Low carbon economy, a new model for social and economic development, is based on making full use of clean energy. The utilization of bioenergy can provide dependable fuel for big or middle electricity-generating factories. It is very meaningful at present, because the fossil fuel is exhausted increasingly. This paper utilized MODIS standard product MOD 17 obtained from NASA Science Research Team to get the NPP of Guangdong province. In combination with land cover data created by TM images, the authors got the paddy’s biomass distribution map and some statistical data. The best locations for paddy’s bioenergy factories in Guangdong province were also determined by using Zonal Sum and Location-Allocation models in the ArcGIS. The results show that two cities (Zhaoqing and Chaozhou) and their neighborhood areas are suitable for bioenergy industry. The quantitative analysis of the paddy’s bioenergy in Guangdong Province can provide valuable information for low carbon economy in the future.
Hydrocarbon micro-seepage is a common phenomenon over oil and gas reservoirs. Remote sensing data are important sources in extracting seepage information for the exploration of oil and gas resources. This paper presents the theory of hydrocarbon micro-seepage and describes different manifestations of hydrocarbon micro-seepage at continental surface, in offshore area and on sea surface. An overall discussion is given in this paper concerning the research progress and the development trend of the remote sensing technology in China.
With the development of science and technology, 3S technology has been more and more widely applied in various disciplines and research fields. In the land supervision, the application of 3S technology can produce more dependable data for land supervision to follow and make land supervision more efficient and powerful. This paper has studied all the work done by Bureau of State Land Supervision and summarized the application and enforcement of 3S technology in land supervision in detail with the purpose of making researchers in the field of land management better understand the work of land supervision. Some examples given in this paper show that the application of 3S is very important in land supervision. This paper also discusses some problems existent in the land supervision system based on 3S technology and gives corresponding solutions. This paper can provide reference for further improvement and optimized designing of the information system for land supervision.
The quantification of factors for landslide is very complex. Under different circumstances, the contribution of the same factor to landslide may be quite different or even opposite. Based on an analysis of the specific landslide data obtained from Yongjia County, the authors put forward a quantification method for building Neural Network, which is based on the distribution of landslide samples. The results from several estimation models were compared with each other. It is proved that the quantification method advanced by the authors and the Neural Network model based on Supported Vector Machine are the best means. The correctness is up to 84.2%, which is satisfying. According to the estimation result, the quantification solution and the estimation model based on it are very useful.
Image fusion is the essential way to integrate the advantages of panchromatic and multi-spectral data of high spatial resolution remote sensing imagery. The comparative study of the present image fusion methods emphasizes the visual effect of the fused imagery and pays less attention to the processing and application steps such as segmentation and analysis which are subsequent to image segmentation. With QuickBird imagery of a place in Beijing as the test data source, the authors combined the quantitative analysis with the study results of fusion and segmentation experiments and performed a comparative study of such pixel-based main fusion methods as IHS, PCA, HPF, Wavelet-PC, Ehlers and GS in the aspects of spectral and geometric features. It is shown that evident differences exist in terms of visual effects and quantitative indices of fused imagery derived from different fusion methods, and that, of these methods, GS seems to be the best.
With Ganzhou area in Jiangxi province as the study area, this paper deals with the methods for extracting clay information from Hyperion data. Based on studying advantages and disadvantages of Spectral Angle Mapper (SAM) and Matched Filtering (MF), the authors have developed a method that combines SAM and MF to fix the information of all kinds of clay minerals in the study area. The results show that this method can be successfully used to Hyperion data and can totally integrate SAM with MF by combining their advantages, remedying their shortcomings, and accurately extracting the weight of information of clay minerals from the background image. In addition, the major parts of the weights of the locations and types of clay are consistent well with the sampling locations and the analytical results of the samples, suggesting the feasibility of this method.
The sensor with Ultra-Width has become an important data source. The method for utilizing the commercial remote sensing disposal software to accomplish the orthorectification of the remote sensing image with wide breadth has aroused much attention. BJ-1 small satellite multiple spectral images were used as an example to discuss the technology of orthorectification, and the influencing factors of the product’s geometrical precision using the Generic Pushbroom Model(GPM) and Rational Function Model(RFM) were also comparatively tested in this paper.
The authors studied the feasibility of estimating Leaf Area Index (LAI) of the crop by using intensity and texture characteristics of SAR, and analyzed the texture characteristics of SAR which have relatively high correlation with LAI. In this study, six texture characteristics calculated from ENVISAT-ASAR image were selected and compared with measured LAI of the corn. The results show that the texture characteristics of HH polarization for gray level co-occurrence matrix have higher correlation with the LAI of corn than those of VV polarization. Dissimilarity of HH polarization and skewness and homogeneity of VV polarization are significantly related to LAI. In combination with backscattering coefficient, multiple regressions of two formulae were computed respectively, and the correlation coefficients are 0.68 for HH polarization and 0.87 for VV polarization. It is thus held that the methods discussed in this paper have potential application values in the estimation of the crop Leaf Area Index.
With Yongan City of Fujian Province as the study area, the authors investigated the best VIs for estimating LAI of masson pine. Several VIs were calculated from the IRS-P6(LISS-III) image, which included DVI， EVI2，MSAVI， NDVI， RDVI， RVI and TNDVI. The correlation between the measured LAI of masson pine using LI-COR LAI-2000 and VIs was established， and the effects on the LAI of masson pine were studied. The LAI estimation models based on different VIs were quantitatively analyzed with both R2 and standard error. The estimation models included linear model， quadratic curve model，exponential curve model and power curve model. The results show that there exists curvilinear correlation (exponential correlation or power correlation) between selected VIs and LAI of masson pine. The exponential curve model and the power curve model constitute the best inversion models， and TNDVI， NDVI and RVI are fairly good for inversing LAI of masson pine， in which the R2 of the exponential curve model and the power curve model are all larger than 0.76 and their verification R2 are all larger than 0.84， but the standard errors of RVI's inversion models are much larger than those of the other two models. In general，both the exponential curve model and the power curve model of TNDVI and NDVI can yield good results in estimating LAI of masson pine.
In the dynamic monitoring based on RS image data，the Pseudo Invariant Features (PIF) method is often chosen by domestic researchers. However，when the RS image data are lack of temporally invariant features，they would make interference errors because of temporally variant features. Some mining environments contain large areas of vegetation and less areas for inhabitants. In such cases，the PIF method doesn’t work when it is used for relative radiometric normalization in the mining environment. The Temporally Invariant Cluster (TIC) method is thus introduced in this paper. TIC is a simple and effective method which creates a regression function thorough the high density of the temporally invariant features, so it wouldn’t be interrupted by the temporally variant features and is suitable for mining environment dynamic monitoring. The study area is a polymetallic ore deposit in southeast Hubei Province. The image is based on TM data. The TIC method was used in the NDVI. It is proved that this means can effectively reduce the radiometric difference, and that further analysis can be carried out based on the results obtained.
The nuclear power station needs to drain a mass of cooling water to the near-sea area during its operation. Its influence on surrounding environments and the running of the station itself needs further research on the distribution and the features of the sea surface temperature field in different seasons and under different tide conditions. The research can also validate the effect of the cooling water and the Temperature Drainage Mathematic Model as well as the Physical Analogue Model. The authors carried out airborne thermal remote sensing survey of the temperature field near the nuclear power station in the belief that airborne thermal remote sensing survey has the advantage that it can obtain high resolution sea surface temperature under different tide conditions. Data processing was carried out, and the result can provide reference and ideas for thermal drainage remote sensing survey of the nuclear power station.
Leave water reflectance is an important parameter in the study of water optical characteristics. To better interpret the effect of cyanophytes contamination on water optical characteristics, the authors conducted in situ measurement of spectral reflectance and water sampling in the Taihu Lake on 10 and 11, November 2008. Remarkable effects were observed in leave water reflectance of the cyanobacterial water, leading to an obvious absorption peak in the red region and an increase in the near-infrared region. Equivalent leave water reflectance based on FY-3A and MODIS band settings was derived by using the spectral response functions. Furthermore, the authors used the Ration Index (RI) model for the estimation of chlorophyll-a on 12, November 2008, and observed high determination coefficients R2=0.72, which were further used to map the chlorophyll-a distribution. The results obtained will be helpful to the further evaluation of optical characteristics and water quality.
