With the increase in the development and application of geological remote sensing technology,a lot of research and surveying results have been achieved in various fields of geological investigation,which have laid a foundation for the formulation and revision of the standard system of remote sensing geological survey. To a certain extent,the lack of the standard system of geological remote sensing survey has long affected the width and depth of geological remote sensing investigation; in consequence, it is difficult for remote sensing geological survey to meet the urgent need of national geological tasks. In response to these circumstances,the authors, on the basis of analyzing new geological remote sensing development and application and analyzing and sorting out the problems of existing technology standards,propose in this paper the general idea,main tasks,system construction,concrete content and future vision of building a technical standard system for remote sensing geological survey(TSSRSGS)to accelerate the system construction of geological remote sensing survey and promote the geological remote sensing survey technology and its application to a new level.

Forest biomass is very important in the study of carbon cycle at the earth’s surface, and hence its accurate estimation has great significance for the problem of the global and even regional forest conditions and climate environments. Due to its unique imaging mechanism, all-weather all day long properties and penetration capability of the forest canopy, synthetic aperture radar (SAR) plays an enormous role in forest resources management and forest mapping research. This paper first summarizes the traditional forest biomass estimation methods in the forestry and the methods based on the optical remote sensing data and LiDAR data, and then deals with the forest biomass inversion methods from such angles as SAR backscatter (different polarization mode), interference coherence, and polarization interference. The advances and development trend for forest biomass estimation based on SAR are also summed up in this paper.

With Jiefang gate irrigation area of Hetao region in Inner Mongolia as the research district, and the biomass, the soil water and the relation equation between them in the measured values as the research foundation, the authors set up a regional evapotranspiration retrieving model based on the Radiation Use Efficiency (RUE). The SEBAL(surface energy balance algorithm for land) model was taken as the referenced model to make a comparative analysis between the regional evapotranspirations in the same period. The results showed that the spatial distributions of evapotranspiration estimated by using the RUE method and the SEBAL model were similar in spatial distribution and texture features, and there only existed insigficant differences between the calculated results of the two models. The correlation coefficient between the RUE method and the SEBAL model was remarkably improved in comparison with that of the DSSAT(decision support system for agrotechnology transfer) method and the SEBAL model. It is also proved that the regional evapotranspiration can be better retrieved by the RUE method, with the retrieving accuracy obviously higher than that of the DSSAT method, and hence this method is a new and effective method for monitoring regional evapotranspiration.

Aiming at reliable registration of remote sensing images,the authors present in this paper a remote sensing image registration method based on improved ORB (oriented brief) algorithm. The proposed method mainly includes three stages:The first stage is feature matching, the improved ORB algorithm is used to detect features and build descriptors,and the descriptors are matched to obtain initial control points. The second stage is to employ RANSAC (random sample consensus) processing via transformation parameters estimation to remove possible wrong matching points. The third stage is to rectify the image based on the transformation parameters calculated by the least square method. The proposed method is evaluated based on two sets of optical and SAR remote sensing images,and is compared with the registration methods based on SIFT and SURF algorithm. The results show that the method proposed in this paper can provide the same accurate remote sensing image registration result as or even the higher result than the methods based on SIFT and SURF algorithm,and can obtain improved efficiency.

To tackle the problems existent in road information extraction from high resolution remote sensing, the authors put forward an improved approach to road extraction based on watershed segmentation according to the basic theories of object-oriented method and mathematical morphology. Firstly, the image is processed by improved watershed segmentation to extract basic road information after preprocessing. Then object-oriented method is used to extract road per-parcel so as to optimize the road extraction results. Finally, after binary image processing, the incomplete results can be removed and corrected by using mathematical morphological transformation. Experimentation shows that the proposed method can extract urban road information efficiently and process the roads from the complex urban context fairly satisfactorily.

