automation of mine remote sensing monitoring and make up for deficiencies in traditional monitoring methods, the authors constructed an object-based change detection method with high degree of automation for dynamic monitoring of mine and the surrounding environment based on GF-2 remote sensing images. The method automatically selected training samples based on change vector analysis (CVA) and extracted change information by using extreme learning machine (ELM). The experimental results show that the detection accuracy of this method is 98.73%, and it can be used in the dynamic monitoring and analysis of mine environment with highly automation. Taking the typical mine and tailings pond in Miyi County of Sichuan Province as examples, the authors carried out the dynamic monitoring of mines and the surrounding areas based on GF-2 remote sensing images. The changes of mine and its surroundings were accurately detected, which verifies the feasibility of the method and provides examples for large-scale remote sensing monitoring in mine.

    Figures and Tables | References | Related Articles | Metrics
    An analysis of landscape pattern spatial grain size effects in Qinghai Lake watershed
    Jun ZHAI, Peng HOU, Zhiping ZHAO, Rulin XIAO, Changzhen YAN, Xuemin NIE
    Remote Sensing for Land & Resources. 2018, 30 (3): 159-166.   DOI: 10.6046/gtzyyg.2018.03.22
    Abstract   HTML ( 7 )   PDF (6822KB) ( 571 )

    Watershed is the basic and important spatial scale unit of ecosystem. The scientific analysis of watershed scale landscape pattern depends heavily on the accuracy of the selection of the optimal grain size. In this paper, Qinghai Lake watershed was selected as the study area. Based on the object-oriented classification method, the authors interpreted satellite remote sensing data to generate watershed landscape data. Resampling method was used to obtain different spatial grain size watershed landscape data. Then the landscape pattern indexes were calculated and statistical relation curve was drawn between each landscape pattern index and grain size. Thus the scale effect of landscape pattern index could be identified. Finally, landscape pattern index information loss caused by increasing grain size was used to determine the optimum spatial grain size of watershed scale landscape pattern analysis. The result showed watershed landscape pattern index changed significantly with the increase of spatial grain size, but laws of change were different. Taking into account the landscape pattern spatial grain size effect and the change characteristics of information loss, the authors hold that the best spatial grain size choice of watershed landscape pattern analysis was 90 m.

    Figures and Tables | References | Related Articles | Metrics
    Research on the DEM-assisted offset tracking technique applied to glaciers movement monitoring
    Qun WANG, Jinghui FAN, Wei ZHOU, Weilin YUAN, Liqiang TONG, Zhaocheng GUO
    Remote Sensing for Land & Resources. 2018, 30 (3): 167-173.   DOI: 10.6046/gtzyyg.2018.03.23
    Abstract   HTML ( 9 )   PDF (9002KB) ( 680 )

    To improve the offset results influenced by large spatial baseline and topography when traditional offset tracking technique is applied to extracting mountain glaciers surface movement, the authors studied a DEM-assisted offset tracking technique. Two pairs of TerraSAR-X images with different baseline lengths which cover the eastern section of Chomo Lhari Mountains located in Kangmar and Nagarze County of Tibet were selected to test the traditional and external DEM-assisted offset tracking techniques in this paper. And the offset results of the two methods in ice-free region were comparatively studied. A pair of COSMO-SkyMed images acquired by different beam modes, with different incidences and covers, were selected and processed with DEM-assisted offset tracking technique. It is shown that the DEM-assisted offset tracking technique could obtain more reliable offset results than the traditional technique where the terrain is steep and the spatial baseline is large. The technique can also apply to SAR images which have different beam modes and can make more SAR data useful for glaciers surface movement monitoring.