Remote sensing technology can play an important role in metallogenic prognosis. The study of foundational geology and ore-forming theory is the basis of metallogenic prognosis. The theoretical innovation of metallogenesis will expand the scope and direction of ore prediction, and can change the traditional prospecting thoughts. Remote sensing technology has much superiority over conventional geological investigation in such aspects as the ore-control factor interpretation, the extension of the mineralization belt, the tone anomaly caused by mineralization, the annular imagery controlled by mineralization，the geomorphic feature for prospecting, the mineralization information extraction and the comprehensive analysis of multi-source geoscience information. According to the results of ore prediction conducted in western China, this paper sums up a set of metallogenic prognosis methods and procedures based on remote sensing technology.
At 14:30 on June 28, 2010, continuous heavy rainfall caused enormous landslides at Gangwu of Guanling County, Guizhou Province. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources immediately collected pre-landslide correlative satellite data. At the same time aerial data for the landslide whose resolution was 0.08m were obtained successfully on June 30. Using these high-resolution image data and digital elevation model, the authors adopted digital landslide technique to interpret the landslide information from the quantitative point of view on influence sphere, sliding direction, size, casualty loss and so on. At last, a series of quantitative data such as landslide area, slump scale, debris accumulation scale, damaged plantation area and buried building number, were obtained in time. The results can provide timely abundant and accurate data for front-line succor and disaster management. Based on these data, the authors hold that the Guanling landslide should be regarded as a rare large complex debris flow landslide, which had never happened before in Guizhou Province.
Research on the quantitative remote sensing detection of the Rujigou coal fire area in Ningxia by using the night-time airborne hyperspectral imagery is reported in this paper. Based on synchronous measurement of spectra and temperature，the author performed the spectral analysis and information extraction of indicated ground objects and thermal anomaly for defining the right thermal band for temperature simulation，simulation formula and minimum anomalous temperature，with the detection precision attaining the 1∶2 000 scale. The coal fire area was delineated and the combustion intensity was detected accurately. The author also analyzed the thermal diffusion regularity and the corresponding relations between the remotely sensed thermal anomaly and the underground coal fire anomaly，and achieved the goal that remote sensing quantitative detection results could be directly applied to the design of fire-fighting engineering.
In this paper，topographic maps，aerial photos and satellite remote sensing images were used to analyze the changes of the Beijing-Hangzhou Grand Canal (Hangzhou Section). The result shows that, through several times of expansion and renovation from 1955 to 2007, the length of the canal was shorten from 21.05 km to 16.23 km, the water area was expanded from 0.76 km2 to 1.03 km2, and the average river width was expanded from 36.10 m to 63.46 m. In canal buffer area (r=2 km), the urban construction area was increased from 31% to 68%, the agricultural land was decreased from 61% to 16%, and the industrial land was increased from 8% to 16%. An analysis of the changes of the industrial land surrounding the canal reveals that industry in Hangzhou has been dependent on the canal. The canal and the Qiantang River re-engineering project has changed the river way of the canal. The distribution of industrial land was changed from 1988 to 2007, although the proportion of the total industrial and mining land area remained 16%. The area near the old river (the abandoned river) was decreased from 2.77 km2 to 0.82 km2, while the area near the new river was increased from 0.74 km2 to 3.38 km2.
In this paper，the MOD10A1 and Landsat-5 TM images were used as the basic data，and the snow information was extracted from Landsat-5 TM with SNOMAP developed by Hell et al.. Furthermore，a comparison between the MOD10A1 data and the classification map from Landsat-5 TM was made，and the quality accuracy of MOD10A1 was calculated at three statistical sample scales (50 pixel × 50 pixel，10 pixel × 10 pixel and 3 pixel ×3 pixel). The results show that, with the decrease of statistical sample scales，the statistical classification accuracy of snow in MOD10A1 images decreases，and the mean quantity accuracies at 50 pixel × 50 pixel，10 pixel × 10 pixel and 3 pixel ×3 pixel scale are 0.94，0.87 and 0.80 respectively. These data suggest that，limited by the spatial resolution，there is an efficient or optimum scale when MOD10A1 is applied. Meanwhile，the statistic results show that, with the decrease of the statistical classification accuracy，the stability of the MOD10A1 gradually becomes lower.