Coupled plant leaf spectral model PROSPECT, vegetation canopy spectral model SAIL(scattering by arbitrarily inclined leaves) and atmospheric radiative transfer model 6S(second simulation of the satellite signal in the solar spectrum)were used to simulate the top of atmospheric(TOA) reflectance of vegetation under different conditions. And then the influences on the spectrum of the leaf mesophyll structure parameters, chlorophyll content, leaf dry weight, leaf water content, plant canopy of LAI, solar zenith angle, aerosol optical thickness (AOT), adjacency effect and mix-pixel effect were analyzed. The research results show that the vegetation TOA reflectance error caused by the atmosphere is by far larger than the error caused by the biochemical parameters of plant itself. At the leaf level scale, the main factors causing reflectance change are chlorophyll content and mesophyll structure parameters, the effect of water content is very small on leaf reflectance in 400~900 nm. At the canopy level, the main factors causing spectral change are LAI and leaf angle distribution.

In this paper, hyperspectral remote sensing technology was applied to the quantitative study of the relationship between the reflectance spectra of vegetation and vegetation moisture content, and reliable data were obtained for the study of vegetation water content as one of the "Eco-water" information parameters. Sensitive bands were extracted by relevance analysis and stepwise regression of the reflectance spectra and the moisture content of palm leaves collected in the sampling points. In avoidance of the interaction of sensitive bands, the relationship between principal constituents and moisture content was identified as a transition in the first place by extracting principal constituents using principal component analysis, the regression equation of every principal component and standard variables was established, the equation of regression between every standard variable and original variables was also established and, finally, the model of the relationship between vegetation moisture content and reflectance spectra was obtained from translating the transition model. The results showed that the reflectance spectra of palm leaves had significant correlation with vegetation water content at 454 nm, 668 nm,1 466 nm,1 664 nm and 1 924 nm, and that the relative correlation between the predicted values obtained in the niche model and the monitoring values was 0.92, with the root mean square error being 0.06.

The estimation of aboveground biomass (AGB) is necessary for studying productivity, carbon cycles, nutrient allocation, fuel accumulation in terrestrial ecosystems, and rangeland management and monitoring. In this study, AGB estimate models were developed for 3 major grassland types (alpine meadow, alpine steppe, and temperate steppe) in the Tibetan Plateau by integrating AGB data collected from 6 sites in central Tibet in 2004 and concurrent vegetation index (VI) derived from MODIS data sets. The results show that MODIS VI is more suitable for estimates of alpine meadow and alpine steppe. The cubic polynomial regression based on NDVI is the best estimate model for alpine meadow with the correlation of 0.82, while for alpine steppe the model is EVI based cubic polynomial regression model with the correlation of 0.83; due to strong spatial heterogeneity of temperate steppe in central Tibet, the relationship between AGB and VI for temperate steppe is poorer than that for alpine grassland (alpine meadow, alpine steppe). The MODIS VI based estimates of AGB during the growing season is better than the total biomass; during the growing season the correlation between AGB of alpine grassland (alpine meadow and alpine steppe ) and MODIS VI is higher than 0.8 with a maximum value of 0.92, and for temperate steppe it is above 0.67 also. In contrast, NDVI is the best vegetation index for AGB estimates of alpine meadow and temperate steppe while EVI is the best for alpine steppe. Due to unique spectral response of green vegetation, MODIS VI is more suitable for estimates of AGB during the growing season, and the accuracy of AGB estimates will decrease during the non-growing season. For the same types of grassland with less difference in AGB, the linear or polynomial regression model is more suitable for modeling or estimating AGB in the Tibetan Plateau than other estimate models.

This paper proposes a object-oriented change detection method based on the characteristic mapping pattern analysis. The method is improved from the information transfer model of remote sensing image interpretation. The image objects are acquired by the vector auxiliary data. The spectral and texture features are extracted, and an unsupervised clustering method is used to obtain the characteristic clusters of the objects. According to the priori information which exists in the auxiliary data, the mapping between the multi-temporal feature clusters is analyzed class by class. Then, the change object, whose mapping mode is inconsistent with other objects of the same class, can be identified. The experiments prove the feasibility and effectiveness of the proposed method, and the results show a new way for the object-oriented change detection.

In order to extract the information of earthquake damage from multi-source images, the authors explored a high-accuracy algorithm of automatic image registration. Firstly, It uses Moravec operator to extract feature points and uses random sample consensus (random sample consensus, RANSAC)algorithm to reject mismatching points. Secondly, it makes a log-polar transformation according to the feature points to obtain the rotated angles and the scaled factors of the reference image and the image to be registered. After compensating coefficients of the rotated angles and the scaled factors, it uses an algorithm of sub-pixel level and phase-correlated to calculate the offset between the images and uses the interpolation algorithm to resample the registration image. At last, the images before and after the earthquake are processed as classification targets. They are used to classify and extract the earthquake damage information based on the features. The results show that the designed algorithm in this paper is of the high robustness and registration precision, and is more suitable to the registration of multi-source remote sensing images. The information of earthquake damage can be better applied to the assessment of the earthquake damage than before.

High resolution SAR image is different from the previous low resolution SAR images in that the former is more seriously influenced by objective complexity and imaging factors such as noise, thus resulting in damage to target detection. The utilization of the high resolution SAR image therefore becomes more difficult. The traditional methods applicable to low resolution SAR image extraction are hence no longer suitable for high resolution SAR images. In order to accurately extract the damage information from high resolution SAR images, the authors, starting with the SAR imaging mechanism and backscatter characteristics, analyzed characteristics of earthquake damage to buildings, roads and bridges, and the results obtained provide the train of thought for target detection and the method for extraction.

The multichannel dual-polarized radiation characteristic database of corn vegetation canopy was constructed by using the corn structure parameters field measured data and the Matrix-Doubling model, and the relations between the emissivity and the transmissivity of the corn canopy were obtained using regression analysis based on the database. These relationships were applied to the microwave radiation propagation equation to compute the microwave radiation bright temperature of the surface covered with corn canopy. The results show that the correlation of the measured LAI value and the model inversion LAI is higher than 0.9, which suggests that the multichannel passive microwave data have considerable application potential in the aspect of corn LAI inversion.

With Luobusha ophiolite as the study case and on the basis of remote sensing data of ETM and ASTER,the authors used the ratio and principal component analysis methods to extract the altered mineral information of iron-stain alteration(magnetite and olivine)and that of hydroxyl alteration(serpentine and chlorite)respectively so as to study the utilization of remote sensing technology to recognize and extract the rock and altered mineral information of ophiolite. In addition, pure pixel index(PPI) method was employed to extract endmember spectrum. In combination with the available field lithologic information,dunite was distinguished from peridotite by methods of spectral angle mapper (SAM) and spectral feature fitting(SFF). On such a basis, the spatial distribution of Luobusha ophiolite rock and its main altered minerals was determined. The results of comparative analysis show that rock and mineral information extracted by different methods and different data types can be verified reciprocally. The extracted information of dunite and peridotite is well consistent with the extracted information of iron-stain alteration and hydroxyl alteration and is also coincident with the result of the ground survey. The results of this study show that the methods proposed in this paper are feasible for extraction of ophiolite rock and mineral remote sensing information, and have good geological effect.

With the "Zhongxi-1 Glacier" in Nagqu County of Tibet as the study area, the authors carried out pretreatment and filtering classification of airborne LiDAR point cloud data obtained in August 2011 and extracted DEM of the study area; 3D terrain simulation was conducted by airborne hyperspectral DEM data in comparative correlation respectively with DEM vector data and raster data. At the same time, based on the classification results of maximum likelihood method using the DEM hyperspectral data, ortho-rectification was performed, and thus digital orthophoto map (DOM) was obtained. Finally, the DOM and the airborne LiDAR point cloud data were combined to extract the snowline of "Zhongxi-1 Glacier". The results show that, through data fusion by using the advantages of the airborne hyperspectral data and the airborne LiDAR data, the snowline of the glacier can be extracted more easily, and the height of the snowline can be better displayed.

Airborne LiDAR technology provides large quantities of three-dimensional point clouds coordinates for detecting buildings. To effectively identify the building region from the vegetation, the authors adopt a progressive densification TIN method to filter no-ground points. After removing some point clouds whose height is less than 3m from ground surface and isolated point clouds, a binary grid cell is produced based on no-ground points. Next, defined segmentation operators are used to disconnect the possible link between buildings and vegetation. Two kinds of regions are clustered based on height difference criteria using the region growing method. Then building regions are extracted according to large slope density values. Finally, a morphological closing operator is applied to fill small holes and smooth edges of extracted building regions. Three typical areas with complex urban conditions were selected to test this algorithm. The results show that this algorithm gives a comparative performance with a precision of over 91 percent in quality and completeness. The results also demonstrate that this algorithm can automatically recognize buildings.

Aerosol is an important factor which not only influences land-atmosphere energy balance and climate change but also affects the environmental quality of human life. Based on TM image of Landsat 5, the authors built up a look-up table by 6S atmospheric radiative transfer model, and then got the aerosol optical depth (AOD) of the dark pixels based on regression analysis. After that, the spatial distribution of AOD over Nanjing City was calculated by kriging interpolation. The results were tested by atmospheric correction and an analysis was made on the inversion results at last. The results show that the TM images, which have a higher resolution, can be used to retrieve AOD accurately through the "dark pixel" method, that the AOD value in the north of Nanjing is relatively higher than that in the south, that the distribution of vegetation, urban area and elevation in Nanjing City is the main factor influencing the distribution of AOD, and that high resolution images are capable of obtaining more details of the spatial distribution of aerosol than low resolution images in the urban area.

Problems such as complex algorithm, heavy computation and low efficiency occur when Forman method is directly used in the implementation of HJ-1A real-time hyperspectral data processing system. In this paper, an improved method is proposed. With this method, phase calculation is simplified and, at the same time, the calculation process is optimized by using the property of Fourier transform of the complex sequence and the conjugate symmetry of Fourier transform of real sequence. On the basis of analyzing the amount of floating point operations of the algorithm key step before and after the improvement, the improved method is eventually realized based on the graphic processing unit (GPU) as the experimental subject to HJ-1A hyperspectral data. The results show that the operating speed of the improved Forman algorithm is increased by 11.86% in the case of the same calculation accuracy. Thus, the improved Forman algorithm can provide an effective way to realize the HJ-1A real-time hyperspectral data processing system.

The distribution, eco-service functions and the managements of wetlands especially for metropolis have a close relationship with the quality of eco-environments and city resident life. In this paper, a metropolis, Beijing, was selected as a typical study area, and the research activities were supported by the spatial information technologies such as remote sensing and GIS, and the multi-kinds of data such as remote sensing image data, survey data in fields and society statistics data were applied. According to the assessment framework of millennium ecosystem assessment (MA), a value evaluation method was used for constructing an assessment index system of wetland eco-services functions. For the requirements of assessment operations, the authors considered that the administrative districts and counties in Beijing could be taken as the assessing units. The analytic hierarchy process (AHP) method was applied to the weight calculation of each indicator. Then the comprehensive and quantitative indexes were defined and calculated at each assessing unit in the study area. The evaluation of Beijing wetlands ecological services included the adjustment functions, supply functions, culture functions, supporting functions and comprehensive functions. Through investigations, the distribution patterns of Beijing wetlands ecological services were summed up. Some conclusions have been reached: ① the regulating and provisioning functions of wetlands in Beijing are the most important, followed by the cultural function, and the supporting function plays a weaker role; ② the order of the composite function intensity from highness to weakness in the whole assessment units is as follows: Miyun County takes the first place, the districts of Fangshan, Dongchen, Xichen, Chaoyang, Yanqing and Huairou possess the second importance, and the districts of Pinggu, Tongzhou, Haidian and Mentougou occupy the third place, whereas the other districts play the weakest role.

Using ETM⁺ remote sensing data as the basic information sources,the authors carried out remote-sensing geological prospecting in Pb-Zn-Ag polymetallic ore zones of Dongwu Banner,Inner Mongolia. Remote sensing image was processed by geometric correction,atmospheric correction and the noise removal technology. Image filtering was conducted so as to enhance tectonic information and explain linear structure. The fractal dimension values were calculated by the method of fractal geometry and the box-counting dimension. As a result, the linear structures showed excellent statistical self-similarity and fractal characteristics in the study area. Principal component analysis and threshold segmentation were used to enhance the spectrum and space information and extract the iron-stained and hydroxy alteration information. Through comprehensively analyzing the linear structure,remote sensing alteration information,rock mass distribution characteristics,regional geochemical information and known deposits,seven metallogenic prospective areas at three levels were delineated.

The characteristics of the wetlands evolution process and the main driving force in Tarim Basin and Junggar Basin were comparatively studied based on MSS(1975),ETM(2000) and CBERS02(2007) remote sensing data. Some conclusions have been reached: ① The wetlands area of Juggar Basin increased by 254.94 km², but that of Tarim Basin decreased by more than 2 739.88 km² from 1975 to 2007. The rapid degradation of swamp wetlands in Tarim Basin was the major factors which caused the reduction of the wetlands. ② The Shannon-weaver index, the Evenness indexes and the species diversity of wetlands were reduced and the dominant wetlands types changed from swamp wetlands into river wetlands in Tarim Basin from 1975 to 2007, and the evolution of the wetlands in Tarim Basin could be divided into two steps: landscape fragmentation and extinction. In contrast, the Shannon-weaver and the Evenness indexes of wetlands in Junggar Basin sustainably increased, but the Evenness index continuously decreased. The wetlands scenery structure of Junggar Basin became rationalized. ③ The precipitation and temperature of Tarim Basin increased by 0.59 mm/a and 0.042 ℃/a in the past 32 years, whereas the corresponding values were 1.69 mm/a and 0.047 ℃/a in Junggar Basin. The wetlands evolution process of Junggar Basin was closely related to climate change .④ During 1975-2000 and 2000-2007, the areas that converted from wetlands to farmlands were 1 035.06 km² and 1 030.30 km² respectively, and the percentages of the reduced area were 81.74% and 69.92%. Respectively therefore, human activities seemed to be the main driving force which caused wetlands degradation in Tarim Basin.

In order to conduct land use dynamic remote sensing monitoring with clearer aim, this paper proposes appropriate monitoring ideas and methods. With Jinnan district as the study area and on the basis of establishing the development pressure evaluation index system,the authors selected the appropriate quantitative indicators and used the multi-factor evaluation method to evaluate development pressure grade of each unit in the study area and zone the area. The zoning results show that the key monitoring area of land use remote sensing dynamic monitoring in Jinnan district is 11 650.5 hectares,and the general monitoring area is 9 011.7 hectares,respectively accounting for 56.4% and 43.6% of the total area of the evaluation unit. In combination with the land-use characteristics of each zone,the selection of different remote sensing monitoring ideas and methods according to the local conditions is of great significance for efficient promotion of land use dynamic monitoring by remote sensing technology.

In order to further investigate and analyze the recent dynamic evolution of Pearl River delta coastline,the authors used multi-satellite and multi-temporal remote sensing images,such as TM,ETM and ALOS,as the data source to extract the coastline. After geometric correction and image registration,all images had the same coordinate system. According to the different features and interpretational keys of the coastlines,the authors conducted naked eye interpretation and computer automatic extraction to extract all kinds of coastlines in 1998,2003 and 2008, with the coastline extraction accuracy higher than 80%. With the help of the overlap and statistical tools in GIS,the authors also analyzed the recent evolution characteristics,trends and causes of Pearl River delta coastlines. The results show that the total length of Pearl River delta coastline changed insignificantly from 1998 to 2003,but increased remarkably from 2003 to 2008,mainly because of the artificial coastline increase. The artificial coastline possesses the highest proportion (more than 50% ),followed by rocky coastline,estuary coastline,sandy and gravel coastline,and mangrove coastline has the lowest proportion. Pearl River delta coastline mainly extends to the sea,and the main factors seem to be coastal engineering construction,beach reclamation,land reclamation and artificial breeding,with artificial reclamation being the main driving factor of the coastline changes.

Understanding the thermal infrared background field and its temporal-spatial evolution characteristics under the condition of no earthquake is the key to the effective extraction of infrared anomaly information related to earthquake. The brightness temperature background fields in the study areas of the Qilian Mountains and the Capital Zone were established using NOAA satellite thermal infrared remote sensing data from 2003 to 2011. At the same time,the temporal-spatial evolution characteristics of infrared brightness temperature background fields were analyzed. The results show that the background field of brightness temperature is influenced jointly by many factors,such as seasonal variation,terrain,and fault activity. Seasonal variation is the most important factor affecting infrared brightness temperature which has the obvious annual variation feature. In consideration of geographical environment difference,the characteristics of annual variation show different manners. The brightness temperature changes unstably in the region where topographical features are complicated. The relationship between the infrared brightness temperature and the elevation shows prominent negative correlation,and the brightness temperature is reduced by about 0.21~0.63℃ with the increase of 100 m in ground elevation,which is in accordance with the temperature lapse rate. The active fault belts obviously display linear belts or the boundary of the brightness temperature in the thermal infrared temperature images. Studies show the variation characteristics of the multi-annual average background field which smoothes some climate change information such as atmosphere, and this field is regarded as a stable reference field of brightness temperature to detect the temperature-increase anomaly caused by fault activity and earthquake.

The geographical position of the Yellow River Delta is unique and there is a sharp contradiction between the supply and the demand of water resources. In order to study its groundwater distribution, the authors adopted MODIS satellite remote sensing data to measure soil moisture and groundwater level. The relative soil moisture was estimated by using temperature vegetation dryness index (TVDI) and apparent thermal inertia (ATI) methods. The correlation between the soil moisture at different depths and the groundwater level was analyzed, which helped to get the linear equations and calculate the groundwater depth distribution. A comparison with the measured groundwater level data shows that it is feasible to retrieve groundwater distribution by using MODIS data, and 10 cm is the best depth for the inversion of relative soil water content and groundwater level in the study area. In case when the soil moisture data are lacking, we can estimate the groundwater depth distribution by using the factors which can reflect the relative soil water content.

The judgment of the drought threat and aphid harm of winter wheat can further improve the accuracy of monitoring disaster types based on hyperspectral remote sensing data. In this paper, the responses of the reflectance of winter wheat canopy to aphid harm(Macrosiphum avenae(Fabricius))and the drought threat were monitored through controlling the different water treatments under the last phase of the wheat existent in the milk. The most sensitive spectral bands for recognizing aphid pest and drought threat of winter wheat were selected through first derivative data transformation. The experimental results show that, under aphid harm and drought threat,the changes of winter wheat's spectral characteristics in near-infrared band are significantly higher than those in visible light band during the last phase of the wheat existent in the milk. And the most sensitive spectral bands identifying aphid harm and drought threat are visible and near-infrared bands. After the first derivative data transformation,it is found that the slope of the red edge is the smallest when the natural precipitation treatment is less than 40%,and the slopes of the red edge of aphid harm become bigger and bigger when the water treatments of the irrigation amount are higher than 70%,60%~70%,50%~60% and 40%~50% of water requirement, respectively. The red edge wavelength of aphid harm is the shortest,and the wavelengths of different water treatments become shorter with the increase of the drought stress. The red edge parameters can therefore serve as the important parameters for recognizing aphid harm and drought threat of winter wheat.

Nighttime light data have been widely used for mapping urban land. Previous application of the TM-assisted thresholding method mainly determined threshold of the nighttime light data in each city, which is not suitable for the study at a large scale due to its low processing efficiency and high data acquisition cost. In this paper, based on the TM-assisted thresholding method, the authors put forward the partition idea to extract the urban area using the DMSP/OLS nighttime light data. China was divided into 7 major regions based on economic partition and then TM-assisted thresholding method was employed to extract urban land areas. Finally, applying real urban land use pixels judgment, the authors obtained China’s urban land information of the years 1992, 1995 and 2000. A comparison with the previous method shows that the performance of the method based on partition idea is more efficient and can ensure overall accuracy.

The comprehensive evaluation of analytic hierarchy process (AHP)and fuzzy mathematics combines AHP with fuzzy mathematics. A more accurate evaluation through choosing the advantages of the two methods can be achieved. In this paper,taking the sand mining area in Changping of Beijing as the study area,the authors applied the comprehensive evaluation of AHP and fuzzy mathematics to the evaluation of the ecological environment and, with the help of remote sensing, to the monitoring of the ecological environment of the mining area. The ecological evaluation index system was established through the selection of the six indexes comprising density of the water bodies,vegetation coverage,residential density,topography,mining occupies and ecological diversity. Then the weights of the evaluation indexes were determined by using the fuzzy mathematics comprehensive evaluation method based on AHP,and the evaluation factors were superimposed on the platform of GIS to get the evaluation map of ecological environment for the ecological environment evaluation of the mining area. The results show that the method proposed in this paper is an effective method for the evaluation of ecological environment of the mining area, and has an important practical significance for the protection of the ecological environment of the mining area and the rational development of mineral resources.

With Guangheqiao basin in Zixing City of Hunan Province as the study area and by adopting field investigation and sampling, laboratory measurement and analysis, RS techniques and mathematical modeling, the authors calculated each parameter of the universal soil loss equation (USLE) regarding this tributary and estimated the soil erosion. The results show that the value of K parameter (soil erodibility) is between 0.14 to 0.42 t·hm²·h·hm^-2·MJ^-1·mm^-1 with a mean of 0.27 t·hm²·h·hm^-2·MJ^-1·mm^-1. This implies that the soil erodibility is at the medium level. The soil erosion module varies from 0 to 3 817 t·hm^-2·a^-1 with a mean of 78 t·hm^-2·a^-1, and the soil loss has reached 292 266 t·a^-1. Thus, the soil erosion intensity is high.

This paper aims at analyzing greenbelt distribution and change in Tangshan City and providing scientific basis and technical support for urban planning. In this paper, the authors provided a method for the extraction of the vegetation information in Tangshan City based on TM and ETM⁺ data. Vegetation information graph was calculated firstly by normalized difference vegetation index (NDVI), then through setting up the actual NDVI threshold parameter and the near infrared band threshold parameter, the accurate vegetation pixels were obtained, and vegetation information diagrams for several areas in Tangshan City were compiled. Using 3 periods of vegetation information diagrams during 1999—2009, a synthetic dynamic change diagram was computed. The diagram shows that, in the past 10 years, the park greenbelt as the mainly covering area of the city vegetation in Tangshan City has been increased. The effect of the South Lake ecological construction is obvious, and the city limits of Tangshan City have experienced expansion toward the peripheral area.

The reasonable utilization of grassland and the balance of grass and livestock based on remote sensing dynamic monitoring of the nutritional status of alpine grassland constituted the key factors for four periods monitoring of the nutritional status of the grassland. The authors studied the dynamic monitoring models for four periods of biomass and crude protein and, through direct and indirect models, analyzed the content of biomass and crude protein. The results show that the indirect model is a feasible means to retrieve the biomass and crude protein content, especially in the withered-grass period and the following green-grass period; the nutritional status of the grassland varies remarkably, with the maximum difference of the nutritional status between different periods reaching about night times.