    Figures and Tables | References | Related Articles | Metrics
    Extracting impervious surfaces from multi-source remote sensing data based on Grabcut
    Jiasi YI, Xiangyun HU
    Remote Sensing for Land & Resources. 2018, 30 (3): 174-180.   DOI: 10.6046/gtzyyg.2018.03.24
    Abstract   HTML ( 6 )   PDF (2377KB) ( 801 )

    Impervious surface is a major indicator of rapid urbanization, which leads to urban waterlogging. In this study, the authors took the advantages of multi-spectral satellite imagery and LiDAR data based on Grabcut to extract impervious surfaces. Taking the Guangzhou City as a study case, the authors reveal that the method can reach higher overall accuracy and robustness than the traditional single-source method.

    Figures and Tables | References | Related Articles | Metrics
    Spatial statistics of TRMM precipitation in the Tibetan Plateau using random forest algorithm
    Binren XU, Yuanyuan WEI
    Remote Sensing for Land & Resources. 2018, 30 (3): 181-188.   DOI: 10.6046/gtzyyg.2018.03.25
    Abstract   HTML ( 8 )   PDF (3828KB) ( 676 )

    So far, precipitation products with high spatial resolution have been crucial for the basin scale hydrology, meteorology and ecology. The climate in the Tibetan Plateau is of vital significance to global climate variation. So, the study of the distribution of precipitation with high spatial resolution is in the basic position of environmental science. Based on random-forest algorithm, the authors introduced environmental factors such as topography and vegetation, which was developed for downscaling the remote sensing precipitation products accurately and effectively. The non-linear spatial statistical downscaling model was demonstrated with the Tropical Rainfall Measuring Mission (TRMM) 3B43 dataset with the spatial resolution of 0.25°, the Normalized Difference Vegetation Index (NDVI) from NOAA-AVHRR with the spatial resolution of 8km, the Digital Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM) with the spatial resolution of 90 m and the information of slope, aspect, longitude and latitude. And the model based on time series and vegetation factor, which was demonstrated with TRMM3B43 annual data in order to forecast the precipitation, was introduced in this paper. The downscaling results were validated by applying the observations from the rain gauges in the Tibetan Plateau and the coefficient of determination R 2 is 0.89. The analytical results showed that the downscaling results improved the spatial resolution and accuracy by applying the random-forest algorithm and introducing environmental factors. And the model, which was developed for forecasting the precipitation, captured the trends in inter-annual variability and the magnitude of annual precipitation with the R 2 ranging from 0.81 to 0.87.

    Figures and Tables | References | Related Articles | Metrics
    An analysis of spatial-temporal coupling relationship between seawater intrusion and regional coastline changes in south coast of Laizhou Bay from 1979 to 2012
    Yonghui MENG, Jining WANG, Lixia ZHANG, Mei LUO
    Remote Sensing for Land & Resources. 2018, 30 (3): 189-195.   DOI: 10.6046/gtzyyg.2018.03.26
    Abstract   HTML ( 5 )   PDF (3767KB) ( 771 )

    Based on the regional seawater intrusion observation data and the remote sensing integrated observation data, the authors examined spatio-temporal dynamic change characteristics and mode of seawater intrusion and coastline evolution in the south coast zone of Laizhou Bay. Firstly, multi-period remote sensed images were used for monitoring of the regional coastline changes from 1979 to 2012. And then, the temporal and spatial features of seawater intrusion were reconstructed by digital vectorization from the historical filed survey maps. On the basis of above information, the EPR model was introduced and the spatial-temporal coupling mechanism between the seawater intrusion and coastline changes was studied and analyzed. Some conclusions have been reached: ① The regional seawater intrusion experienced a change process from rapid to slow, and the rate of invasion was slowing down after 1990. The front of intrusion line was stable since 1995 and retreated from 2008 to 2012. ② The coastal coastline is dominated by the coastal retreating coastline, besides the local artificial coastline. ③ There is a strong coupling relationship between the change of seawater intrusion frontline and coastline in time and space. The correlation coefficient is 0.407, at the significant level of P less than 0.01 (bilateral). The research results can provide data support and scientific basis for regional seawater intrusion prevention and control.

    Figures and Tables | References | Related Articles | Metrics
    Assessment of forest damage due to ice-snow disaster based on the method of threshold ratio:A case study of Hunan Province
    Xuecheng WANG, Fei YANG, Xing GAO, Yinghui ZHANG
    Remote Sensing for Land & Resources. 2018, 30 (3): 196-203.   DOI: 10.6046/gtzyyg.2018.03.27
    Abstract   HTML ( 9 )   PDF (4520KB) ( 550 )

    Ice-snow disasters are one of the main disruptions to forest ecological systems, causing the loss of forest structure and degeneration of ecological system's functions. Rapid and accurate assessment of forest resource loss has an important significance for starting the process post-disaster recovery and forest ecosystem management. Using MODIS Normalized Difference Vegetation Index (NDVI) images during 2001—2007, the authors extract pre-disaster reference value of plant NDVI and growth change threshold. In combination with post-disaster NDVI images, the range of Hunan forest ice-snow disaster is extracted by pre-disaster reference value and growth change threshold in 2008. The method of threshold ratio is proposed on the basis of method of image threshold, which is used to assess the loss of forest resources within the region of forest ice-snow disaster. A comparison with the method of image threshold shows that the assessing results from the method of threshold ratio are more close to the manual survey results, and its standard error is only 0.95, which is less than 1/3 of that of the image threshold method. The assessing results show that forest resources of the whole province have suffered serious losses: severe damaged rate, moderate damaged rate and mild damaged rate are 53.69%, 27.50% and 18.81%, respectively. What’s more, the analysis combined with topographic factors shows that forests in high altitudes are more severely affected than in low altitudes, and forests located in shady aspect are especially more severely affected.

    Figures and Tables | References | Related Articles | Metrics
    Remote sensing monitoring for temporal and spatial expansion of construction land of industrial cities in Heilongjiang
    Jingpeng GUO, Yinghui ZHAO, Huiqian CHEN, Ya’nan XIANG, Xumeng ZHAO, Chang QIAO
    Remote Sensing for Land & Resources. 2018, 30 (3): 204-212.   DOI: 10.6046/gtzyyg.2018.03.28
    Abstract   HTML ( 7 )   PDF (3140KB) ( 755 )
    Figures and Tables | References | Related Articles | Metrics
    Remote sensing analysis of temporal-spatial variations of urban heat island effect over Beijing
    Min YANG, Guijun YANG, Yanjie WANG, Yongfeng ZHANG, Zhihong ZHANG, Chenhong SUN
    Remote Sensing for Land & Resources. 2018, 30 (3): 213-223.   DOI: 10.6046/gtzyyg.2018.03.29
    Abstract   HTML ( 9 )   PDF (11553KB) ( 703 )

    In order to study the temporal-spatial variation of the urban heat island effect over Beijing since 1985, the authors utilized the 7 phases of Landsat TM/ETM+/TIRS images in summer to perform retrieval of the land surface brightness temperature so as to replace the true land surface temperature(LST). And the LST data were used for a series of qualitative and quantitative analysis of urban heat island effect to reveal Beijing heat distribution and the characteristics of urban heat island effect. Some conclusions have been reached: ① The high-temperature regions and sub-high temperature regions are continuously centralized to the urban area, but the high-temperature regions in Dongcheng District and Xicheng District show a significant downward trend, and the large scale of heat island is replaced by the small heat islands;② The influence of industrial estate on the urban heat island effect in Beijing is much higher than that of the residential district in Beijing;③ The temperature of the areas with low-rise and dense buildings and low vegetation coverage are much higher than the temperature of the areas with tall and sparse buildings and high vegetation coverage. The results of the study would play an important role in urban planning in that they provide the reference frame for the government departments to reduce the impact of urban heat island effect based on rational planning of the distribution of water, green land,industrial estate and residential areas.