To achieve the remote sensing dynamic monitoring of land use in Duolun County, this paper tried to apply knowledge-based remote sensing information extraction technology to this area. Through an in-depth analysis of spectral characteristics, the main cover types were decomposed by the linear spectral mixture model and a number of thematic information models were set up. Extraction rules of all types were set up based on empirical knowledge, and then land use information of Duolun was extracted automatically on a computer. By analyzing the two remote sensing survey results, the information of the land use dynamic changes and conversions between different land use types was obtained. The results show that the previous “three-three” system of land use structure has been broken and the development trend of desertification has been effectively contained. Finally, some proposals on using land rationally are put forward.
The Huludao mining area in Liaoning Province was chosen as the study area. In this paper, grid method, vector polygon method and buffer method were used to conduct the assessment of mine geological environment in Huludao. Results of the assessment were comparatively analyzed, and the vector polygon method yielded the best result. It is thus held that the vector polygon method can be used to perform mine geological environment assessment in this area.
Based on comparing the capabilities of different water indices in monitoring water status of wheat, the authors selected the best indices for different periods. Using the data of wheat spectra and water status observed in a whole growth season of wheat, the authors calculated five popular water indices, i.e., NDVI, NDWI, GVMI, PWI and WI, and conducted a correlation analysis between these indices and EWT (Equivalent Water Thickness) as well as FMC (Fuel Moisture Content). The Results show that, in the early period of wheat growth, FMC is better than EWT in reflecting water status of the wheat, whereas in the late period, EWT is more suitable. Different periods have different best water indices, and the correlation between indices and water status tends to experience an increase in early periods and decrease in later periods. In the application, therefore, we should choose different indices for different periods.
With remote sensing and GIS technology, the spatial-temporal characteristics of rural settlements of Shandong Province during the period of 1980s-2005 were analyzed from the aspects of structure, morphology, spatial scattering and change intensity. Five indices were chosen, which indicated the change value of the area proportion, bi-directional change value, relative change rate, the change of aggregation value and the stability change of rural settlements of every city in Shandong Province respectively. Based on these indices, 17 cities in Shandong Province were classified into 3 classes quantitatively and objectively by using the hierarchical cluster method. The first class includes Dezhou City and Binzhou City, which have the maximum stability change value, the highest relative change rate, the fast dynamic change speed, the biggest aggregation change value and the smallest structure change value. The second class includes Zaozhuang City, Tai’an City and Heze City, which have the minimum stability change value, the lowest relative change rate, the slowest dynamic change speed and the biggest structure change value, and the middle-level morphological and aggregation change value. The other 12 cities belong to the third class, characterized by the middle-level rural resident land structure change value, stability change, relative change rate and dynamic change speed, and the minimum aggregation change value.
MODIS data with high spectral and temporal resolutions were used as input parameters for regional land cover classification in China. First, EVI, NDWI and NDSI were calculated as input spectral features on the basis of an annual time series of twelve MODIS 8-day composite reflectance images (MOD09) acquired during the year of 2007. The three indices were added to the image form a 10 spectral bands image. The authors employed the mean Jeffries-Matusita distance as a statistical separability criterion and classification accuracy of SVM to evaluate the contribution of different bands for land cover classification. Once the aim was achieved, the monthly three largest contribution spectral bands (EVI、B7 and B4) were dealt with. The Principal Component Analysis (PCA) method and its first three principal components were used as input parameters for SVM classification. The result shows that the three largest contribution spectral bands together with temporal information as input parameters can reach certain high classification accuracy (78.04%) at moderate spatial scales without other accessorial data.
Aimed at improving the accuracy and efficiency of shallow groundwater exploration and opening up a new way to seek groundwater by remote sensing, this paper presents a new fusion algorithm based on Principal Component Analysis (PCA) and Wavelet Transformation (WT) by using Landsat-7 ETM data (spatial resolution being 30 m) and Envisat-1 ASAR data (Wide Swath Mode, spatial resolution being 150 m) as the main fusion data. According to the new fusion algorithm, anomaly information of shallow groundwater was successfully extracted. In combination with field investigation, geophysical exploration and drilling, the forecasting results of rating I, II and III were in accordance with the actual state, and rich shallow groundwater was found. It is thus concluded that the method has some feasibility and practicability, and can serve as a new technique for rapid exploration of groundwater in the future.
With the development of the polarimetric Synthetic Aperture Radar (SAR), the research on the land cover classification using SAR data has developed rapidly. However, the classification accuracy is seriously affected by the speckle noises on the SAR image. A new method combining the advantages of multi temporal SAR data and quad-polarization SAR data is presented in this paper. A method of multitemporal SAR data fusion was used to eliminate the effect of the speckle noises on the SAR image. An area of 12 km×17 km was selected as the test area. 6 multi-temporal RADARSAT-2 images were used in this study to conduct the land cover classification. The results show that different land cover types represent different backscattering mechanisms, and the backscattering coefficient value of different land cover types varies as a function of time. Based on the fusion result of multi temporal polarimetric SAR data, the authors fulfilled the land cover classification, and the results show that this method can effectively distinguish such objects as man-made buildings, forests, farms and land and water. The speckle noise is obviously reduced and the visual appearance of the SAR fusion image is obviously improved.
Based on a spectral characteristic analysis of typical wetland plants, the authors used the object-oriented classification method to extract such specific plants in Hanshiqiao area of Beijing as Phragmites australis, Echinochloa crusgallii and Nymphaea tetragona on the basis of a lot of survey work. First, the authors collected spectral data of these three typical wetland plants in the field, which constituted the basis of spectral correlation analysis and could help make classification between different species. The correlation analysis results of highly distinct spectral band combination and vegetation indexes with remote sensing images were involved in segmentation weight assignment. Second, based on the distribution of typical plants, the authors decided the split-scale of object-oriented (Phragmites australis split-scale being 50, Echinochloa crusgallii split-scale 20, and Nymphaea tetragona split-scale 100). A comparison of different classification methods shows that the classification accuracy of the object-oriented method based on spectral features is about 96%, and the classification accuracy is 87.3% in case it is not based on spectral characteristics. Traditional supervised classification accuracy is only 82.3%. The results show that the object-oriented classification method with spectral feature analysis is effective in the information extraction of Hanshiqiao wetlands typical plants, and the differentiation between spectral bands as well as band combinations will play a key role in that it can highly improve the accuracy of classification.
The combination of GIS and environmental models to evaluate the quality of atmospheric pollution dispersion modeling and assess the atmosphere air quality has become a hot research point, which has the advantages of GIS spatial analysis and spatial data visual management. This technique can express the analysis and prediction of all kinds of pollution sources macroscopically and microscopically and can thus realize the visual management of atmospheric pollution dispersion evaluation and provide a plan of decision support for engineering decision-maker and management personnel. The atmospheric pollution dispersion simulation and evaluation system utilizes the integration technology of ArcEngine and .Net to achieve the management of maps, atmospheric pollution dispersion simulation, evaluation and so on. The system brings the advantages of spatial analysis and data processing based on GIS into full play, and accomplishes the visual management of atmospheric pollution. The authors have developed a set of application-oriented and operation-flexible software of atmosphere evaluation and simulation systems for evaluation and decision institutions.
The structure and function of the early warning system for regional grain production safety on the basis of ArcGIS Engine are described in this paper, and a model for grain production safety pre-warning is proposed. With Northeast China as an example, the authors carried out an analysis and appraisal of grain production safety based on the system. The result shows that the regional early warning system for grain production safety on the basis of GIS can realize the effective monitoring of regional grain-production and achieve the aim of pre-warning of grain production safety. Hence it has certain theoretical value and practical meaning in guaranteeing the regional grain production safety.