86 results about "Ground survey" patented technology

A semi-physical simulation testing system of moon soft-land guidance, navigation and control consists of a three-dimensional translation analog module, a three-dimensional turning analog module, a control computer, a simulation computer and a ground survey and master-control computer. The three-dimensional translation analog module and the three-dimensional turning analog module adopt a practicality modeling. Wherein, the three-dimensional translation analog module is used to imitate an orbit motion of a lander relative to the moon surface. A sand table of the moon surface is used to imitate ground features of the moon. The three-dimensional turning analog module is used to imitate an attitude motion of the lander. And other well-developed regular sensors, executing agencies, lander dynamics and kinematics can be replaced by accurate mathematical models built up by the computer. Compared with mathematical simulation, the system can make a GNC proposal and algorithm more effectively and truly verified. Compared with full-practicality analogue system, the system has advantages of low development costs and easy operation.

The invention discloses a hyperspectral remote sensing image SVM classification method by combining spectrum and texture features and a hyperspectral remote sensing image SVM classification system thereof. The method comprises the following steps that S1, original hyperspectral images to be classified and a ground survey data sample set are inputted; S2, the image elements of the corresponding coordinate positions in the original hyperspectral images are extracted so as to form a reference data sample set; S3, a training sample set is randomly selected for each ground feature class; S4, principal component transformation is performed, and first principal component images are extracted; S5, a region segmentation image is acquired; S6, filtering images are acquired; S7, statistics of spectrum feature information and texture feature information of each segmentation region are performed; S8, a support vector machine model is solved; S9, the original hyperspectral images are classified so that the classified hyperspectral images are obtained; and S10, the classified images are outputted. The new strategy for combining the spectrum and texture features is provided so that the hyperspectral image classification precision can be effectively enhanced.

The invention relates to the field of photogrammetry and surveying and mapping, particularly to a digital mapping method and system based on a live-action 3D model. Digital mapping is carried out by unmanned aerial vehicle oblique photography 3D modeling and cooperation with a ground survey robot, digital mapping of the data acquisition result is more portable and flexible, at the same time high resolution live-action 3D model data can be acquired, and the sense of reality is strong. A control point coordinate acquired by the ground survey robot can effectively control the overall accuracy of the model, an acquired feature point coordinate can effectively compensate for the defect of low coordinate precision because of the influence of a barrier object on unmanned aerial vehicle aerial photography modeling. The method and system provided by the invention have greatly improved work efficiency, also can acquire vivid 3D topographic and geomorphic data at the same time, and meet the demand for diversified data results.

The invention discloses a forest disease and pest monitoring and early warning method based on unmanned plane image analysis. The method includes the steps of: S1: shooting a forest area image through a camera carried on an unmanned plane; S2: performing early-stage preprocessing on an image collected by an image collection unit, so as to improve image data and enhance image features; S3: performing image segmentation on the forest area image through an improved fuzzy C-mean algorithm to determine the position of a forest area in the image; S4: performing segmentation on the forest area image through a mark watershed algorithm based on a mixed template to determine the position of a pest plague area are in the image; and S5: on the basis of determining the position of the pest plague area, and in combination with ground survey data, grading the pest plague degree of the pest plague area. The forest disease and pest monitoring and early warning method uses the unmanned plane to carry the camera to shoot data such as pictures of the specified forest area, realizes functions of positioning of the disease and pest area of the forest area, disease and pest grading and early warning and the like, and can satisfy requirements of timely, comprehensive and efficient monitoring and early warning of a disease and pest situation of the forest area.

The present invention relates to a method of calculating a Topography Adjusted Vegetation Index (TAVI) based on a band ratio model and a solar altitude angle. The method includes the folio wing steps: obtaining the apparent reflectance data of a remote sensing image through image preprocessing, analyzing the quality of the image and numerical distribution, calculating a Shadow Vegetation Index (SVI), and constructing a TAVI combinational algorithm:TAVI=BirBr+f(Δ)·1Br,calculating an adjustment factor f (Δ) with the solar altitude angle, and finally obtaining anti-topographic effect TAVI vegetation information. The TAVI in the present invention is composed of two band ratio submodels RVI and SVI, the denominators of both of which are red band data of a remote sensing image, and the adjustment factor f(Δ), which is calculated by a solar altitude angle as a parameter with a sensor factor applied, has great physical significance. The TAVI calculation method does not need digital elevation model (DEM) data and remote sensing image classification when not depending on ground survey data,, and ensures that the interference of the topographic effects with the vegetation information can be effectively eliminated by the TAVI, thereby avoiding the problem of reduced inversion accuracy of ground vegetation information due to different registration accuracy of a remote sensing image and DEM data.

The invention relates to a method for obtaining exterior orientation elements of an aerial photograph. The method comprises the first step of performing ellipsoid correction and projection on a rotation matrix formed by first included angle data obtained in advance to obtain a rotation matrix formed by second included angle data, the second step of obtaining the second included angle data according to the rotation matrix formed by the second included angle data and using the second included angle data as three angle elements of the exterior orientation elements, the third step of obtaining first spatial offset, the fourth step of converting the first spatial offset to second spatial offset through the rotation matrix formed by the second included angle data, the fifth step of obtaining the coordinates of a GPS antenna phase center in a preset national ground survey coordinate system, and the sixth step of converting the coordinates of the GPS antenna phase center in the preset national ground survey coordinate system to the coordinates of a photographing center in the preset national ground survey coordinate system through the second spatial offset and using the coordinates of the photographing center in the preset national ground survey coordinate system as three line elements of the exterior orientation elements. The method is small in error and capable of obtaining the high-precision exterior orientation elements.

The invention provides a spatial distribution acquiring method for spartina alterniflora in a northern sea area of Guangxi. The method comprises the steps of establishing remote sensing interpretation tag libraries of spartina alterniflora and other typical land features in the northern sea area of Guangxi; leading in a shot remote sensing image, wherein the remote sensing image is a satellite or unmanned aerial vehicle remote sensing image which is shot during falling tide and has the spatial resolution of smaller than 2m; delimiting the growth range of the spartina alterniflora according to the living condition information of the spartina alterniflora, and cropping the remote sensing image; interpreting the cropped remote sensing image according to the remote sensing interpretation tag libraries of the spartina alterniflora and other typical land features, and calculating the area to obtain the spatial distribution of the spartina alterniflora in the northern sea area of Guangxi. According to the invention, the traditional artificial ground survey way is replaced with an image analyzing and processing technology, so that a great number of labor and materials are saved, the measuring precision is improved, the measuring efficiency is increased, and the prevention and control costs are reduced.

The invention discloses a method for selecting remote sensing data and classification algorithms in crop identification and area estimation. The method includes the steps of (1), obtaining sensing data of an objective area and performing pretreatment on the obtained remote sensing data; (2), obtaining ground survey data by performing a ground survey on actual distribution of crops in the objective area to obtain a sample crop distribution diagram; determining a training sample and a testing sample of crop classification through the ground survey data; (3), performing dimension expansion on the preprocessed remote sensing data and simulating to generate a multi-resolution image sequence; (4), classifying the crops through a classification algorithm and estimating the planting area of different crops; (5), analyzing the influence of the spatial resolution on the accuracy of crop identification and area estimation and analyzing the effects of planting percentage and aggregation degree on the accuracy of crop planting area estimation; (6), selecting proper remote sensing data and a proper classification method. The method for selecting the remote sensing data and the classification algorithms in crop identification and area estimation provides a theoretical basis and an experimental base for selecting the remote sensing data and the classification algorithms for areas of different crop planting structures.

The invention discloses a method for extracting tree heights by the aid of unmanned aerial vehicles and ground-based laser radar combined with the same, and belongs to the technical field of forest resource dynamic monitoring. The method includes acquiring point cloud data of forest surface layers from two-dimensional images of the unmanned aerial vehicles; acquiring point cloud data of crown canopy lower layers by the aid of ground-base laser scanners; introducing real-time kinematic (RTK) data; registering the point cloud data of the forest surface layers and the point cloud data of the crown canopy lower layers to obtain metasequoia glyptostroboides tree height information in the same coordinate reference system. The method has the advantages that respective merits of the data from twodifferent sources can be complemented by one another, and accordingly the tree height acquisition precision can be improved under the condition of high crown density of tall arbors; manual ground survey can be replaced with the method to a certain extent, accordingly, the cost can be saved, and the efficiency can be improved.

The invention discloses a land utilization change and carbon reserve quantitative estimation method based on remote sensing data. The method comprises the following steps: downloading an image; preprocessing the image; using and classifying land; calculating ground object carbon density according to ground survey data; making correlation analysis on the carbon reserves in the sample plots and the characteristic values, and selecting the characteristic values with significant correlation for modeling; and normalizing the screened characteristic values as an input layer of the convolutional neural network, putting the calculated carbon density of each sample plot into a network output layer, carrying out network training, and carrying out carbon reserve quantitative estimation on a to-be-studied region by utilizing a trained model. The invention is based on a hierarchical learning architecture of the multi-scale convolutional neural network, so that a land utilization classification result is better. On the basis of different feature values in the image and the carbon density obtained from ground survey data, the nonlinear relation between the feature variables and the carbon reserves is better fitted, and the final quantitative estimation result of the regional carbon reserves is improved.

The invention discloses a satellite visibility analysis method considering satellite occlusion conditions, comprising the following steps: S1, measuring the occlusion elevation angle Ei of a satellite at a target point; S2, calculating the spatial position of the satellite and carrying out coordinate transformation; and S3, in a station center coordinate system with a ground survey station R as the origin, calculating out the instantaneous elevation angle e and azimuth angle A of the satellite; calculating the occlusion elevation angle Ei at corresponding time and at corresponding azimuth A; comparing the elevation angle e of the satellite with the occlusion elevation angle Ei at the corresponding time and at the corresponding azimuth; if e<=Ei, judging that the satellite is not visible, and removing the satellite; if e>Ei, judging that the satellite is visible, and keeping the satellite; and filtering satellites according to the method, and obtaining an accurate satellite visibility result. The precision factor of a single survey station is evaluated according to the satellite visibility analysis result, and thus, ephemeris prediction is realized. The method of the invention is suitable for carrying out ephemeris prediction of GNSS observation in alpine and gorge regions and in regions difficult to observe under the effect of city buildings. The problem that the traditional ephemeris prediction result is inconsistent with the actual observation conditions is solved.

The invention relates to a precise surveying and mapping method of a 0.25m contour interval of a flat ground with a large scale of 1:500 to 1:200, which adopts the aerial and ground combining mode of an aerial survey and a ground survey, complements advantages of each other and ensures the high precision of the 0.25m contour interval. The invention comprises the following steps of: acquiring an image by utilizing a DMC (Digital Micro-Circuit) aerial digital camera; collecting topographic map data by combining the aerial survey and the ground survey; utilizing all horizontal and vertical field distribution points for all photo control points; and aerially triangulating and improving the absolute orientation precision of mapping.

An optical sensing detection device and method for fluid medium interface belong to the field of optical fiber sensing technology. The device comprises a medium interface sensor, a ground survey instrument and an armored optic / electric composite cable, and is characterized in that the medium interface sensor comprises sensing basic units which are serially connected, wherein each sensing basic unit comprises an electric heater and an optical fiber temperature measuring device which are encapsulated integrally; 1 to 2 metal wires and 1 optical fiber are included in the optic / electric composite cable; the ground survey instrument comprises an optical fiber sensing demodulation instrument, a constant-current power supply and a computer, the constant-current power supply provides heating current to the electric heater in a square wave form, meanwhile the optical fiber sensing demodulation instrument is used for reading the temperature value of the optical fiber temperature measuring device continuously, and the medium species and interface positions at the periphery of an electrical heating body are identified according to differences of characteristic parameters of temperature-time curves in different media. The optical sensing detection device has the effects and benefits of high reliability, corrosion and pollution resistance, zero maintenance and long service life, and is particularly suitable for detecting oil-water surface of in underground salt cavern made cavity.

The invention provides a method for accurately settling agricultural disaster claim based on remote sensing data and digital field, involving remote sensing technology, GPS technology, GIS technology,Using high-definition remote sensing image data (remote sensing satellite data or aerial photograph data of unmanned aerial vehicle) and ground survey data to interpret the disaster situation of crops, digital field data is combined to accurately locate the scale of farmers and fields, so as to realize online inquiry of agricultural disaster degree and disaster area according to the information of the fields and the right holders. The invention provides a method for accurately settling agricultural disaster claim based on remote sensing data and digital field, which only needs to sample the disaster areas with different degrees and a small number of people to carry out on-the-spot investigation to realize fast, Accurate identification and inquiry of the disaster situation of each farmer and field, not only improving the work efficiency, but also saving a lot of manpower and material resources in agricultural insurance claim settlement.

The invention relates to a method for identifying a deformation evolutionary phase of red rock landslide in east Sichuan. The method comprises the following steps: confirming a disaster-pregnant background condition in a surveying area, main geological disaster problems and controlled factors; confirming the deformation evolutionary phase of large and super-large bedding rock landslide in the surveying area and an identification mark feature of each deformation evolutionary phase by investigating typical cases in the surveying area; establishing high-precision remote sensing interpretation data and DEM in the surveying area; explaining the geological environments, such as, material construction, geologic structure and slope landform, in the surveying area according to the remote sensing interpretation data and DEM; preliminarily pre-judging the hidden danger slope in the surveying area according to the identification mark feature and the interpretation result; and rechecking the preliminarily confirmed hidden danger slope adopting an engineering geological analogy method through field ground surveying, thereby identifying the hidden danger slope, judging the deforming phase and determining. According to the invention, the hidden danger slope in the red layer in east Sichuan is more effectively determined in the ground surveying process and the guiding basis is supplied for the group measurement and prevention, monitoring, early warning and forecasting of the landslide.

According to the technical scheme, the sky-ground integrated monitoring method comprises the steps that S1, firstly, infected and withered trees are extracted through unmanned aerial vehicle images, plaques of the infected and withered trees are extracted through satellite images, and on-site marking, positioning and measuring are conducted on the withered trees through ground investigation; s2, respectively acquiring high-spatial-resolution satellite remote sensing data and unmanned aerial vehicle remote sensing data as data sources, and jointly forming a data set of a monitoring area in combination with ground survey data and forest resource second-class survey data; s3, establishing samples of the epidemic trees according to the data, wherein the samples comprise spectral features, texture features and geometric features of the pine wood nematode disease withered and dead trees; and S4, according to the sample and satellite remote sensing, confirming the infected, withered and dead tree plaques, comprehensively applying an image enhancement and image classification method, performing verification, and establishing spatial distribution information and position information of the pine wood nematode disease withered and dead trees. The method has the advantages of high epidemic area screening efficiency, capability of realizing large-area efficient monitoring, convenience in acquisition of remote sensing data of the unmanned aerial vehicle, high recognition precision and guarantee for precision verification.

The invention discloses an automatic regulating device used for surveying and mapping equipment. The automatic regulating device comprises a support plate, and three adjustable support legs which areconnected with the support plate via hinge joint; the side surfaces of the support plate are provided with at least two horizontal sensors; the horizontal sensors are arranged on the side surfaces ofthe support plate which are not parallel to each other; each adjustable support leg is provided with a power unit; the power units are used for driving length adjustment of the support legs; the horizontal sensors are connected with the power units; when it is detected by one horizontal sensor that the horizontal sensor is inclined, the power units are adopted to adjust the length of the corresponding adjustable support legs; the automatic regulating device also comprises a centring adjusting device which is arranged on the support plate, and an installation plate which is arranged on the centring adjusting device; a laser device is arranged on the installation plate, and is used for vertical emitting of laser onto the ground; the centring adjusting device is used for driving translation of the installation plate relative to the support plate, so that the laser emitted by the laser device is moved to a position on the ground which is overlapped with a ground survey station point.

The invention provides a method for accurately verifying and protecting agricultural insurance based on remote sensing data and digital field, crop species and crop areas are identified using high-resolution remote sensing image data (remote sensing satellite data or aerial photographs of unmanned aerial vehicles) and ground survey results, by Combining digital field data, the farmer scale and field scale are accurately located, so as to realize the online inquiry of crop species and area and agricultural insurance online protection function according to the field information and the ascertained right holder information. The on-line verifying and protection method for agricultural insurance based on the agricultural remote sensing technology can realize the on-line verifying and protectionof the farmer household and the farmland only by a small amount of field sampling investigation, which not only improves the work efficiency, but also saves a large amount of manpower and material resources in the verifying and protection work of the agricultural insurance.

A detecting method for monitoring mountain skidding and geological calamity characterized in that, a number of inspection wells with built-in steel sleeves are arranged in a monitoring region, arranging control device connected with ground control survey instrument and pushing device into the inspection wells, the control device controls the pushing device configure a plurality of magnetosensitive sensing unit onto the internal walls of the steel sleeves, the ground survey instrument then continuously measure the stress variation information on the magnetosensitive sensing device.

The invention discloses an ensemble learning method based on self-adaptive sample expansion. On the one hand, multiple weak classifiers are integrated through adopting a manner of bootstrap feature sampling and dynamic weighted voting, and the advantages of high classification accuracy and good repeatability of the ensemble learning method are inherited; and on the other hand, the method can realize self-adaptive expansion of samples through iteration classification and sample screening based on spatial dispersion and attribute similarity on the basis of a small number of ground survey samples, and the model under-learning problem caused by small / medium-sized samples in classification is solved. The ensemble learning method to which the scheme relates adopts a manner of self-adaptive sample expansion, can effectively solve the problem of insufficient samples in a remote-sensing classification process, and reduces manpower and time spent by researchers for obtaining samples at the sametime.

The invention relates to a TAVI regulatory factor algorithm based on solar altitude. The method includes the following steps: conducting image pre-processing, analyzing the numerical distribution of image wave section apparent reflectance, extracting the solar altitude and computing a regulatory factor. According to the invention, the method obviates the need for DEM data and remote sensing image classification, independent from ground survey data, uses solar altitude in actual physics significance as a computing parameter, ensures that TAVI can effectively eliminate interference on vegetation information by orographic influence, can achieve the effects of orographic correction of a C model and even produces better effects, prevents the inversion of surface feature vegetation from being reduced in precision due to the difference between remote sensing images and DEM data registration accuracy, and provides scientific and economic basis for the large-scale application and promotion of the TAVI to the inversion of vegetation information of complex geography and mountains.

The invention discloses a method for carrying out tree species classification on hyperspectral data of an artificial forest by using a three-dimensional convolutional neural network. The method is suitable for obtaining distribution information of artificial forest species, and belongs to the technical field of machine learning in forestry application. The key technical points comprise: 1, taking image data of a test area, and building a sample data set according to ground survey points; 2, building a three-dimensional convolutional neural network, and completing training of a model; and 3, predicting the image by using the trained model, and completng tree species distribution drawing and precision evaluation. The key problems to be solved comprise: 1, only a small number of samples are needed to complete the model training, and the workload of ground survey is reduced; and 2, compared with the traditional hyperspectral classification method, the method does not need to perform feature extraction and screening in advance, and is higher in classification precision. The method is suitable for hyperspectral data tree species classification, the three-dimensional convolutional neural network is applied to artificial forest tree species classification for the first time, and the result can provide basic data basis for forest resource investigation and tree species distribution information acquisition.

The invention relates to the field of ground survey, in particular to a probing method of a static penetrometer. The probing method is characterized by at least including the following steps: installing a survey device on a static probing probe, and enabling the survey device to measure an inclined angle of the static probing probe; and arranging an analog-to-digital converter on the static probing probe, and enabling the analog-to-digital converter to receive analog signals measured by a static probing sensor, convert the analog signals into digital signals and transmit the digital signals to a data collector. The probing method has the advantages of being digitalized, capable of measuring angle values and temperature values, unidirectional in data, capable of performing controlling through a touch screen, audio-visual in data and capable of performing wireless transmission.

The invention discloses a new method for pump diagram metering stability. The new method generates a pump diagram on the basis of ground survey data, oil well parameters, mathematical models and algorithms and consists of two parts including a valve opening and closing point initial position determination method and a correction method, wherein the valve opening and closing point initial position determination method is characterized in that a valve opening and closing point initial position is established and directly extracted on the basis of the pump diagram, and the correction method is characterized in that an initial valve opening and closing point is corrected when a moving valve opening and closing point is subjected to a hopping phenomenon under the state of a constant working condition by combining with the shape features of the pump diagram. The combination of the valve opening and closing point initial position determination method and the correction method has the outstanding advantages that the position determination speed of the valve opening and closing point is high, the valve opening and closing point can be accurately positioned, the hopping phenomenon of the position of the valve opening and closing point due to the subtle change of the pump diagram can be effectively avoided, the new method can be applied to the real-time metering production of an oil well group, and metering precision is high.

The invention discloses a real time monitor method for early stage well kick overflow based on transient flow. By means of a wellhead transient flow meter, a slurry pressure sensor, and a slurry liquidometer, the drilling fluid returning from the wellhead is monitored in real time for early discovery of well kick overflow to solve the problem of poor real-time performance and accuracy of the current early stage well kick overflow detection. According to the method, on the drilling site, related measure devices are used for collecting the pressure, the temperature and fluid volume of wellbores which are not limited by the well size and drilling machine types so that the monitor method is simple, quick, and effective. According to the method, by aggregate analysis of pressure, temperature and volume of the wellbore, and the torque vertical segment and horizontal segment friction / torque data, the required parameter can be accurately obtained through ground survey data and real time monitor on early well kick overflow can be quickly and accurately performed.

The invention provides a method for realizing moon rotation measurement based on the inverse same beam interferometry measurement technology. The method comprises the steps that two ground survey stations between which the distance is within 50km are arranged on the ground; two signal sources are arranged on the surface of the moon; the first ground survey station GS1 and the second ground survey station GS2 simultaneously receive the downlink signals forwarded by the first signal source S1 and perform signal phase estimation so as to obtain first inter-station phase difference; the first ground survey station GS1 and the second ground survey station GS2 simultaneously receive the downlink signals forwarded by the second signal source S2 and perform signal phase estimation so as to obtain second inter-station phase difference; the relationship of a baseline formed by the first signal source S1 and the second signal source S2 and differential delay values is established; and moon rotation information is solved according to the relationship of the baseline and the differential delay values. The advantages of the method are that the method has the advantages of being high in measurement accuracy, quite simple in measurement mode and relatively easy to implement and can be widely popularized and used.

A detecting system for an auto-passing phase-splitting function of an electric locomotive is characterized by at least comprising a first incoming line simulation ground inductor, a first outgoing line simulation ground inductor, a main circuit breaker detecting unit, a wireless transmitting unit, a ground survey display unit, a front induction receiver and a rear induction receiver, wherein both the first incoming line simulation ground inductor and the first outgoing line simulation ground inductor are arranged on one side of a track, the front induction receiver and the rear induction receiver are respectively arranged at the front and the rear ends of the electric locomotive, the main circuit breaker detecting unit and the wireless transmitting unit are arranged in the electric locomotive, and the wireless transmitting unit is connected with the ground survey display unit in a wireless mode. Due to the adoption of the technical scheme disclosed by the invention, the structure is simple, the arrangement is reasonable, the installation is convenient, the failure rate is low, the measuring accuracy is reliable, and the convenience and accuracy of detection and maintenance for the auto-passing phase-splitting function can be ensured.

The invention relates to a non-contact underwater detection method of a river channel underwater foundation stone. The underwater detection method can effectively, quickly, accurately and safely detect the underwater foundation stone. The method comprises the following steps: firstly performing ground survey and fracture surface location, including setting up a base station and measuring fracture surface control points; according to the river channel environment conditions, determining a detecting manner, including a foundation stone surrounding fracture detecting manner or a dam surrounding detecting manner; mounting a detecting instrument: including connecting a detector with a GPS (Global Positioning System) and connecting a navigator with the GPS; adopting the GPS navigation function to guide underwater foundation stone detection; processing and analyzing data information: including calculating stone lost area and stone lost amount; outputting the result, including outputting a foundation stone detection result map and a detection result table. The non-contact underwater detection method is easy to operate, quick, accurate, safe and effective to detect the underwater foundation stone, high in the working efficiency, low in the labor intensity, and capable of effectively solving the technical problem of river channel foundation stone detection.

The invention discloses an underground engineering depth combination geological survey arrangement method. The method comprises the steps that ground survey is carried out, and a geological backgroundreport of a survey area and a geological survey implementation scheme are formed; surface area geophysical prospecting is carried out, engineering geological partitioning is carried out, an engineering geological partition map of the survey area is generated, and a geophysical prospecting abnormal zone is delineated; conventional vertical drilling is carried out on an underground engineering shallow buried section, in-situ testing is carried out, a sample is reserved for testing by coring, and the engineering geological condition of the shallow buried section is analyzed and judged; underground engineering excavation support is pre-designed; the underground engineering shallow buried section is excavated, and in-hole advanced geophysical prospecting is carried out before excavation; long-distance horizontal drilling is carried out, in-situ water pressure testing is carried out, a sample is reserved for testing by coring, and the condition in front of underground engineering excavationis analyzed; and the condition is compared with advanced geophysical prospecting geological data, and support design parameters are dynamically adjusted. The geological condition of underground engineering is accurately surveyed, the method is suitable for underground cavities with different formation lithology, and the construction efficiency is high.

The invention discloses an establishing method for a reference sample plot used for remote sensing monitoring of alpine grassland. According to the invention, ground survey is carried out on the basis of determination of one hectare of a reference sample plot, wherein the area of the reference sample plot can cover more information including a plurality of information like vegetation, soil, terrain and interference; positioning accuracy guaranteed by differential GPS can provide more accurate interpretation information for high spectral remote sensing; unreliable information in data of 9 control quadrats can be removed according to a data confidence interval, and strong noisy data removing capability is obtained; the reference sample plot has good repeatability and verifiability, so the defect that conventional meadow survey cannot be reproduced is overcome; and the method has strong information integration capability, information like species, soil, hydrology, microorganisms, isotope and heredity except vegetation can be simultaneously acquired and brought into an information platform according to research and monitoring needs, so the method provides technology and standards for further enlargement of construction of a reference sample plot network of the alpine grassland in China.