    Figures and Tables | References | Related Articles | Metrics
    Research on application of unmanned aerial vehicle technology to dynamic monitoring of reserves in the Shouyun iron mine, Beijing
    Jie XIANG, Jianping CHEN, Shi LI, Zili LAI, Haozhong HUANG, Jing LIU, Shuai XIE
    Remote Sensing for Land & Resources. 2018, 30 (3): 224-229.   DOI: 10.6046/gtzyyg.2018.03.30
    Abstract   HTML ( 7 )   PDF (5676KB) ( 627 )

    An open challenge for the remote sensing community is to explore a fast, accurate and low-cost method to monitor the open-pit mining. For this purpose, the authors selected the Shouyun iron mine as the case study. Firstly, the authors implemented field campaigns and data acquisition of unmanned aerial vehicle(UAV) in August 2014 and October 2016. Secondly, the authors generated high-resolution of the digital surface model (DSM) and digital orthophoto map (DOM) by using UAV structure from motion (SfM) technology. Finally, the volumetric changes of reserves were calculated by using the algorithm of DSM of difference (DoD), and then multiplied by the average of ore-bearing rate, density of iron ore and ore grade to obtain the mined tonnage. The result shows that the UAV and SfM technology could be a fast and accurate solution for monitoring the reserves of open-pit mines. This study provides a new idea for dynamic monitoring of reserves and environment in open-pit mine.

    Figures and Tables | References | Related Articles | Metrics
    Active faults interpretation of Shannan area in Tibet based on multi-source remote sensing data
    Yangming WANG, Jingfa ZHANG, Zhirong LIU, Xuhui SHEN
    Remote Sensing for Land & Resources. 2018, 30 (3): 230-237.   DOI: 10.6046/gtzyyg.2018.03.31
    Abstract   HTML ( 10 )   PDF (12193KB) ( 568 )

    The remote sensing interpretation of active faults in Shannan region of Tibet was carried out by using multi-source remote sensing data, which showed remarkable difference from previous work. In addition, previous researches made by other people were used to study the distribution and activity of active faults synthetically. First, taking Sentinel-1 Radar images which have properties of all-weather, side looking and penetrating and Landsat ETM+ images that have abundant spectral information as master data sources, combined with high resolution GF-2 remote sensing image, the authors extracted and analyzed geological structure information at different scales. What is more, it was convenient to analyze tectonic geomorphology of active faults from different angles and levels with the help of the fusion of DEM data and ETM+ remote sensing images so as to make 3D visualization remote sensing images. Finally, the authors used a wide range of methods such as image preprocessing, image enhancement and multi-source remote sensing image fusion to reduce the multiple solutions and dubiety of active fault remote sensing interpretation. With the help of Radar and optical remote sensing respective imaging advantages, the authors clearly displayed the characteristics of active fault remote sensing image of the study area. According to the remote sensing interpretation marks of active faults, a total of 4 active faults were interpreted in the study area: the Yarlung Zangbo River fault, the Zanda-Lhaze-Qiongduojiang fault, the Sangri-Cona fault and the Darjeeling-Ngamring-Rinbung fault. The results of active fault interpretation in the study area show that the application of multi-source remote sensing data could greatly improve the accuracy and credibility of the interpretation of active faults and provide a reference for later researches on the study area.

    Figures and Tables | References | Related Articles | Metrics
    Research and construction of interpretation result data management system toward remote sensing application
    Xinxin SUI, Suwen SUI, Kun LIU
    Remote Sensing for Land & Resources. 2018, 30 (3): 238-243.   DOI: 10.6046/gtzyyg.2018.03.32
    Abstract   HTML ( 6 )   PDF (2831KB) ( 448 )
    Aim

    ed at tackling the problems of data storage, management and application of remote sensing interpretation, and considering the needs of geological survey information service system, the authors established interpretation data system toward remote sensing application. Through the effective organization of map data, element layers and texts, with ArcGIS 10 and MapGIS K9 as the platform, and by using C# as the development language, the authors designed and constructed the database management system of remote sensing interpretation which is based on C/S mode. This system provides the flexible tools of importing data, query display and data system construction and maintenance. This system realizes the integrated management and service of the multiple format maps that are in scattered storage which ensures the effective utilization and sustainable development of the resources of remote sensing interpretation data.

    Figures and Tables | References | Related Articles | Metrics
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech