38 results about "Topographic factor" patented technology

The invention discloses a drought remote sensing monitoring method suitable for high altitude areas. The method comprises: S10, collecting data of a target area, S20, preprocessing the data obtained in step S10 to obtain an enhanced vegetation index, a surface temperature index, a land cover type and downscaling rainfall data, S30, calculating a vegetation state index, a temperature condition index, a rainfall state index, a reclassified land cover type and elevation by the data in step S20, and S40, constructing a drought remote sensing monitoring model based on spatial principal component analysis. The method comprehensively considers various factors affecting drought, wherein the various factors include a vegetation factor, a surface temperature factor, a rainfall factor, a land cover type factor and a topographic factor, a drought monitoring model is constructed by a spatial principal component analysis method, can effectively eliminate variables with large correlation in the selected variables and can extract few unrelated comprehensive indicators.

The invention relates to a river water quality and biological monitoring system and a river water quality and biological monitoring method for an irregularly-shaped region. The system comprises a base station, a communication network and a logic analytical unit, wherein the base station is arranged at a preset position of a river basin, comprises a biological monitoring unit and a water quality monitoring unit, and is used for monitoring the biological and water quality parameters of the position of the base station respectively, acquiring the corresponding index information, sorting signals and transmitting into the logic analytical unit through the communication network, and the logic analytical unit can perform operation to the real-time monitoring data through a constructed monitor model and also can carry out index data evaluation and output the monitoring result. The system and the method comprehensively consider multiple transverse and longitudinal factors of the rivers and territory and topographic factors to construct the parameter monitoring model in real time and obtain the quality evaluation index, therefore, the river can be accurately monitored and evaluated.

A power transmission and transformation equipment ice coating disaster monitoring and forecasting method based on meteorological and topographic factors comprises the following steps of: S1, collecting meteorological and topographic data comprising geographic information such as a sea level elevation, river network information, a slope, an exposure, slope variability, exposure variability, a waviness, a roughness, a surface illumination degree and the like; S2, establishing an ice coating thickness estimation meteorological model, wherein the meteorological model is as follows: Y=-0.11x1-0.49x2-0.34x3-0.335x4+0.00x5-0.013x6+0.27x7+1.75x8; S3, carrying out topographic correction of the ice coating thickness estimation meteorological model and carrying out contrastive analysis on an ice coating thickness increment and a difference value of an actually measured value and a meteorological model estimated value, which are obtained by utilizing the formulas, wherein a topographic correction model is as follows: delta Y'=0.19+0.0014x1-0.0035x2+0.045x3; S4, adding the meteorological model in the step 2 with a topographic correction model in the step 3 to obtain a final ice coating thickness comprehensive correction model, completing monitoring on ice coating thickness distribution and carrying out forecasting on the basis of an obtained result. The method considers influence of microtopography and micrometeorology on monitoring of a power transmission and transformation equipment ice coating disaster and has the advantages of high accuracy, high practicality, high reliability and the like.

An embodiment of the present invention provides a method and a device for selecting a wind tower site in wind farm generation and operation, wherein the method includes: dividing a wind farm site into grids, with the intersection points of the grids being candidate locations for the wind tower site; selecting from all candidate locations the candidate positions that satisfy the requirements of topographic factors, obstacle factors, tower representativeness and wake current factors; using the selected candidate locations to form a primary candidate location set; selecting a candidate location that meets the wind resource monitoring site selection index, the power generation amount post-assessment site selection index, and the ultra-short-term power forecasting location index from the primary candidate location set; and determining the one selected candidate location as the location where the wind tower is installed, wherein the wind resource monitoring site selection index indicates the degree to which the candidate location meets the requirements of wind resource monitoring requirement, the power generation amount post-assessment site selection index indicates the degree to which the candidate location meets the power generation amount post-assessment requirement, and the ultra-short-term power forecasting location index indicates the degree to which the candidate location meet the ultra-short-term power forecasting requirement.

The invention discloses a forest stock inversion method based on the high-score satellite remote sensing data made in China, which adopts a number table method to calculate the measured value of the forest stock in a sample plot. Based on the pretreatment of remote sensing data, the panchromatic texture features and multi-spectral vegetation index features of different windows are extracted. The correlation between the image features and the measured volume is analyzed, and the image features with significant correlation are selected as the variables of the model. The terrain factors of the sample plot are extracted according to the terrain data. Finally, based on the measured data, texture features, spectral features and topographic factors, a forest stock inversion model is constructed.The invention also discloses a forest stock retrieval system based on the high-score satellite remote sensing data made in China. The invention makes full use of the advantages of retrieving forest stock from the high-score satellite remote sensing data made in China, and further improves the precision of the forest stock retrieval.

The invention discloses a post-earthquake mud-rock flow early recognition method, which belongs to the technical field of mud-rock flow monitoring engineering, and is characterized by comprising the following steps of: a, determining an evaluation factor, and calculating a prior probability PP (m) and a posterior probability P (m) under each classification; b, constructing a regional debris flow susceptibility model through equal-weight superposition calculation; c, constructing a post-earthquake debris flow terrain induction degree model, and predicting the debris flow rushing-out range of each valley; and d, combining the object source sensitivity of the debris flow with the terrain induction degree to construct a post-earthquake debris flow early recognition model. The object source andtopographic conditions of the post-earthquake debris flow basin are considered, the object source sensitivity of the debris flow is introduced into a model, topographic factors are analyzed through alinear regression analysis method, and then an early recognition result of the post-earthquake debris flow is obtained through comprehensive equal weight superposition. The accuracy of debris flow identification in an earthquake area can be effectively improved, and powerful evidence is provided for prediction and prevention of debris flow after the earthquake.

The invention discloses an ArcGIS-based geomorphic type division method, which is used for dividing geomorphic types by establishing a model and a division system in ArcGIS, and comprises the following steps of: data preprocessing: generating a basic map layer on the basis of a digital elevation model; terrain factor extraction: extracting an optimal terrain factor by using ArcGIS; geomorphic typedivision: using ArcGIS to establish a model and a division system to divide geomorphic types. According to the invention, a digital elevation model (DEM) is used in ArcGIS and a spatial analysis processing function is applied to carry out automatic discrimination and division of landform types; according to the method, topographic factors (elevation, gradient, topographic relief, earth surface cutting depth and the like) are extracted mainly based on a specification statistical unit, then multiple topographic factors are comprehensively analyzed, time and labor are saved, and standard consistency, system unification and quantification accuracy can be achieved.

The invention discloses a feature screening method for key topographic factors of debris flow watershed, aiming at the defects that the prior art cannot provide specific discriminant indexes and comprehensive action effects of various factors. In this method, the feature sets of possible key topographic factors are collected from the samples of debris flow basin and non-debris flow basin, and thenthe Lasso penalty function is established to solve the optimal solution of the penalty function. The feature corresponding to beta not equal to 0 regression coefficient in the optimal solution feature is the feature of the selected key topographic factors. The invention also provides an application of a feature screening method for a key topographic factor of a debris flow basin. The method of the invention is based on the Lasso method for comparative analysis and screening of the characteristics of the key terrain factors of the debris flow basin, and utilizes a machine learning algorithm and a program to complete quantitative analysis, thereby overcoming the drawback that the prior art can only qualitatively screen the characteristics of the key terrain factors because the statistical method is taken as the basis. The method is reliable in principle and accurate in result.

The invention provides a hazardous chemical transport hazard predicting and controlling system. The adjoint mode provided by the hazardous chemical transport hazard predicting and controlling system is set up on the basis of a CAMx diffusion mode and is more suitable to practical diffusion by considering affection of meteorological factors and topographic factors; starting from protective targets, the adjoint mode only needs to solve adjoint equation once to acquire risk value, and time for solving the adjoint equation is equal to time for solving diffusion equation; prediction of hazardous chemical transport coming risks is realized by application of the numerical diffusion mode is realized, practical conditions of transport objects, transport time and transport lines are comprehensively considered, elaborate risk field distribution during practical transport is obtained, blindness of emergency preparation is avoided, and a real-time hazard evaluation mode matched with actual topography, weather, environments and the like is provided, so that hazard control during hazardous chemical transport accidents is more scientific and effective. Accordingly, hazard prediction results are more accurate, hazard prediction efficiency is higher, and hazard control policy is more scientific.

The invention discloses a valley debris flow early warning method based on soil moisture content, which belongs to the technical field of debris flow prevention and control engineering, and is characterized by comprising the following steps: S1, determining basic parameters of a potential debris flow basin through Google Earth or a topographic map; s2, early-stage rainfall of the position where the debris flow basin formation area is located and rainfall 10 minutes before excitation are monitored or forecasted in real time; s3, investigating the average width of channels in the debris flow basin forming area and the particle size of particles in the debris flow basin forming area; s4, calculating a topographic factor T of the debris flow basin; s5, calculating a debris flow basin geological factor G; s6, calculating a rainfall factor R inducing debris flow; s7, judging the occurrence of debris flow; according to the method, starting from the starting principle of the gully debris flow, the soil moisture content is directly adopted as a main precondition for exciting debris flow rainfall, the rainfall contribution can be calculated more accurately, and thus the debris flow can be early warned more accurately.

The invention discloses a ground vehicle path planning method based on maneuverability evaluation, which comprises the following steps: multi-source data is acquired and terrain and environment three-dimensional reconstruction is performed by using a geostatistics method to obtain a three-dimensional point cloud terrain model, and the multi-source data comprises remote sensing elevation terrain data, land utilization data, soil type distribution data and vehicle data; according to trafficability analysis and maneuverability cost quantification of topographic factors and a terrains effect, vehicle maneuverability evaluation is carried out on the traffic area; and path planning is carried out by adopting a cost function of an improved A-Star algorithm. According to the method, the three-dimensional point cloud terrain model is reconstructed by acquiring multi-source data, vehicle maneuverability evaluation is carried out after terrain and soil data analysis, and finally, an optimal planned path is acquired according to an improved A-Star algorithm. The problem that the path planning technology of the special operation vehicle in a field environment without a road network is deficient is solved. Visual three-dimensional visualization display is provided, and a decision maker is assisted in analysis and optimization after path planning.

The invention discloses a landslide early warning method for a cutting slope in a granite area. The method comprises: step a, on-site investigation and mapping of a landslide body gradient alpha, a landslide body area A, a landslide body upper side area Au and a landslide body upper side gradient beta of an artificially cutting slope in a granite area are carried out; step b, according to a formula T=A+1.9U, a terrain comprehensive discriminating factor T of the artificially cutting slope in the granite area is calculated; step c, an equivalent rainfall R* is calculated based on a formula 4 and a rainfall factor R is calculated according to a formula 5; step d, a landslide determination value P is calculated according to a formula 6; and step e, condition determination is carried out on the landslide determination value P and a landslide threshold value Cr. According to the invention, for the artificially cutting slope in the granite area, the internal mechanism study is carried out ona landslide occurrence degree by studying a topographic factor and a rainfall factor; an early-warning calculation model of the landslide of the artificially cutting slope is established; and the landslide early-warning level is determined by a quantitative way. Therefore, the accuracy of early warning is improved substantially.

The invention discloses an aqueous sediment geochemical anomaly mapping method based on BME-GWR, and the method comprises the following steps: extracting topographic factors based on ASTGTM2DEM data, the topographic factors comprising gradient, slope direction and topographic relief degree information; constructing a probabilistic soft data model of the research area for the extracted topographic factors and the average rainfall information of the research area based on a GWR method; by taking the geochemical data of the 1:200,000 water-system sediments as hard data, identifying the geochemical anomalies of the water-system sediments in the research area for the established probabilistic soft data model and the hard data based on a BME method; and comparing the identified geochemical anomalies of the water-based sediments with a Pocrige interpolation result, and performing interpolation precision and uncertainty evaluation. According to the BME-GWR-based geochemical anomaly mapping method for the water-based sediments, the recognition precision of geochemical anomalies of the water-based sediments is improved, and the uncertainty is reduced.

The invention discloses a shallow landslide type valley debris flow early warning method, which belongs to the technical field of debris flow prevention and control engineering, and is characterized by comprising the following steps of: a, measuring a full watershed area A of debris flow without accumulation areas; b, measuring the percentage S0 of the sensitive slope area in the whole drainage basin area of the debris flow without the accumulation area and the longitudinal gradient J of the gully bed, and determining a debris flow topographic factor T; c, determining the annual average rainfall R0 of the debris flow channel in the monitoring area and the one-hour rainfall variation coefficient Cv of the debris flow channel, measuring the one-hour excitation rainfall It, determining the mother rock type of the soil, calculating the soil moisture content factor K, and determining the debris flow rainfall factor R; d, calculating a debris flow occurrence index P; and e, judging the occurrence of debris flow. The measurement and calculation result of the method is more in line with the debris flow formation mechanism, the debris flow early warning accuracy is improved, and the method has higher disaster prevention applicability.

The invention discloses a technical method for studying and building main arbor species land parcels/class classification indexes in China. The technology is used for exploring the influence of topography, terrain and soil conditions in different places on tree growth and forest distribution. the influence factors are concluded as land parcel/class classification indexes; a Chinese dominant arborland parcel/class classification index map (table) is provided, (1) the influence of position change on a forest arbor growth process is divided into a slope (alpha), a slope direction (beta), a slopeposition (gamma) and a soil thickness (h), data standardization processing is carried out on data, and a relation model of the influence of topographic factors on the forest arbor growth process is established; and (2) a mathematical model is established, in the formula, lambda alpha is an arbor growth slope influence coefficient, lambda beta is an arbor growth slope direction influence coefficient, lambda gamma is an arbor growth slope position influence coefficient and lambda h is an arbor growth soil thickness influence coefficient.

The invention discloses a multi-source rainfall fusion method based on principal component regression. The method comprises the following steps: acquiring and sorting ground station observation data, remote sensing inversion rainfall data and terrain factor data; comparing the observed rainfall at each ground station with remote sensing inversion rainfall, and estimating a rainfall background error at the grid where each station is located; fusing the multi-source rainfall information and the topographic factors by adopting a principal component regression method to obtain a grid background field residual error; selecting an addition model to obtain a multi-source rainfall estimation result; according to the scheme, multi-source precipitation information is fused through the principal component regression method, important information is reserved while the collinearity problem among independent variables is eliminated, and the precision of precipitation space distribution estimation is further improved.

The invention provides a terrain surface area calculation method based on slope constraint. In order to the problem that in the prior art, topographic information data cannot be effectively and directly stored, and the skeleton control effect of the topographic elements on the topographic and geomorphological elements are neglected, the method comprises the following steps: extracting topographic and geomorphological elements through topographic analysis, mining topographic and geomorphological information hidden in DEM data, and improving the topographic surface area modeling precision through the assistance of the topographic factors.

The invention discloses a method for judging landslide danger of an artificially cut slope of phyllite, which is characterized by comprising the following steps: a, investigating and mapping the slopelength L of the landslide body of the artificially cut slope in a phyllite area, the slope degree alpha of the landslide body, the area A of the landslide body, the upper side area Au of the landslide body and the slope degree beta of the upper side of the landslide body on site; b, calculating a terrain comprehensive discriminating factor T of the artificially cut slope in the phyllite area according to T=S+1.8U; c, discriminating the landslide danger of the artificially cut slope of the phyllite. According to the method for judging landslide danger of the artificially cut slope of phyllitein the invention, internal mechanism study is carried out on the occurrence degree of landslide by studying the topographic factors, and a danger calculation model of side slope landslide of the artificially cut slope of the phyllite is established; the pointedness is strong; the landslide danger region is accurately divided in a quantitative manner by comprehensively considering the topographic influence factor of side slope landslide of the artificially cut slope; and the dividing precision is effectively ensured.