306 results about "Sample plot" patented technology

The invention is concerned with a method for forest inventory and for determination of stand attributes. Stand information of trees, sample plots, stands and larger forest areas can be determined by measuring or deriving the most important attributes for individual trees. The method uses a laser scanner and overlapping images. A densification of the laser point clouds is performed and the achieved denser point clouds are used to identify individual trees and groups of trees. The invention is also concerned with a computer program for performing the method.

The invention provides a forest aboveground biomass inversion method fused with spectrum and texture features and a forest aboveground biomass inversion system fused with the spectrum and texture features. The method comprises the following steps of calculating an aboveground biomass of a research region sample plot so as to obtain a sample plot biomass observation value; performing geometric correction and radiometric correction on high-resolution remote-sensing image panchromatic data and multispectral data; respectively performing statistical regression on the sample plot biomass observation value and a corresponding spectrum feature vegetation index, and selecting a spectrum feature inversion model; extracting various texture feature variables under different windows, respectively performing statistical regression on the sample plot biomass observation value and the corresponding texture feature variables, and selecting a texture feature inversion model; determining a weight through a sensitivity analysis of a spectrum key factor and a texture key factor, constructing a spectrum texture feature combination inversion model of the biomass, and realizing the forest aboveground biomass inversion. The method and the system provided by the invention have the advantages that the spectrum features and the texture features are fused, and the advantages of the spectrum features and the texture features for biomass inversion are fully exerted, so that the quantitative inversion precision of a forest aboveground biomass is effectively improved.

The invention relates to a bamboo forest carbon sequestration capacity measuring and carbon sequestration capacity improving fertilizer preparation method, which comprises the following six steps: 1, test design: selecting a bamboo forest sample plot, setting and processing a test area, then sampling, determining and computing; measurement and computation of annual respiration carbon emission amount of bamboo forest: measuring soil respiration rate, computing greenhouse gas CO2 emission flux and CO2 emission amount in soil annular accumulated respiration and determining no-root respiration soil CO2 emission amount; 3, measurement and estimation of bamboo forest vegetation carbon storage; 4, measurement and computation of soil carbon storage; 5, computation of bamboo forest annual net carbon fixation amount; and 6, optimum fertilizer preparation for improving bamboo forest carbon sequestration capacity. Through fertilizer application according to the optimum fertilizer preparation scheme obtained in the method disclosed by the invention, the carbon sequestration capacity of the bamboo forest can be obviously improved, and the invention provides an effective and feasible novel scheme for solving the greenhouse effect caused by the increase of atmospheric CO2 concentration.

The invention relates to a domestication method for enhancing the salt resistance of festuca arundinacea. The domestication method comprises the following domestication processes that: a domestic garbage compost substrate is flatly spread on a sample plot, then the compost becomes compact and flat by press, and the average thickness of the compost substrate is 20cm; the sowing mode is spring sowing, water in the compost substrate, which is used for domesticating the festuca arundinacea in each year, only depends on natural precipitation, and the seeds of the festuca arundinacea are harvested after 4 domestication years; a lawn nursery strip mode is as follows: the carrier of the lawn nursery strip of the festuca arundinacea is designed into double layers, i.e. a lower layer is newspaper and an upper layer is face tissues, and the seeds of the domesticated festuca arundinacea are bonded between an upper carrier and a lower carrier by an adhesive; the sowing quantity is 0.02g/cm2; after the seeds germinate, the seeds are transplanted onto a saline soil substrate with the salt content of 0.5 to 1 percent, the temperature is controlled at 20 to 26 DEG C, the relative humidity is 30 to 50 percent, and the normal growth of plants is guaranteed; and after the plants of the festuca arundinacea are cultured for 35d, lawn plants and the substrate are mown, and the salt resistance of the domesticated festuca arundinacea is measured after treatment.

The invention relates to a method and a system for quantitatively estimating carbon reserves of a native coastal wetland ecosystem. The method comprises the following steps: completing native coastalwetland mapping by adopting multi-source and multi-temporal remote sensing data; obtaining native coastal wetland soil and vegetation samples by adopting a traditional sample plot and quadrat investigation method, and realizing soil carbon reserve space inversion by adopting a geographically weighted regression method; adopting a remote sensing technology to realize biomass inversion of the nativecoastal wetland, and combining a biomass carbon coefficient to realize vegetation carbon reserve estimation of the native coastal wetland; and finally, estimating the carbon reserves of the native coastal wetland by combining the soil carbon reserves and the vegetation carbon reserves. The system and the method break through the limitation that the previous research on the native coastal wetlandis only limited to the estimation of experimental points, greatly improve the estimation precision of the carbon reserves, realize the intuitive and reliable analysis of the spatial heterogeneity andreserves of the carbon reserves, and can provide a scientific basis for the carbon cycle research of an ecological system.

The invention relates to a soil gas collector, in particular to the field of equipment for collecting and measuring a trace amount of soil gas. In the technical scheme for fulfilling the aim of the invention, a gas collector for collecting the soil gas consists of a cone frustum-shaped air chamber body without a bottom surface, a tubular connecting ring and a tubular fixed pipe which are connected with one another sequentially, wherein the lower port of the cone frustum-shaped air chamber body is directly connected with one end of the tubular connecting ring; the upper end orifice of the tubular fixed pipe is connected with the other end of the tubular connecting ring in a sleeved type and is embedded into an inclined plane rubber seal ring which is arranged on the outer wall of the tubular connecting ring so as to ensure air tightness; and the lower end orifice of the tubular fixed pipe has a tool edge shape so as to be conveniently and directly inserted into soil. The soil gas collector provided by the invention is extremely convenient to manufacture, use and maintain, has low cost, can be suitable for different soil environments such as mountains, plains, wetlands and the like through sample plot investigation, is extremely flexibly used, meets the requirements of field environments and has accurate acquired data.

The invention discloses a forest above-ground biomass remote sensing estimation general model construction method. Remote sensing data is preprocessed first to obtain a normalized data set with the remote sensing data of Landsat from 1987 to 2011 and 6 periods of measured data as data sources; a sample plot remote sensing factor, the biomass value and a change value are calculated; static and dynamic models of the forest above-ground biomass are constructed through multiple regression, linear simultaneous equations, geographical weighted regression and linear models; and the optimal model is determined as the general model of the forest above-ground biomass through verification, and a parameter form of the model is given. The invention fully exploits the relationship between the change ofthe remote sensing factor and the forest biomass change, therefore, the uncertainty caused by the estimation of single-period remote sensing data is reduced; the forest above-ground biomass model is constructed through a linear mixed model, therefore, the simulation and prediction accuracy is greatly improved; and the constructed general model can be used for real-time and on-site estimates of theforest biomass.

The invention discloses a tree survey method by using a close-range common digital camera. Take the common digital camera to shoot fixed sample plot. Modeling to deal with homonomial image points by renewing tree three-space and interpolating arbitrary point coordinate by fitting part curvilinear equation. To calculate tree survey factors including diameter height, any diameter, tree height and crown capacity etc. Making the best of handiness and flexibility of digital camera can shorten measured cycle. Dealing with data by computer modeling and calculating various tree survey factors by using characteristic point coordinates of the renewed tree three-space can largely improve the precision and work efficiency of forest resources investigation, which can reduce the cost greatly.

The invention relates to a method for enhancing the drought resistance of festuca arundinacea by adopting domesticated plant seeds. The process of domesticating the festuca arundinacea by a domestic garbage compost substrate comprises the following steps that: the domestic garbage compost substrate is flatly spread on a sample plot, then the compost becomes compact and flat by press, and the average thickness of the compost substrate is 20cm; the sowing mode is spring sowing, water in the compost substrate, which is used for domesticating the festuca arundinacea in each year, only depends on natural precipitation, and the seeds of the festuca arundinacea are harvested after 4 domestication years; then, the seeds of the domesticated festuca arundinacea are sown in a soil substrate according to 130/m2 in spring, the temperature is controlled at 20 to 26 DEG C, the relative humidity is 30 to 50 percent, the seeds are fully watered at the initial stage of sowing, and the conditions that the seeds can successfully germinate and seedlings grow at the initial stage are ensured; water is quantitatively supplied according to the stress degree of the water content after two weeks, 55 to 65 percent of the field moisture capacity is reached, and the experimental period is 38d; and the festuca arundinacea and the substrate are mown after being cultured for 38d, the festuca arundinacea is cleanly rinsed by using distilled water, and the index of the drought resistance of the domesticated festuca arundinacea is measured.

The invention discloses a complex heterogeneity forest stand mean height estimating method based on multisource remote sensing data. The complex heterogeneity forest stand mean height estimating method is a multi-data source multi-kind information forest stand mean height estimating technology which integrates the phase and amplitude information of a polarization interference radar, vegetation index information, entropy information reflecting a forest structure, second class investigation information and sample-plot survey information. The spectral information and the structure complexity of a forest are reflected by introducing the vegetation index (NDVI) and the entropy in the information theory in the technology. According to specific forest conditions, different compensation factors are given to different forest stands, and a compensation factor function is established. A coherent phase-amplitude algorithm is improved by using the changed compensation factor after correction to replace a constant compensation factor. Large area, high precision and fast extraction and charting of the forest stand mean height of a complex forest structure in a cloud and rain area are achieved.

The invention relates to a pair of waterproof wicking shoes, belonging to the technical field of human daily living goods; the shoes comprise soles, footwear uppers which are combined with the soles, shoe-tops that are combined with the sample plot and soles and tongues that are arranged on the shoe-tops in an extending way; the shoes are characterized in that the shoe-tops is formed by combining a first water resisting layer, a first connecting layer and a first wicking layer, wherein, the first connecting layer is positioned between the first water resisting layer and the first wicking layer which is positioned at the outer side of the first connecting layer, and the first wicking layer is positioned at the inner side of the first connecting layer. The waterproof wicking shoes have the advantages that as the shoe-tops, the tongues and insoles is made of laminated unidirectional wicking fabric which is composed of three layers, and has air permeability and waterproof performance, on the one hand, moisture formed in the shoes is easy to emit; on the other hand, the outside moisture is prevented entering the shoes; therefore, the shoes play the role of protection; the shoes also can keep the internal environment dry, thus being beneficial to the health care of human feet; the shoes have simple structure, convenient processing and manufacture as well as low cost.

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 provides a device for determining soil respiration and carbon isotopes. The device comprises an air suction pipeline, a carbon dioxide filter, a soil air chamber and a carbon isotope analyzer. An air inlet hole of the carbon dioxide filter is connected with the air suction pipeline. An air outlet hole of the carbon dioxide filter is connected with the soil air chamber. The soil air chamber is connected with the carbon isotope analyzer through an air path pipeline. The invention further provides a method applying the device for determining soil respiration and carbon isotopes. The device is arranged on a sample plot for directly obtaining soil respiration data, sampling is not needed back to a laboratory, no damage is caused to plants, and the device is rapid and convenient to use; the adopted device can achieve measurement in the day, at night and when it rains, and complete tree respiration information within one season and one year can be obtained.

The invention relates to the field of soil ecology, in particular to a method for evaluating influences of global changes on agricultural soil animals on the basis of in-situ earth pillar displacement. The method aims to solve the problems that a sample plot treatment area and the sample plot external environment climate are inconsistent and air in the sample plot treatment area does not circulate in an existing method. The method comprises the first step of in-situ soil preparation, the second step of manufacturing of soil animal PVC isolation boxes, the third step of moving of in-situ earth pillars, the fourth step of plant cultivation or vegetation removal, the fifth step of soil temperature and humidity monitoring and the sixth step of sampling and analyzing. According to the method, in the moving process of the in-situ earth pillars, a plough layer and a plough pan are differentiated, it is guaranteed that the layer where the soil animals are most active is located at the same position all the time, communication of the soil animals is blocked through the soil animal PVC isolation boxes, and meanwhile the bottoms of the soil animal PVC isolation boxes are covered with gauze so that normal water and nutrient circulation of soil can be kept.

The invention relates to a national forest resource continuous checking cloud platform and a sample plot monitoring method, the cloud platform comprises a sensing layer, a network layer, a platform layer, a data layer, an application layer and a user layer, and the invention provides a sample plot monitoring method, through executing checking sample plot reset and equipment layout, checking sample plot data automatic acquisition, and checking sample plot dynamic monitoring management, the data of the checking sample plot can be automatically acquired. According to the method, a national forest resource continuous checking cloud platform is operated, manual investigation is replaced by automatic monitoring, a national forest resource continuous checking work organization mode is changed, fixed time interval investigation is replaced by real-time monitoring, and the working efficiency is improved. According to the invention, national forest resource continuous checking global and all-weather real-time continuous monitoring is realized, the organization and guarantee difficulty of forest sample plot investigation work is greatly reduced, the investigation work danger is reduced, the investigation work and personnel technical requirements are reduced, the investigation work quality control difficulty is reduced, and the repeated work of investigation and quality inspection work is greatly reduced.

The invention discloses a multi-classifier fusion-based land unused condition prediction method. The method includes the following steps that: step A, training sample plots are selected, the characteristic data of the plots are extracted, the plots are manually divided into unused plots, used plots and undetermined plots according to land unused condition standards; step B, with the characteristic data of the training samples adopted as classifier input and the categories of the training samples adopted as desired output, a plurality of different classification models are trained separately; step C, the characteristic data of a plot to be predicted are extracted and are inputted into a plurality of classifiers, the classification results of the plurality of classifiers are obtained; and step D, a confidence-based classifier fusion method is adopted to fuse the classification results of the plurality of classifiers, so that the land unused condition prediction result of the plot to be predicted is obtained. The invention also discloses a multi-classifier fusion-based land unused condition prediction device. With the multi-classifier fusion-based land unused condition prediction method and device of the invention adopted, land unused conditions can be accurately predicted, and therefore, scientific basis can be provided for the use, planning and management of land.

The invention relates to a forest calculating and measuring method for observing a sample plot composed of fiver trees. A compass and a tape serve as tools, a polygonal sample plot composed of the five trees, including one tree in the center and four trees, in the surrounding is selected, the magnetic azimuth of each tree is measured, the uniform angle index, the mingling degree, the size ratio, the uniformity, the layered ratio, the volume of wood and the average height of the sample plot are calculated via mathematical models, and the characteristic parameters of the forest are rapidly estimated. The used tools are simple, and the efficiency and precision in calculating and measuring the structural parameters and the sample plot of the forest are improved.

The invention discloses a normal case photography forest metrology method through a common digital camera. The method comprises the following steps: setting a sighting rod as a measurement reference object at a place which is farthest away from a shooting point on the sample plot edge under random topographic condition, and measuring two parameters, namely the diameter at breast height and the tree height of each sample tree in the sample plot by utilizing fixed focus horizontal normal case photography. According to the method, the defects that the data acquisition period is long, the efficiency is low and the precision is low in the traditional method for measuring the diameter at breast height and tree height of sample trees are overcome, the efficiency and precision are improved, and the period is shortened.

The invention discloses a forest ecological function evaluation method based on forest resource second-class investigation and GIS. The method is based on forest resource second-class investigation. The method comprises steps of sampling and selecting N forest micro-sample plots in a forest subcompartment; establishing a forest subcompartment database by using a GIS technology, wherein the database comprises eight factors of forest accumulation, forest naturalness, community structure, tree species structure, forest stand average height, canopy density, vegetation total coverage and dry branchand fallen leaf thickness grade; calculating the comprehensive score Yj of each subcompartment through a formula, then calculating the comprehensive score Y of N subcompartments of the whole forest farm, finally solving a forest ecological comprehensive index K, and determining the forest ecological function grade of the forest farm.

The invention relates to a remote sensing estimation method for weight of withered grass in a non-growing season on desert grassland. The remote sensing estimation method comprises the following steps: acquiring land utilization data in a study area; selecting a withered grass sample plot; determining the weight of the withered grass in the sample plot; calculating vegetation index of the sample plot; determining the best spectrum index for estimating the weight of the withered grass and a remote sensing model; calculating the best spectrum index of the study area in a to-be-estimated date; carrying out remote sensing estimation on the weight of the withered grass in the study area in the to-be-estimated date; and carrying out remote sensing dynamic estimation study on the weight of the withered grass in the non-growing season in the study area. The remote sensing estimation method provided by the invention has the advantages that the gap of estimation of the weight of the withered grass in the non-growing season on the desert grassland based on MODIS remote sensing data is made up, a new method is provided for timely and accurately estimating the weight of the withered grass in the non-growing season on the desert grassland in a large regional scale range, quick and accurate monitoring on the weight of global regional withered grass in the non-growing season on the desert grassland based on the MODIS remote sensing data is realized, and a scientific basis is provided for ecological research and sustainable use of the desert grassland.

The invention discloses a mixed effect model for predicting large-area subtropical forest biomass, belonging to the technical field of forest management and related to an extraction technology of forest biomass. By relatively convenient data acquisition approaches and relatively less capital and personnel investment, an extraction technology aiming at large-area subtropical forest biomass is designed. The technology is mainly composed of five stages including extraction of laser radar data feature variables, ground sample plot data stem volume estimation, model construction and model verification based on vegetational forms and biomass calculation based on the stem volume and a biomass relative growth model. The technology improves biomass estimation precision of a laser radar method in alarge-scale forest, and provides a simplified technical solution for an airborne laser radar in forestry reconnaissance application of a large-area subtropical forest.