CN111667879A - Moso bamboo forest stand structure optimization method based on minimum entropy - Google Patents
Moso bamboo forest stand structure optimization method based on minimum entropy Download PDFInfo
- Publication number
- CN111667879A CN111667879A CN202010692804.8A CN202010692804A CN111667879A CN 111667879 A CN111667879 A CN 111667879A CN 202010692804 A CN202010692804 A CN 202010692804A CN 111667879 A CN111667879 A CN 111667879A
- Authority
- CN
- China
- Prior art keywords
- diameter
- age
- moso
- stand
- moso bamboo
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 244000302661 Phyllostachys pubescens Species 0.000 title claims abstract description 238
- 235000003570 Phyllostachys pubescens Nutrition 0.000 title claims abstract description 238
- 238000005457 optimization Methods 0.000 title claims abstract description 95
- 238000000034 method Methods 0.000 title claims abstract description 49
- 210000000481 breast Anatomy 0.000 claims abstract description 102
- 235000017166 Bambusa arundinacea Nutrition 0.000 claims description 45
- 235000017491 Bambusa tulda Nutrition 0.000 claims description 45
- 241001330002 Bambuseae Species 0.000 claims description 45
- 235000015334 Phyllostachys viridis Nutrition 0.000 claims description 45
- 239000011425 bamboo Substances 0.000 claims description 45
- 238000003306 harvesting Methods 0.000 claims description 29
- 238000005520 cutting process Methods 0.000 claims description 18
- 210000000038 chest Anatomy 0.000 claims description 9
- 241000745988 Phyllostachys Species 0.000 claims description 3
- 230000008901 benefit Effects 0.000 abstract description 6
- 230000008859 change Effects 0.000 description 13
- 238000011160 research Methods 0.000 description 10
- 241000196324 Embryophyta Species 0.000 description 9
- 238000004519 manufacturing process Methods 0.000 description 6
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 5
- 229910052799 carbon Inorganic materials 0.000 description 5
- 238000005184 irreversible process Methods 0.000 description 5
- 241000544043 Blyxa aubertii Species 0.000 description 4
- 238000009826 distribution Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
- 239000002028 Biomass Substances 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- 239000002023 wood Substances 0.000 description 3
- 244000050510 Cunninghamia lanceolata Species 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 241001522633 Betula utilis subsp. albosinensis Species 0.000 description 1
- 239000008830 Carthamus tinctorius Honghua extract Substances 0.000 description 1
- 235000018782 Dacrydium cupressinum Nutrition 0.000 description 1
- 240000006055 Dacrydium cupressinum Species 0.000 description 1
- 235000013697 Pinus resinosa Nutrition 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 238000004177 carbon cycle Methods 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 230000000739 chaotic effect Effects 0.000 description 1
- 235000009508 confectionery Nutrition 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000013401 experimental design Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 230000002195 synergetic effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B5/00—ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Medical Informatics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Biotechnology (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Biophysics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Data Mining & Analysis (AREA)
- Mining & Mineral Resources (AREA)
- Bioethics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physiology (AREA)
- Databases & Information Systems (AREA)
- Epidemiology (AREA)
- Evolutionary Computation (AREA)
- Public Health (AREA)
- Software Systems (AREA)
- Agronomy & Crop Science (AREA)
- Animal Husbandry (AREA)
- Marine Sciences & Fisheries (AREA)
- Artificial Intelligence (AREA)
- Molecular Biology (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Medicines Containing Plant Substances (AREA)
Abstract
The invention discloses a moso bamboo stand structure optimization method based on minimum entropy, which comprises the steps of respectively optimizing a moso bamboo stand structure by adopting a constrained nonlinear model and a real stand structure adjustment mode, and comparing optimization results of the two optimization modes, wherein the constrained nonlinear model optimization mode is used for optimizing and solving a model by constructing a minimum entropy breast diameter structure optimization model and an age structure optimization model to obtain an optimization result of the moso bamboo stand breast diameter structure and the age structure; the adjustment and optimization mode of the structure of the real forest stand is realized by combining the actual conditions of the moso bamboo forest stand through the statistics of age grade and diameter grade and carrying out comprehensive structure adjustment on each age grade and diameter grade moso bamboo in a felling mode respectively to obtain the breast diameter structure and age structure optimization results of the moso bamboo forest stand. The method has the advantages that the moso bamboo stand structure is optimized in two modes of a nonlinear model with constraint and real stand structure adjustment, inspiration is provided for the operation of the moso bamboo stand, and the productivity of the moso bamboo is promoted.
Description
Technical Field
The invention relates to a moso bamboo stand structure optimization method, in particular to a moso bamboo stand structure optimization method based on minimum entropy.
Background
Mao bamboo is the best in the south of ChinaThe forest type is the most important and typical bamboo forest resource type, China is one of the most abundant countries of bamboo forest resources, and according to the 8 th national forest resource continuous checking result, the bamboo forest area of China is 600 ten thousand hm2China is the major country of Mao bamboo, and the area of the Mao bamboo forest is 443 ten thousand hm2The area of the bamboo forest is about 70 percent of the area of the bamboo forest in China, the moso bamboos have the characteristics of fast growth, high yield, wide application, short period and the like, are important food and economic sources for bamboo farmers in mountainous areas, and according to research, the annual carbon fixation amount of the arbor layer of the moso bamboo forest is 5.097 thm-2(Zhou national model, Jiang Peikun, 2004), 1.46 times of China fir in fast growing stage (Fangqing et al, 2002), 1.33 times of rain forest in tropical mountain area (Li Ityd et al, 1998), and 2.16 times of China fir forest in 27 years in Sunan (Ruan hong Hua et al, 1997), so the Mao bamboo stand has very strong carbon sink function.
The structure of the moso bamboo stand refers to the distribution state of moso bamboos in the stand, is an important parameter for determining multiple functions of the moso bamboo stand, is also the basis and the performance of the stand function, and comprehensively reflects the development process of the stand, such as updating mode, competition, natural sparseness and experienced interference, and a plurality of characteristic factors in the stand, such as diameter, tree height, shape number, wood quality, age, tree species composition and the like, have a certain distribution rule no matter whether the forest is an artificial forest or a natural forest and under the condition of not suffering from serious natural or artificial interference and long-term natural growth loss and succession. In the actual forestry production, people perform necessary intervention such as felling, updating, tending and thinning on a forest stand structure according to the change rule of the forest stand structure, so that the forest stand structure develops towards the expected direction, therefore, the analysis and reconstruction of the moso bamboo forest stand structure are an important basis for developing a new generation of moso bamboo forest stand growth model and a premise for making a moso bamboo forest management planning scheme, and the method has important practical significance for moso bamboo forest resource investigation, an operation number table, sustainable back technology system and the like, and the research of the moso bamboo forest stand structure becomes the key and hot problem of the research of people under the historical background that global climate change and global carbon cycle are widely concerned by scholars at home and abroad.
Various human operation activities directly influence and change the moso bamboo stand structure, further influence the play of multiple functions of moso bamboo, lead the moso bamboo to an ideal state and a top-level state through the stand structure optimization, keep the health and the stability of the moso bamboo ecological system, further fully play multiple functions and multiple benefits of the moso bamboo, therefore, the optimization of the stand structure is the key of scientific and effective forest culture and management technology and the sustainable development of the moso bamboo.
At present, researches on forest stand structure optimization include that a forest stand structure mode for bamboo shoots is optimized by a Chenshuanglin, a high-yield forest stand structure mode (Chenshuanglin, 2005) for the forest shoots is obtained through optimization, the Chenshuanglin optimizes a forest stand structure for a Boshi sweet dragon bamboo shoot seedling, and by adopting different forest stand structure combinations, the aims of researching the age-level structure of a bamboo shoot seedling dual-purpose bamboo shoot, namely, the high-yield bamboo shoot can be realized and high-quality bamboo shoots can be produced (Chenshuanglin, 2003), and the Zhuglan 25035and the like are carried out on the age-level structure of the bamboo shoot dual-purpose moso bamboo shoot, wherein the ratio of each age-level is l age level: 2, age class: 3, age class: the 4 th age group is 30: 30: 30: 10 or so, the forest stand productivity can be improved (zhuangliv 25035, 2000), liu en bin and the like establish a nonlinear constraint equation to study the non-spatial structure of the moso bamboo forest, and the study is considered as an l age level: 2, age class: 3, age class: the 4 th age is 1: 1: 1: 1, N ═ 4363 (Strain/hm)-2)，Dg12.1691(cm), the carbon reserve of the bamboo forest stand reaches the maximum (Liu bin, 2012), Hao and Q establish a forest stand structure optimization model to obtain the optimal forest stand structure of large-diameter-order forest trees (Hao, Q, 2006), Jin and X establish a multifunctional optimization model for wood production, seed production and carbon reserve, the purpose is to research an optimal rotation-down period to enable various benefits of the red pine forest to reach the maximum (Jin, X, 2017), Hof J and the like to research an optimization model combining single forest selection and natural updating, but the operation target of the model is still wood harvesting, the influence of harvesting on the forest structure is not considered too much (Hof J, 2000), the restriction condition is established or the forest stand structure is optimized by experimental design under the preset target, and for researching the optimality of the forest stand state, a system is used, and the vigorous vitality can be kept only if the state reaches the optimum, the development of the moso bamboo is more durable and sustainable, the entropy is a quantity for describing the disorder degree of the system state, the state of the system is more ordered when the entropy is smaller, and therefore how to research the optimal state of the moso bamboo by adopting the minimum entropyThe forest stand structure is a large direction for the optimization research and development of the current forest stand structure.
Disclosure of Invention
The invention aims to provide a moso bamboo stand structure optimization method based on minimum entropy. The method has the advantages that the moso bamboo stand structure is optimized by using a nonlinear model with constraint and a real stand structure adjustment mode, inspiration is provided for the operation of the moso bamboo stand, and the promotion of the moso bamboo productivity is facilitated.
The technical scheme of the invention is as follows: a moso bamboo stand structure optimization method based on minimum entropy adopts two modes of a nonlinear model with constraint and real stand structure adjustment to respectively optimize the moso bamboo stand structure, and compares the optimization results of the two optimization modes;
the nonlinear model optimization mode with constraints comprises the following steps:
step A, setting the chest diameter structure or the age structure of a moso bamboo forest stand in a certain year in a target area as a set S in a discrete state, and setting the probability space of S as follows:
in the formula siIndicating the ith diameter or age, p, of the Phyllostachys pubescensiA probability of being the ith radial or age;
b, constructing a minimum entropy breast diameter structure and age structure optimization model of the moso bamboo forest stand structure by adopting a Renyi entropy;
step C, setting constraint conditions according to the actual situation of the moso bamboo stand;
d, constructing a minimum entropy breast diameter structure optimization model and an age structure optimization model;
e, according to the Kuen-Tack condition, writing a program by matlab software to carry out optimization solution on the minimum entropy breast diameter structure optimization model and the age structure optimization model to obtain an optimization result of the breast diameter structure and the age structure of the moso bamboo forest stand;
step F, substituting the average breast diameter of the optimal breast diameter structure into the relation between the average breast diameter of the forest stand and the number of plants
In the formula, N represents the number of the moso bamboos per mu, and D represents the number of the moso bamboos per mugThe mean breast diameter of the forest stand;
the adjustment and optimization mode of the real forest stand structure comprises the following steps:
firstly, continuously checking data of a plurality of moso bamboo sample plots in a certain year, and performing statistical sorting to obtain a statistical table containing age grades and diameter grades;
combining the actual situation of the moso bamboo stand, and respectively carrying out comprehensive structure adjustment on each age-grade moso bamboo and each diameter-grade moso bamboo in a felling mode according to the age grade and the diameter grade in the statistical table;
step three, summarizing and counting the moso bamboo stand structures obtained by each felling and corresponding entropy values, and further obtaining the optimization results of the breast diameter structures and the age structures of the moso bamboo stands;
step ④, substituting the average breast diameter in the optimal breast diameter structure into the relation between the average breast diameter of the forest stand and the number of plants
In the formula, N represents the number of the moso bamboos per mu, and D represents the number of the moso bamboos per mugThe mean breast diameter of the forest stand.
In the foregoing method for optimizing a moso bamboo forest stand structure based on minimum entropy, the Renyi entropy in step B is defined as:
where a is the adjustable parameter, n is the maximum number of radial steps or age classes, p(s)i) The probability of the ith radial or ith age.
In the method for optimizing a moso bamboo forest stand structure based on minimum entropy, the minimum entropy breast-height structure optimization model in step D is as follows:
wherein n is the maximum diameter step of the moso bamboo, saveRepresents the average breast diameter p(s) of the bamboo stands after rounding and roundingi) Probability of i radial order or i age order, p(s)ave) The probability corresponding to the mean chest diameter is used.
In the method for optimizing a moso bamboo forest stand structure based on minimum entropy, the minimum entropy age structure optimization model in step D is as follows:
in the method for optimizing a moso bamboo forest stand structure based on minimum entropy, the constraint conditions in step C are as follows: firstly, in the moso bamboo stand, the probability of the diameter order smaller than the average breast diameter is smaller than that of the average breast diameter; secondly, the probability of the radial order of more than or equal to 14cm is less than the probability of the average chest diameter; third, the probability of each radial order is equal to or greater than 0, and the sum of all radial order probabilities is equal to 1.
In the method for optimizing the structure of the moso bamboo forest stand based on the minimum entropy, the step ii of performing comprehensive structure adjustment in a felling manner includes:
the method comprises the following steps of sequentially felling 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age level each time, and not felling moso bamboos of other age levels;
the method comprises the following steps of (1) harvesting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain diameter grade in sequence each time, and not harvesting moso bamboos of other diameter grades;
the method comprises the following steps of sequentially cutting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age grade and a certain diameter grade every time, and not cutting moso bamboos of other age grades and diameter grades;
sequentially cutting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age level each time, and cutting moso bamboos of other ages after the moso bamboos of the certain age level are cut;
the method comprises the following steps of (1) harvesting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain diameter grade in sequence each time, and harvesting moso bamboos of other diameter grades after the moso bamboos of the certain diameter grade are harvested;
the method comprises the steps of harvesting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age grade and a certain diameter grade in turn each time, and harvesting moso bamboos of other ages grades and diameters after the moso bamboos of the age grade and the diameter grade are harvested.
Compared with the prior art, the method has the advantages that entropy analysis is carried out on the forest stand structure, the state of the forest stand structure is measured through the entropy, continuous checking data of a moso bamboo sample plot are utilized, the moso bamboo forest stand structure is optimized through a constrained nonlinear model and a real forest stand structure adjusting mode, the optimization results are analyzed and compared, and the moso bamboo forest stand structure optimization method based on the minimum entropy is obtained; specifically, a constrained nonlinear model optimization mode is used for optimizing and solving a minimum entropy breast diameter structure optimization model and an age structure optimization model by constructing the minimum entropy breast diameter structure optimization model and the age structure optimization model and writing a program by matlab software according to the Kuen-Tack condition to obtain a moso bamboo forest stand structure optimization result; the adjustment and optimization method of the structure of the real bamboo stands is characterized in that data obtained by continuously checking a plurality of moso bamboo sample plots of a certain year are subjected to statistical arrangement to obtain a statistical table containing age classes and diameter classes, then the actual situation of the moso bamboo stands is combined, the age classes and the diameter classes in the statistical table are taken as the basis, comprehensive structure adjustment is respectively carried out on the moso bamboos of all the age classes and the diameter classes in a felling mode, the structures of the moso bamboo stands obtained by felling each time and corresponding entropy values are subjected to summary statistics, and the optimization result of the structure of the moso bamboo stands is obtained.
In conclusion, the method has the advantages that the moso bamboo stand structure is optimized in two modes of the nonlinear model with the constraint and the real stand structure adjustment, the inspiration is provided for the operation of the moso bamboo stand, and the improvement of the moso bamboo productivity is facilitated.
Drawings
Fig. 1 is a schematic diagram of the relation between an adjustable parameter a and entropy.
The invention is further illustrated by the following figures and examples, which are not to be construed as limiting the invention.
Example (b): a moso bamboo stand structure optimization method based on minimum entropy carries out theoretical basis of entropy analysis on stand structures:
the entropy is a state function and is used for measuring the chaos degree of a system, the entropy is also a quantity for describing the uncertainty of the system, the larger the entropy value is, the larger the uncertainty in the system is, the more chaos the system is in operation, the lower the efficiency is, and the system function is degraded.
The moso bamboo forest exchanges substances, energy and information with the environment, so the moso bamboo forest stand is an open system, S represents the biological entropy value of the moso bamboo forest stand, dS represents the entropy change of the moso bamboo forest stand, and Lijin decomposes the entropy change dS of the system into the sum of two terms, namely:
dS＝dSe+dSi
in the formula dSeRepresenting the entropy change caused by the exchange of energy and substances between the system and the outside world, called entropy flow term, whose value can be positive, negative or zero, and generally has no definite sign; dSiRepresenting the entropy change produced by an irreversible process occurring within the system, called entropy production, whereas according to the second law of classical thermodynamics, the entropy-producing term dS, caused by an irreversible processiAlways positive, i.e. dSiIs greater than 0, so that the entropy change dS of the open system is not necessarily greater than zero, but can be equal to or less than zero, when the moso bamboo forest is subjected to extreme climate or man-made negative interference, the dS iseAt the moment, the moso bamboo forest declines rapidly, the forest stand structure tends to be in a disordered state, when the moso bamboo forest is operated artificially and scientifically, so that more moso bamboos of low age grade in the forest stand are provided and the breast diameter is larger, more energy is absorbed by the moso bamboo forest from the outside in the same time, and dS is obtained at the momenteAnd the dS is reduced, the growth state of the moso bamboo forest is good, and the forest stand structure tends to be ordered.
The phyllostachys pubescens forest grows under the synergistic effect of system entropy flow and entropy generation when dSe＝-dSiThat is, the negative entropy flow absorbed from the outside exactly offsets the entropy generation caused by the irreversible process in the system, and the system is in a fixed state with macroscopic property not changing along with time, in this case, the moso bamboo forest only maintains the state of the current forest stand structure, so the forest stand structure in the fixed state is not necessarily optimal; when dSeWhen the total entropy of the forest stand is less than zero but is very close to zero, the total entropy change of the forest stand mainly depends on the generation of the internal entropy, and in this case, the system cannot generate any new structure, and the forest stand is degraded; if dSeFar less than zero, it shows that the mao bamboo forest stand constantly obtains material and energy absorption negative entropy flow from the external environment, and the total entropy value of system will reduce, and the orderliness increases, and information (negative entropy) volume increases, and the vitality and the carbon fixation function of mao bamboo forest all strengthen, and under this condition, mao bamboo forest stand probably forms a new organizational structure, and the mao bamboo forest rises to the higher one-level ordered structure from certain ordered structure promptly, so mao bamboo forest avoids the degradation, just must constantly obtain a certain amount of negative entropy from the external world.
The method is characterized in that the aging of the moso bamboo stands and the internal mutual competition lead to the generation and continuous increase of positive entropy, the positive entropy of the forest stands is the disordered root cause and is also the source of unstable forest stand structures, the continuous increase of the positive entropy leads to the reduction of the functions of the forest stand structures, the productivity of the moso bamboo stands is reduced, the entropy produced by artificial scientific management is negative entropy, the accumulated-removing influence caused by the positive entropy can be inhibited, and the ordered state of the forest stand structures is maintained, so the negative entropy is the source of ordered forest stand structures, the generation of the positive entropy of the forest stands has spontaneity and initiative to some extent, even the generation of the positive entropy is considered to be a necessary result of the moso bamboo stands, and the generation of the negative entropy of the forest stands is not.
There are two ways for the moso bamboo forest stand to absorb the negative entropy flow from the outside: 1) continuously absorbing useful substances and energy from the environment, simultaneously releasing wastes, namely continuously metabolizing, going against failure and accepting new things, thereby obtaining extremely precious negative entropy, and 2) inputting the negative entropy to the phyllostachys pubescens forest by scientifically cutting and digging bamboo shoots so as to reduce the irreversible entropy change in the phyllostachys pubescens forest. The artificial scientific management can generate negative entropy by the moso bamboo forest, inhibit positive entropy, reduce total entropy change of the moso bamboo forest stand, increase the orderliness of the forest stand, and better maintain the long-term productivity of the moso bamboo forest, so the orderliness and stability of the moso bamboo forest in the aspects of structure and function are maintained by continuous negative entropy flow from the outside, and the stability of an ecosystem is realized through an entropy minimization process. The method mainly researches the forest stand structure of the moso bamboo forest, and the moso bamboo forest has the smallest total entropy and the most ordered system.
The entropy of the moso bamboo forest stand is not a conservative quantity, and the change of the total entropy of a system along with time can be expressed as:
in the formula, JSRepresenting the exchange rate through entropy per unit area, i.e. entropy flow, and σ represents the rate at which entropy is produced per unit volume, i.e. entropy production, then there are:
if ρkGeneralized flow, X, representing the k-th irreversible process related to ratekGeneralized forces representing the kth irreversible process related to the impulse force, entropy production can be expressed as:
the generalized force is a cause of generation of a generalized flow, which can be considered to be some function of the generalized force.
Since the bamboo forest stand structure is subject to external interference, it can be described by the logistic equation:
where K is the environmental capacity, N is the generalized flow,
is a generalized force.
For the non-linear region of the non-equilibrium state, the generalized force X is:
the generalized stream ρ ═ N, the entropy is generated as:
when in use
When is dSi> 0, the system was stable.
When in use
Or
When is dSiAt 0, the system is in a critical state.
When in use
Occasionally, the system is stable both locally and globally (Ma Shijun, 1989; Yuanetianxiang, 1991).
The method adopts two modes of a nonlinear model with constraint and real stand structure adjustment to respectively optimize the moso bamboo stand structure, and compares the optimization results of the two optimization modes;
data sources, Zhejiang province established a forest resource continuous checking system in 1979, taking 5 years as a re-checking period, and totally setting 4250 fixed sample plots, wherein the sample grid is 4km × 6km, the sample plots are square, the side length is 28.28m, and the area is 800m2. 177 continuous checking sample plots of moso bamboos in 2009 are used for research, and the basic conditions of the moso bamboo sample plots are as follows: the number of the moso bamboo plants in each sample plot is 22-897, the diameter of the breast in the moso bamboo in each sample plot is 5-15 cm, and the age is 1-4 degrees (the current-year-old bamboo is 1 degree bamboo; the 2-3-year-old bamboo is 2 degree bamboo)Bamboo, and so on). The survey factors of the sample plot include soil thickness, slope direction (1: north, 2: north-east, 3: east, 4: south-east, 5: south, 6: south-west, 7: west, 8: north-west, 9: mountain top without slope), slope position (1: ridge, 2: upper, 3: middle, 4: lower, 5: valley, 6: flat), slope, elevation (10m-1200m), average breast diameter of the sample plot, number of sample plots, breast diameter and age of each moso bamboo in the sample plot, and the like.
In China, moso bamboo is a special regional plant, which is different from other plants in that: 1) the diameter at breast height growth and high growth of the moso bamboo are completed in the first year; 2) the bamboo shoots and bamboo shoots of the moso bamboo forest appear every other year, namely the habit of the young and the old, so the stand age structure of the moso bamboo forest is divided into 1 age class according to 2 years; 3) for a single bamboo plant, when the growth of the breast diameter and the height of the bamboo are finished, the breast diameter and the height of the bamboo are not changed any more, but the biomass of the bamboo is changed, and the change of the biomass is mainly caused by age; 4) the moso bamboo forest is a different-age forest, so the age is an important characteristic of the forest stand structure besides the breast diameter; 5) the moso bamboo stand density is one of important factors influencing the growth of the moso bamboo stand, the growth of overground and underground parts of the forest stand is restricted at each age and each breast diameter stage of plants, competition or mutual interference of the plants to resources is caused (Turkton R et al,2005), and the stand density control is an effective means in forest culture measures, so the influence of the adjustment of the stand density on the structure of the moso bamboo stand is great. Based on the analysis of the characteristics of the moso bamboo stand, the paper selects the growth amount in the bamboo shoot period, the stand density, the stand age, the sample plot biomass and the stand breast diameter as basic indexes influencing the structure of the moso bamboo stand. In this study, considering that the average breast diameter (there are many kinds of forest stand structures with the same average breast diameter) and the average age cannot accurately describe the breast diameter structure and the age structure of the moso bamboo stand, the breast diameter and the age of the moso bamboo stand are represented by the proportion of each breast diameter and the proportion of each age in the forest stand.
The nonlinear model optimization mode with constraints comprises the following steps:
step A, setting the diameter of breast or age structure of a moso bamboo forest stand in a certain year of a target area as a set S in a discrete state (S ═ D is the diameter of breast and S ═ A is the age structure), and setting the probability space of S as:
in the formula siIndicating the ith diameter or age, p, of the Phyllostachys pubescensiA probability of being the ith radial or age;
the Shannon information entropy of set S is defined as:
the Rneyi entropy is defined as:
where a is the adjustable parameter, n is the maximum number of radial steps or age classes, p(s)i) A probability of being the ith radial or age;
compared with Shannon entropy, Renyi entropy introduces a tunable parameter a, the description of the information quantity is more flexible and general, and when a → 1, R (S) → H (S), the Shannon entropy can be regarded as a special form of Renyi entropy. Therefore, the minimum entropy breast diameter and age structure optimization model of the moso bamboo forest stand structure is constructed by adopting the Renyi entropy.
B, constructing a minimum entropy breast diameter structure and age structure optimization model of the moso bamboo forest stand structure by adopting a Renyi entropy;
and C, setting constraint conditions according to the actual situation of the moso bamboo forest stand, wherein the constraint conditions are as follows: firstly, in the moso bamboo stand, the probability of the diameter order smaller than the average breast diameter is smaller than that of the average breast diameter; secondly, the probability of the radial order of more than or equal to 14cm is less than the probability of the average chest diameter; thirdly, the probability of each radial order is greater than or equal to 0, and the sum of the probabilities of all radial orders is equal to 1;
d, constructing a minimum entropy breast diameter structure optimization model and an age structure optimization model;
the minimum entropy breast diameter structure optimization model is as follows:
wherein n is the maximum diameter step of the moso bamboo, saveRepresents the average breast diameter p(s) of the bamboo stands after rounding and roundingi) Probability of i radial order or i age order, p(s)ave) The probability corresponding to the mean chest diameter is used.
The p(s)ave) The calculating method of (2):
1) fitting 3-parameter weibull probability density function for moso bamboo diameter distribution data of the year of the object region
Parameter a is-0.421102; 9.194212; c is 4.357042; the coefficient was determined to be 0.9967 at this time; wherein x is the diameter of breast, and a, b and c are parameters;
2) if the determined coefficient obtained by fitting is very high and reaches more than 0.95, the diameter of the moso bamboo breast height is subject to weibull distribution;
3) calculating the average breast diameter of the moso bamboos in the year of the object area;
4) the mean chest diameter is substituted into the fitted weibull probability density function to obtain p(s)ave)。
The minimum entropy age structure optimization model is as follows:
e, according to the Kuen-Tack condition, writing a program by matlab software to carry out optimization solution on the minimum entropy breast diameter structure optimization model and the age structure optimization model to obtain an optimization result of the breast diameter structure and the age structure of the moso bamboo forest stand;
step F, substituting the average breast diameter of the optimal breast diameter structure into the relation between the average breast diameter of the forest stand and the number of plants
In the formula, N represents the number of the moso bamboos per mu, and D represents the number of the moso bamboos per mugThe mean breast diameter of the forest stand;
the average breast diameter of the optimal breast diameter structure is 11.7800 according to the relation between the average breast diameter of the forest stand and the number of plants
(k, a, b) ═ (1173.8391,0.0395, -376.953) (liun bin, 2012), R20.9587, the best number of bamboo plants per mu is 300.
The adjustment and optimization mode of the real forest stand structure comprises the following steps:
step one, carrying out statistical sorting on 177 continuous checking data of moso bamboo sample plots in 2009 to obtain a statistical table containing age grade and diameter grade, and the statistical table is shown in table 1:
table 12009 years bamboo continuous checking data statistics
Combining the actual situation of the moso bamboo stand, and respectively carrying out comprehensive structure adjustment on each age-grade moso bamboo and each diameter-grade moso bamboo in a felling mode according to the age grade and the diameter grade in the statistical table;
the moso bamboo stand structure is taken as a whole, the system state of the stand structure is taken as the most order, and the stand structure is optimized by applying the minimum entropy principle. Because the forest stand structure optimization is to select an optimal structure from a plurality of moso bamboo forest stand structures, the more comprehensive moso bamboo forest stand structure is obtained by adopting the following adjustment scheme in table 1 in combination with the actual situation of the moso bamboo forest stand;
1) the method comprises the following steps of (1) sequentially cutting 20%, 30%, 40%, …, 90% and 100% of i-th-age moso bamboos (i is N, N-1 and 1) each time, and cutting other-age moso bamboos without cutting, wherein 9 times of cutting are needed for cutting all the i-th-age moso bamboos, when the i-th-age moso bamboos are cut, the number of the other-age moso bamboo plants is kept unchanged, and each cutting corresponds to a moso bamboo forest stand structure;
2) the method comprises the following steps of (1) sequentially harvesting 20%, 30%, 40%, …, 90% and 100% of the j-th diameter-level moso bamboos (j is 1,2 and M) each time, and not harvesting the other diameter-level moso bamboos, so that 9 times of harvesting are required for completely harvesting the j-th diameter-level moso bamboos, when the j-th diameter-level moso bamboos are harvested, the number of the other diameter-level moso bamboos is kept unchanged, and each harvesting corresponds to a moso bamboo stand structure;
3) the method comprises the following steps of (1) harvesting the i-th age-level and j-th diameter-level moso bamboos sequentially each time (i is N, N-1, 1; 20%, 30%, 40%, …, 90%, 100% of j 1,2, M), and no felling of other age-level and diameter-level moso bamboos, so that 9 felling times are required for all the moso bamboos felling the i-th age-level and j-th diameter-level moso bamboos, and when the i-th age-level and j-th diameter-level moso bamboos are felled, the number of the moso bamboo strains of other age-level and diameter-level is kept unchanged, and each felling corresponds to a moso bamboo forest stand structure;
4) the method comprises the steps of sequentially harvesting 20%, 30%, 40%, …, 90% and 100% of the i-th-age moso bamboo (i is N, N-1, 1) each time, harvesting the other-age moso bamboo after the harvesting of the i-th-age moso bamboo is finished, so that when the i-th-age moso bamboo is harvested, the i + 1-th-age moso bamboo is not stored, and each harvesting corresponds to a moso bamboo forest stand structure;
5) the method comprises the following steps of (1) sequentially harvesting 20%, 30%, 40%, …, 90% and 100% of the moso bamboos of the jth diameter level (j is 1,2 and M) each time, and harvesting the moso bamboos of other diameter levels after the moso bamboos of the jth diameter level are harvested, so that when the moso bamboos of the jth diameter level are harvested, the moso bamboos of the jth diameter level are not stored, and each harvesting corresponds to a moso bamboo forest stand structure;
6) the bamboo is harvested in the ith age level and the jth diameter level sequentially each time (i is N, N-1, 1; j is 1,2, M), 20%, 30%, 40%, …, 90% and 100%, and cutting off the moso bamboos of the age class and the diameter class, and then cutting off the moso bamboos of other age classes and diameter classes, so that when the moso bamboos of the i-th age class and the j-th diameter class are cut off, the moso bamboos of the i + 1-th age class and the j-1-th diameter class do not exist, and each cutting corresponds to a moso bamboo forest stand structure.
Thus obtaining 1278 moso bamboo forest stand structures.
Step three, summarizing and counting the moso bamboo stand structures obtained by each felling and corresponding entropy values, and further obtaining the optimization results of the breast diameter structures and the age structures of the moso bamboo stands;
step ④, substituting the average breast diameter in the optimal breast diameter structure into the relation between the average breast diameter of the forest stand and the number of plants
In the formula, N represents the number of the moso bamboos per mu, and D represents the number of the moso bamboos per mugThe mean breast diameter of the forest stand.
The average breast diameter of the optimal breast diameter structure is 11.7800 according to the relation between the average breast diameter of the forest stand and the number of plants
(k, a, b) ═ (1173.8391,0.0395, -376.953) (liun bin, 2012), R20.9587, the best number of bamboo plants per mu is 300.
Optimizing the breast diameter structure:
adopting a nonlinear model with constraints to carry out the result of the optimization of the breast diameter structure:
different adjustable parameters a are selected, the corresponding relationship diagram of the diameter at breast height entropy values is shown in fig. 1, and it can be known from fig. 1 that when a is 15, the entropy value of the diameter at breast height tends to be stable, and the optimization result of the diameter at breast height is shown in table 2 below:
TABLE 2 breast diameter structure optimization results
In Table 2, Di(i ═ 5, 6.., 15.) represents the proportion of the i-th-diameter moso bamboos in the forest stand, and the entropy value of the breast diameter structure after model optimization is 0.1129.
The result of adopting the adjustment and optimization of the actual forest stand structure to optimize the breast height structure is shown in the following table 3:
TABLE 3 adjusted stand breast diameter structure and corresponding entropy
In Table 3, DiThe meaning of (A) is similar to that of Table 2, and as can be seen from tables 2 and 3, the results of the two optimization methods are basically the same, and the structure of the moso bamboo forest stand can be optimized.
Optimizing an age structure:
adopting a nonlinear model with constraints to carry out the result of age structure optimization:
when a is 8, the entropy value of the age structure tends to be stable, and the optimization result of the age structure at this time is shown in the following table 4:
TABLE 4 age Structure optimization results
At this time, the entropy of the age structure after model optimization is: 1.1217.
the results of the age structure optimization using the real stand structure adjustment optimization are shown in table 5 below:
TABLE 5 adjusted stand age Structure and corresponding entropy
As can be seen from tables 4 and 5, the results of the two optimization methods are substantially the same, and both of them can optimize the structure of the bamboo forest stand.
Optimizing the number of the bamboo forest branches:
the average breast diameter of the optimal stand structure is 11.7800 according to the relation between the average breast diameter of the stand and the number of plants
(k,a,b)＝(1173.8391,0.0395,-376.953)，R20.9587, the best number of bamboo plants per mu is 300.
The forest stand structure is an important content of forest stand characteristics and is always a key problem of research, the improvement of the bamboo forest productivity depends on the reasonable forest stand structure, and the analysis in the embodiment is combined to draw the following conclusion:
1) the entropy is used for measuring the chaos degree of a system, the larger the entropy value is, the larger the uncertainty of the moso bamboo forest stand is, the more chaotic the system operation is, the lower the efficiency is, and the forest stand function is degraded, and the negative entropy is a source of ordered forest stand structures, so that a certain amount of negative entropy needs to be input into the forest stand structure for optimization.
2) The average breast diameter of the phyllostachys pubescens forest in Zhejiang province in 2009 is 8.5083cm, and the result of optimizing the breast diameter structure of the forest stand by using the minimum entropy shows that the proportion of the phyllostachys pubescens which are lower than the average breast diameter and slightly larger than the average breast diameter in the forest stand is not more than 10%, and the phyllostachys pubescens which are larger than the average breast diameter by more than 3 and more than each diameter step are kept.
3) According to the optimization result of the age structure, the proportion of moso bamboos with 4 degrees or more in the forest stand is not more than 2%, and the breast diameter structure and the age structure optimization result are integrated, so that the moso bamboos with the average breast diameter lower than the average breast diameter, a little larger than the average breast diameter and large age are obtained through multi-harvest.
Claims (6)
1. A moso bamboo stand structure optimization method based on minimum entropy is characterized in that: respectively optimizing the moso bamboo stand structure by adopting a nonlinear model with constraint and a real stand structure adjustment mode, and comparing the optimization results of the two optimization modes;
the nonlinear model optimization mode with constraints comprises the following steps:
step A, setting the chest diameter structure or the age structure of a moso bamboo forest stand in a certain year in a target area as a set S in a discrete state, and setting the probability space of S as follows:
in the formula siIndicating the ith diameter or age, p, of the Phyllostachys pubescensiA probability of being the ith radial or age;
b, constructing a minimum entropy breast diameter structure and age structure optimization model of the moso bamboo forest stand structure by adopting a Renyi entropy;
step C, setting constraint conditions according to the actual situation of the moso bamboo stand;
d, constructing a minimum entropy breast diameter structure optimization model and an age structure optimization model;
e, according to the Kuen-Tack condition, writing a program by matlab software to carry out optimization solution on the minimum entropy breast diameter structure optimization model and the age structure optimization model to obtain an optimization result of the breast diameter structure and the age structure of the moso bamboo forest stand;
step F, substituting the average breast diameter of the optimal breast diameter structure into the relation between the average breast diameter of the forest stand and the number of plants
In the formula, N represents the number of the moso bamboos per mu, and D represents the number of the moso bamboos per mugThe mean breast diameter of the forest stand;
the adjustment and optimization mode of the real forest stand structure comprises the following steps:
firstly, continuously checking data of a plurality of moso bamboo sample plots in a certain year, and performing statistical sorting to obtain a statistical table containing age grades and diameter grades;
combining the actual situation of the moso bamboo stand, and respectively carrying out comprehensive structure adjustment on each age-grade moso bamboo and each diameter-grade moso bamboo in a felling mode according to the age grade and the diameter grade in the statistical table;
step three, summarizing and counting the moso bamboo stand structures obtained by each felling and corresponding entropy values, and further obtaining the optimization results of the breast diameter structures and the age structures of the moso bamboo stands;
step ④, substituting the average breast diameter in the optimal breast diameter structure into the relation between the average breast diameter of the forest stand and the number of plants
In the formula, N represents the number of the moso bamboos per mu, and D represents the number of the moso bamboos per mugThe mean breast diameter of the forest stand.
2. The method for optimizing the structure of the moso bamboo forest stand based on the minimum entropy as claimed in claim 1, wherein: the Renyi entropy in the step B is defined as:
where a is the adjustable parameter, n is the maximum number of radial steps or age classes, p(s)i) The probability of the ith radial or ith age.
3. The method for optimizing the structure of the moso bamboo forest stand based on the minimum entropy as claimed in claim 1, wherein: and D, the minimum entropy breast diameter structure optimization model in the step D is as follows:
wherein n is the maximum diameter step of the moso bamboo, saveRepresents the average breast diameter p(s) of the bamboo stands after rounding and roundingi) Probability of i radial order or i age order, p(s)ave) The probability corresponding to the mean chest diameter is used.
4. The method for optimizing the structure of the moso bamboo forest stand based on the minimum entropy as claimed in claim 1, wherein: and D, the minimum entropy age structure optimization model in the step D is as follows:
5. the method for optimizing the structure of the moso bamboo forest stand based on the minimum entropy as claimed in claim 1, wherein: the constraint conditions in the step C are as follows: firstly, in the moso bamboo stand, the probability of the diameter order smaller than the average breast diameter is smaller than that of the average breast diameter; secondly, the probability of the radial order of more than or equal to 14cm is less than the probability of the average chest diameter; third, the probability of each radial order is equal to or greater than 0, and the sum of all radial order probabilities is equal to 1.
6. The method for optimizing the structure of the moso bamboo forest stand based on the minimum entropy as claimed in claim 1, wherein: the step II of carrying out overall structure adjustment in a harvesting mode comprises the following steps:
the method comprises the following steps of sequentially felling 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age level each time, and not felling moso bamboos of other age levels;
the method comprises the following steps of (1) harvesting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain diameter grade in sequence each time, and not harvesting moso bamboos of other diameter grades;
the method comprises the following steps of sequentially cutting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age grade and a certain diameter grade every time, and not cutting moso bamboos of other age grades and diameter grades;
sequentially cutting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age level each time, and cutting moso bamboos of other ages after the moso bamboos of the certain age level are cut;
the method comprises the following steps of (1) harvesting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain diameter grade in sequence each time, and harvesting moso bamboos of other diameter grades after the moso bamboos of the certain diameter grade are harvested;
the method comprises the steps of harvesting 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100% of moso bamboos of a certain age grade and a certain diameter grade in turn each time, and harvesting moso bamboos of other ages grades and diameters after the moso bamboos of the age grade and the diameter grade are harvested.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010692804.8A CN111667879B (en) | 2020-07-17 | 2020-07-17 | Minimum entropy-based phyllostachys pubescens stand structure optimization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010692804.8A CN111667879B (en) | 2020-07-17 | 2020-07-17 | Minimum entropy-based phyllostachys pubescens stand structure optimization method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111667879A true CN111667879A (en) | 2020-09-15 |
| CN111667879B CN111667879B (en) | 2023-04-28 |
Family
ID=72392996
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010692804.8A Active CN111667879B (en) | 2020-07-17 | 2020-07-17 | Minimum entropy-based phyllostachys pubescens stand structure optimization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111667879B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113057076A (en) * | 2021-03-25 | 2021-07-02 | 国际竹藤中心 | Method for improving carbon reserve of moso bamboo forest |
| CN114258793A (en) * | 2021-12-29 | 2022-04-01 | 湖南省林业科学院 | Chemical prevention and control evaluation system and method for moso bamboo expansion |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107607053A (en) * | 2017-09-20 | 2018-01-19 | 浙江农林大学 | A kind of standing tree tree breast diameter survey method based on machine vision and three-dimensional reconstruction |
| CN109002621A (en) * | 2018-07-25 | 2018-12-14 | 中国林业科学研究院资源信息研究所 | A kind of mean height and diameter of a cross-section of a tree trunk 1.3 meters above the ground calculation method for taking neighborhood and geographical difference into account |
| CN110874454A (en) * | 2019-11-20 | 2020-03-10 | 浙江农林大学 | Method for accurately measuring and calculating regional scale moso bamboo carbon reserves based on mixed probability density |
-
2020
- 2020-07-17 CN CN202010692804.8A patent/CN111667879B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107607053A (en) * | 2017-09-20 | 2018-01-19 | 浙江农林大学 | A kind of standing tree tree breast diameter survey method based on machine vision and three-dimensional reconstruction |
| CN109002621A (en) * | 2018-07-25 | 2018-12-14 | 中国林业科学研究院资源信息研究所 | A kind of mean height and diameter of a cross-section of a tree trunk 1.3 meters above the ground calculation method for taking neighborhood and geographical difference into account |
| CN110874454A (en) * | 2019-11-20 | 2020-03-10 | 浙江农林大学 | Method for accurately measuring and calculating regional scale moso bamboo carbon reserves based on mixed probability density |
Non-Patent Citations (2)
| Title |
|---|
| 刘恩斌;施拥军;李永夫;周国模;杨东;: "浙江毛竹林分非空间结构特征及其动态变化" * |
| 曾春;肖福平;余林;曾庆南;: "江西瑞金毛竹林林分直径分布研究" * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113057076A (en) * | 2021-03-25 | 2021-07-02 | 国际竹藤中心 | Method for improving carbon reserve of moso bamboo forest |
| CN114258793A (en) * | 2021-12-29 | 2022-04-01 | 湖南省林业科学院 | Chemical prevention and control evaluation system and method for moso bamboo expansion |
| CN114258793B (en) * | 2021-12-29 | 2022-10-28 | 湖南省林业科学院 | Chemical prevention and control evaluation system and method for moso bamboo expansion |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111667879B (en) | 2023-04-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103218669A (en) | Intelligent live fish cultivation water quality comprehensive forecasting method | |
| CN111667879A (en) | Moso bamboo forest stand structure optimization method based on minimum entropy | |
| CN102708254A (en) | Method for analyzing intercept ability of canopy on photosynthetic active radiation based on virtual plant | |
| CN108090693A (en) | The structure of the Optimum Regulation model of the photosynthetic desired value of facility of fusion efficiencies constraint and application | |
| CN106096305B (en) | The maximum intermediate cutting optimum design method of the total growth of standing forest after forest thinning | |
| Ozdemir et al. | Biomass estimation of individual trees for coppice-originated oak forests | |
| Zhao et al. | Effects of increased nitrogen deposition and rotation length on long-term productivity of Cunninghamia lanceolata plantation in southern China | |
| Cao et al. | Bamboo in subtropical China: efficiency of solar conversion into biomass and CO 2 sequestration | |
| Mithra et al. | Computer simulation of cassava growth: a tool for realizing the potential yield | |
| CN113057076A (en) | Method for improving carbon reserve of moso bamboo forest | |
| CN105354625A (en) | Method for realizing optimal forest selective cutting model | |
| Lee et al. | Geostatistical analysis of regional differences in stem taper form of Pinus densiflora in central Korea | |
| CN105184069B (en) | A kind of Pinus tabulaeformis forest dynamic density regulation and control method and system based on interception capacity | |
| CN111563824B (en) | Artificial forest land research system and method based on Chinese pine | |
| Metslaid et al. | Recovery of advance regeneration after disturbances: acclimation of needle characteristics in Picea abies | |
| CN101889508A (en) | Barbadosnut low platform type tree-form cutting cultivating technology | |
| Liu et al. | Productivity and efficiency change in China’s grain production during the new farm subsidies years: Evidence from the rice production | |
| Zhang et al. | The construction of winter wheat smart water saving irrigation system based on big data and internet of things | |
| Nonhebel | Energy use efficiency in biomass production systems | |
| Fischer et al. | Climate, land, energy & water strategies: a case study of Mauritius | |
| Sun et al. | Effects of light on tree growth | |
| Fan | Modeling oil palm monoculture and its associated impacts on land-atmosphere carbon, water and energy fluxes in Indonesia | |
| Akmalluddin et al. | Potential Biomass Production Estimation of Wood Energy Species in Post Mining Reclamation Area Using CO2FIX Model | |
| Ding | Effect of spacing management on growth and commercial logging of red pine | |
| Mayati et al. | Growth rates of tissue culture Hevea brasiliensis (rubber) trees. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |