302 results about "Woodlot" patented technology

The invention provides a forest land tree height measurement and determination method and system based on laser radar point cloud data. Stress wave signals are collected based on a trunk base acoustic emission sensor array to generate an acoustic characteristic parameter set, the digital twin model is driven to complete forest stand structure topological optimization, and a three-dimensional growth vector model reflecting the internal mechanical state of a trunk is formed. And synchronously fusing high-precision slope point cloud data returned by the unmanned aerial vehicle laser radar in real time, correcting a terrain distortion error through a dynamic splicing algorithm in combination with stress distribution characteristics, and generating a crown segmentation boundary constrained by physical characteristics. And finally outputting a tree height parameter corrected by the abrupt slope topography through model iterative optimization and space vector analysis. According to the technical scheme, synchronous sensing of the three-dimensional shape and the mechanical state of the tree in the complex terrain environment is achieved, and the tree height measurement error is reduced.

The invention discloses a forest land ecosystem health assessment system, and belongs to the technical field of environmental protection. Comprising the following modules: an intelligent sensing module for realizing omnibearing and high-resolution monitoring of the forest land ecological environment; the feature extraction module automatically extracts, standardizes and dynamically corrects the multi-dimensional features of the ecological system, and constructs a unified ecological index mapping model; the coupling analysis module is used for accurately identifying structural evolution characteristics and key conversion nodes of the ecological system; the health assessment module is used for constructing a dynamic self-adaptive ecological health assessment model, assessing the overall health state of the system and simulating the vulnerability and potential risk of the ecological system under different climate change scenes; the decision and visualization module is used for realizing efficient intelligent interaction and multi-scene decision analysis of ecological big data; and the restoration and regulation and control module intelligently generates a restoration path and an intervention strategy based on ecological risk assessment so as to improve the restoration capability and toughness of the ecological system.

The invention relates to the technical field of remote sensing, and discloses a forest land health state analysis method and system based on multi-source remote sensing image analysis. The system comprises a multi-source remote sensing acquisition module, a feature extraction and fusion module, a health assessment module, a traceability analysis module, a strategy matching module, a visual reconstruction module, an early warning decision module and an execution feedback module, and constructs a multi-modal forest land observation data set by fusing multi-source remote sensing data of multispectrum, hyperspectrum, radar and thermal infrared. The comprehensive extraction of multi-dimensional information such as vegetation coverage, canopy biochemical characteristics, under-forest structures and surface thermal environments is realized, the limitation of single data source analysis is overcome, and the comprehensiveness and accuracy of forest land health condition evaluation are improved; through dynamic comparison of multi-stage remote sensing images and health risk level mapping, early identification and early warning of forest growth abnormity, degeneration trend and pest and disease risk are realized.

The invention provides an annotation method and system based on forest land remote sensing data. The method comprises the following steps: acquiring multi-source remote sensing data of a forest land; processing the multi-source remote sensing data; an improved Mask R-CNN network is adopted to extract optical image features, the weight of a near-infrared band is enhanced through a compression and excitation SE module, and feature fusion is carried out to obtain a multi-modal enhanced feature map; carrying out feature extraction by adopting a 3D convolutional network to obtain a multi-level three-dimensional space feature map; inputting the processed data into a Transform model to obtain a forest growth curve graph; performing initial labeling based on the feature map and the curve map to obtain an initial labeling result; performing morphological filtering on the initial labeling result to remove small-area noise, and optimizing a labeling boundary in combination with a superpixel segmentation algorithm to obtain an optimized labeling result; and generating a vector annotation file according to the optimized annotation result. Multi-dimensional information complementation of spectral features, three-dimensional structure features and time sequence dynamic features is achieved, and data availability and reliability are remarkably improved.

The invention discloses a large-scale forest land carbon reserve estimation method and system based on an active and passive remote sensing technology. The method comprises the following steps: acquiring satellite-borne laser radar data of different sensors in a research area, SAR data of an L wave band and a C wave band, multispectral remote sensing image data, airborne laser radar data, topographic data and land coverage category data containing forest land; discontinuous combined spaceborne laser radar canopy height products are obtained by using spaceborne laser radar data of different sensors; improving a geographic weighted regression model to estimate the canopy height of a continuous scale; extracting polarization parameters by using C-band SAR data, extracting vegetation indexes and texture indexes by using multispectral remote sensing image data, constructing characteristic variables together with topographic data, and screening the characteristic variables based on a variance reduction criterion; and constructing an overground carbon reserve inversion model, and carrying out large-scale forest land carbon reserve estimation. According to the method, the forest land carbon reserve estimation precision of the large-scale regional broken plot is improved.

The present invention discloses a method for detecting forest disturbances based on a full-polarization SAR image, which includes obtaining a full-polarization SAR image within a target area, performing image classification for the reference time phase and the monitoring time phase, performing pre-processing including introduction of the SAR image, polarization matrix transformation of the SAR image, Refined Lee filtering, and false-color synthesis on the classified full-polarization SAR image to obtain a false-color synthesized SAR image, inputting the false-color synthesized SAR image into an optimized surface change detection model to extract surface change patches, combining with a radar vegetation index RVI image to obtain initial forest disturbance patches, performing an overlay check on the initial forest disturbance patches to obtain forest disturbance patches within the target area, and generating a visualization result. It has efficient, accurate, and reliable detection capabilities, can observe the ground all day long, all-weather, and penetrate clouds and fog, can be widely applied in fields such as forest resource monitoring and environmental protection, and can better serve ecological protection restoration supervision and management.

The invention discloses a forest land ecosystem carbon reserve accounting method and system, and the method comprises the steps: obtaining and screening feature variables, such as optical remote sensing data, vegetation indexes, texture factors, satellite-borne laser radar feature parameters, so as to determine features having the most influence on a target variable, and removing redundant and irrelevant variables; the method comprises the following steps of: screening characteristic variables, reserving variables which contribute to the model prediction effect, improving the precision and stability of the model, constructing a canopy height inversion model by adopting a random forest method based on the screened characteristic variables, realizing accurate estimation of the canopy height, and finally calculating the biomass of vegetation of the forest ecological system by using a different-speed growth equation. And finally, summarizing the biomass of the vegetation of the forest ecological system to obtain the total biomass of the vegetation, and multiplying the total biomass of the vegetation by the carbon-containing coefficient to obtain the vegetation carbon reserve of the forest ecological system, so that wide-area and efficient forest parameter monitoring is realized, the monitoring cost is reduced, the environmental adaptability is improved, and the problems of data continuity and standardization are solved.

The invention discloses a sparse forest land single tree segmentation method and system based on NDVI weighted attention, and the method comprises the steps: making a data set containing an image-label-NDVI image array of a sparse forest land single tree, and dividing the data set into a training set, a test set and a verification set; constructing a sparse forest land individual tree segmentation network model based on NDVI weighted attention; performing training, hyper-parameter adjustment and generalization ability evaluation on the constructed sparse forest land single tree segmentation network model by using the training set, the verification set and the test set; and performing individual tree segmentation by using the trained sparse forest land individual tree segmentation network model. According to the method, small target recognition, accurate edge and lightweight inference in the sparse forest land scene are realized, and a new technical path is provided for single-tree-level monitoring in a complex earth surface environment.

The embodiment of the invention provides a tree species identification method, device and equipment based on a dense time sequence image, and the method comprises the steps: obtaining a dense long time sequence multispectral remote sensing image and topographic data of a research area; carrying out image wave band fusion according to the dense long-time-sequence multispectral remote sensing image to construct 12 vegetation spectral indexes; performing land utilization classification on ground features in the dense long-time-sequence multispectral remote sensing image of the research area by utilizing a linear spectrum hybrid model in combination with topographic data, dividing the ground features into buildings, water bodies, other ground features and a forest land data set, and performing pre-classification based on the extracted forest land data set; dividing the forest land data set into an evergreen forest and a deciduous forest by combining an RVI threshold method with a linear spectrum hybrid model; according to the forest land data set, Savitzaky-Golay filtering transformation and spectral differential transformation are carried out, and an NDVI transformation image set is obtained; and performing combination according to the vegetation spectral index NDVI transformation image set as classification features, and discussing the classification effect of the tree species in the research area through a random forest model.

The invention discloses a forest stand tree species identification method and system based on multi-source remote sensing data fusion, and the method comprises the following steps: obtaining data which comprises forest land remote sensing image data and ground data; carrying out preprocessing on the obtained data; a dual-path CBAM-UNet network model is constructed; inputting the preprocessed data into the double-path CBAM-UNet network model to carry out tree species classification prediction and obtain a tree species classification chart; performing image splicing on the tree species classification map to obtain a tree species classification grid map; the system comprises a data acquisition module, a data preprocessing module, a prediction module and an image processing module. According to the forest stand tree species identification method and system based on multi-source remote sensing data fusion provided by the invention, multi-scale feature capture and feature fusion of multi-source heterogeneous data can be realized through the constructed dual-path CBAM-UNet network model, high-precision identification can be performed on forest stand tree species under complex links, and high-quality data can be provided for forest management.

The invention relates to the technical field of forest fertilization, in particular to a forest precise fertilization decision-making method and system based on soil nutrient profit and loss, and the method comprises the steps: obtaining basic information of a target forest land, and dividing forest growth stages based on the basic information; the method comprises the following steps: collecting an undisturbed soil sample and a mixed soil sample of a 0-40cm soil layer of a target forest land by adopting an S-shaped point distribution method, separating the mixed soil sample, and respectively measuring the soil nutrient content, the bioavailability, the soil enzyme activity and the microbial functional gene. According to the method, by measuring the dimension indexes, constructing a five-dimensional profit and loss evaluation index system for determining the reference value and dynamically adjusting the weight according to the forest land data, calculating the comprehensive profit and loss index, judging the nutrient state and generating the personalized fertilization scheme, the defects that an existing fertilization scheme is single in basis index and lacks an effective dynamic adjustment link are effectively overcome; the requirements of multi-generation continuous planting forest land are met, and the environmental risks such as fertilizer waste, soil acidification and water eutrophication are effectively reduced.

The invention relates to the technical field of resource accounting, and discloses a dynamic index accounting system for displacement of cultivated land resources and forest land resources. The system comprises a resource data acquisition unit for acquiring spatial distribution data of cultivated land resources, types and coverage data of forest land resources and replacement constraint condition data and performing space-time alignment to generate a resource multi-dimensional data set; the replacement index accounting unit is used for executing resource adaptability reconstruction processing based on the resource multi-dimensional data set and separating target resource data from abnormal resource data; the replacement scheme generation unit is used for generating an accounting result containing a replacement area, a weight and a priority by combining a preset replacement rate and a development rate; and the dynamic correction unit is used for identifying an exception type based on the exception resource data and correcting an accounting result in real time. The system can comprehensively capture resource dynamics, improves the accuracy and timeliness of replacement accounting, and adapts to complex resource management requirements.

The invention relates to the technical field of land data processing, in particular to a land data updating and analyzing method based on spatial-temporal dynamic change, which comprises the following steps: S1, data collection and arrangement; s2, space-time dynamic evolution analysis based on a GIS model; s3, performing data analysis based on a Python script tool; s4, land data updating; according to the method, the dynamic evolution of land utilization in the time sequence in 2009-2024 is accurately presented, meanwhile, the spatial distribution change is carefully presented, through the combination of the GIS model and a Python script tool, the spatial and temporal change rule of various land features such as cultivated land, garden land, forest land and construction land is accurately revealed, a reliable basis is provided for scientific planning, and the method is suitable for popularization and application. The invention provides an LSTM-CNN fusion model based on deep learning for solving the problem that the abandoned farmland monitoring precision is insufficient, and the abandoned farmland recognition accuracy reaches 94.7% through transfer learning optimization parameters.

A device and method for introducing new vegetation into a forest floor includes seeds, seedlings, and / or saplings carried within a plurality of tapered shells having polygonal cross sections, possibly mixed with soil, sand, gravel, fertilizer, SAP granules, and / or water. The tapered shells are inserted into the ground through the hydrophobic layer by dropping or propelling them from an aircraft, or manually pressing on them. One or more holes proximate the bottoms of the tapered shells enable rain water and germinating roots to penetrate into soil beneath the hydrophobic layer. A perforated lid can prevent the seeds or seedlings from being ejected upon impact with the forest floor. A weighted tip can improve penetration of the tapered shells into the forest floor. A plurality of tapered shells can extend downward from a tray or frame. The tapered shell and / or perforated lid can be made from biodegradable materials.

The invention discloses a forest land restoration and carbon sink management system and method based on a three-dimensional cadastral model, and the method comprises the steps: integrating an earth surface forest right, an underground space right and a block chain information management right through the three-dimensional cadastral model, and collecting forest biomass and soil carbon library data in real time in combination with an Internet of Things sensor network; and data storage and carbon point transaction are realized based on a block chain multi-chain architecture. According to the scheme, the problems of unclear ownership and low data credibility in traditional forest land restoration are solved, the carbon sink value is converted into economic benefits, and the method is suitable for low-efficiency forest land ecological restoration and carbon asset management.

The invention discloses a forest land litter water-holding capacity automatic observation method, which comprises the following steps: identifying topographic factor distribution of different slope gradients and altitudes, calculating vegetation structure parameters by combining vegetation indexes, dividing forest land environment heterogeneity regions according to the topographic factor distribution and the vegetation structure parameters, and generating a spatial distribution map layer, generating an observation point position layout scheme with regional representativeness, deploying a sensing device according to the observation point position layout scheme, and obtaining the dynamic change moment and the change amplitude of the litter water-holding capacity; and decomposing the dynamic change moment and the change amplitude of the litter water-holding capacity, generating continuous spatial distribution data of the forest land litter water-holding capacity, constructing a water-holding capacity prediction model, and calculating litter water-holding capacity observation values of different areas of the forest land in real time according to parameter coefficients of the prediction model. According to the invention, accurate observation of the water holding characteristic of the litter in the forest land is realized.

The invention belongs to the technical field of crop planting, and provides a mushroom crop efficient planting method, which comprises the following steps: 1, land planning: selecting a soil position with sufficient shading and sufficient water supply, and preferably selecting a fruit forest land, a commodity forest land, a nut forest land and an arbor tea tree land; step 2, land preparation: selecting a target open space with the width of 0.8-1.2 m along the wind direction by utilizing the line spacing of fruit trees; carrying out soil preparation, chemical disinfection and physical disinfection on the soil; the problem that bacteria and microorganisms in soil affect the mushroom sticks is avoided, meanwhile, when the mushroom sticks are cultivated and planted, the soil at the planting position of the mushroom sticks is subjected to multiple times of sterilization treatment, the mushroom sticks are covered with protective films for protection, in addition, the soil outside the mushroom sticks is subjected to biological disinfection treatment, and therefore the mushroom sticks are protected. Therefore, the influence of other organisms in the soil on the cultivation and growth of the mushroom sticks is avoided, and the purpose of excellent cultivation and growth of the mushroom sticks is achieved.

The invention discloses an under-forest ecological efficient cultivation method for abrus cantoniensis hance, and belongs to the technical field of abrus cantoniensis hance planting. By interplanting the abrus cantoniensis hance under the arbor forest, the optimal interplanting mode of interplanting the abrus cantoniensis hance under the Chinese fir forest is found, and the mode can improve the utilization efficiency of the forest land, reduce the planting cost and increase the economic benefit; the harm of weeds and diseases and pests is reduced, the use of weeding labor and pesticides is reduced, water and soil loss is reduced, water and soil are kept, and good ecological benefits are achieved. According to the method, a scientific basis is provided for selection of a cultivation mode for interplanting the abrus cantoniensis hance under the forest. In ecological management, if the yield and the nutrient content of the abrus cantoniensis hance are improved as a target, a cedarwood forest stand is preferentially selected for interplanting.

The invention discloses an under-forest cultivation method of a clitocybe maxima Shenshi No.2 strain, and belongs to the technical field of edible mushroom cultivation. The method comprises the steps that a forest land with the canopy density of 60%-75% is selected, and when the air temperature is stabilized at 23 DEG C or above in summer, bag-removed Shenmushroom No.2 fungus bags are placed in a furrow bed at the interval of 8-15 cm and covered with soil; a simple arched shed covered with a plastic film and a sunshade net is built above the furrow bed, and ventilation and humidity are regulated and controlled by opening and closing the two ends of the simple arched shed. According to the method, through two core measures of interval placement and arched shed regulation and control, the problems that fungus bags are prone to fungus burning and rainstorm scouring in the high-temperature period under the forest in summer are systematically solved, efficient and stable production of the high-temperature-resistant variety Shenmushroom No.2 under the forest in summer is achieved, and the blank of under-forest cultivation in the high-temperature season is effectively filled up.

The invention belongs to the technical field of forestry ecological restoration, and discloses a method for transforming a pinus massoniana low-quality and low-efficiency water source forest into a coniferous and broad-leaved mixed forest, which comprises the following steps: (1) forest stand diagnosis and planning; (2) three-dimensional complementary planting; and (3) innovation of a mixed mode. The biological characteristics of different fireproof tree species are utilized, upper, middle and lower mixed spaces are matched, shade-tolerant and sun-loving tree species are matched, and the mutual promotion effect is achieved. The characteristics of various tree species are effectively utilized, matching of deep and shallow root system tree species is fully considered, the improvement of the water and soil conservation function of forest land soil is effectively ensured, and the water and soil conservation function of a water source forest region is particularly promoted.

The invention relates to the technical field of ecological construction engineering. The invention provides a forest small watershed-based under-forest adaptive planting method for different sites in a mountainous area in the eastern Liaoning province. The method comprises the following steps: (1) carrying out site division on the small watershed of the forest in the mountainous area in the eastern Liaoning province according to landforms, slope positions and slope directions; (2) collecting data and determining an optimization scheme by taking a soil condition as a guiding index; (3) collecting data and determining an optimization scheme by taking the canopy density as a guiding index; and (4) based on the optimization schemes in the step (2) and the step (3), selecting a site suitable for forest fruits, forest fungi, forest vegetables and forest medicines, and carrying out under-forest adaptive planting. By means of the technical scheme, forest land resources in mountainous areas in the eastern Liaoning province can be fully utilized, economic plants or fungi can be planted under different site forests in small watersheds of forests according to local conditions, and the economic benefits of under-forest planting are brought into play to a greater extent; under-forest adaptive planting improves the functions of forest soil conservation, water conservation, biological diversity and the like, and ecological benefits are improved.

The invention discloses a forest land soil data management method and system based on unmanned aerial vehicle multispectral inversion, and particularly relates to the technical field of soil ecology, and the method comprises the steps: S1, management region determination: determining target forest land soil data as a target management region, and then dividing the target management region into sub-regions according to an equal-time division mode, the sub-regions in the target management region are sequentially numbered as 1, 2,..., i,..., n according to equal time; s2, unmanned aerial vehicle image data acquisition, which is used for acquiring unmanned aerial vehicle image data of a target management area; the system not only comprises soil physical and chemical indexes, but also covers unmanned aerial vehicle image data so as to obtain spectrum related data, inversion is carried out after multi-source data fusion, the soil ecological function is comprehensively described, and a more comprehensive management result is provided.

Provided in the present invention is an artificial-afforestation area extraction method based on a high-resolution remote-sensing image. The method comprises: acquiring a remote-sensing image, and preprocessing the remote-sensing image; inputting the preprocessed remote-sensing image into an intelligent forest extraction model, so as to obtain a distribution map for all forests; performing edge detection and Hough transform line detection on the distribution map for all the forests, so as to obtain artificial afforestation regions and natural forest regions; and calculating the areas of the artificial afforestation regions and the areas of the natural forest regions, so as to obtain statistical results for artificial afforestation and natural forests. The present invention can solve the shortcomings of conventional monitoring means in terms of efficiency, cost and accuracy, and provides technical supports for large-scale forestry investigation and ecological monitoring.

The invention discloses a multi-task forest land identification method based on a high-resolution remote sensing image, and the method comprises the steps: S1, obtaining forest land remote sensing data, and determining an autonomous input channel; s2, reading sample training data and sample test data in an original data source through a user autonomous input channel, interpreting TFReccord data from the sample training data and the sample test data through data decoding, and extracting remote sensing image data and label data contained in each sample data; s3, performing screening and data enhancement on the remote sensing image data and the label data; s4, based on a double-branch multi-task segmentation identification deep learning model, carrying out forest land and non-forest land identification on the preprocessed remote sensing image data in a large range; and step S5, visual output of an identification result is carried out. The problems that in the prior art, forest land recognition precision is not high, adaptability to forest land fragmented areas is poor, and effective utilization of time sequence change information is lacked are solved.

The invention discloses a tree positioning calculation method based on unmanned aerial vehicle remote sensing, and relates to the technical field of agriculture and forestry vegetation positioning. According to the method, firstly, a digital orthoimage and a digital earth surface model (DSM) are generated through aerial photography of an unmanned aerial vehicle, a crown mask is obtained by using an instance segmentation technology, and a trunk position is accurately positioned by calculating a fusion score in the mask by using a joint resolving mechanism of a DSM local peak domain and an iterative corrosion morphological core. The method improves the positioning precision and efficiency through a DSM highest point * iterative corrosion combined optimization strategy, and improves the positioning stability of dense crowns through the corrosion depth constraint space position. According to the method, the positioning precision and efficiency of a complex forest environment are remarkably improved, and the problems of insufficient positioning precision, difficulty in positioning trunks under dense crowns and the like in the existing unmanned aerial vehicle remote sensing technology are solved.

The invention discloses a camellia oleifera forest water and soil conservation method suitable for a hilly land, which comprises the following steps: carrying out partitioned soil preparation on the hilly land forest land, and arranging an intermittent ladder belt and an undisturbed soil belt in a slope cultivation area along a contour line; constructing a soil stabilizing structure and a water seepage buffer layer on the upstream side of the ladder belt to reduce corrosion and promote seepage; water collection slow-release ditches are arranged on the inner sides of the ladder belts for retaining and storing runoff; arranging a soil and water retention composite layer in the camellia oleifera planting pit; a desilting basin is arranged in the slope toe water collecting area to recover runoff; according to the method, the hilly land forest land is subjected to partitioned soil preparation, and the intermittent ladder belts and the undisturbed soil belts are arranged in the slope surface cultivation areas along the contour lines, so that slope surface runoff scouring can be weakened; a soil stabilizing structure, a water seepage buffer layer and a water collection slow release ditch are combined, so that runoff corrosion reduction and water retention are realized; the soil and water retention composite layers in the camellia oleifera planting pits are matched, so that the stability and the water retention capacity of the root zone can be enhanced, water and soil loss is effectively controlled under the condition that large-scale hard engineering is not needed, and the water utilization efficiency is improved.

The application discloses a kind of forest mountainous area track transport equipment, it is related to track transport technical field, including MCU, transport track, tractor, several loading vehicles and two loading and unloading structures, tractor and several loading vehicles are set on transport track, tractor is used to provide power, tractor is hinged with loading vehicle, adjacent loading vehicle is hinged, two loading and unloading structures are respectively set in the first end of transport track and the end of transport track to realize the loading and unloading of goods, loading vehicle includes loading vehicle compartment, load board and pressure sensor, load board is used to bear goods, pressure sensor is located on load board, adjusting structure is arranged between loading vehicle compartment and load board, pressure sensor transmits the pressure value detected to MCU, and MCU controls adjusting structure to make load board keep level.The application realizes the integrity of goods loading and unloading transport, improves bearing capacity, can adjust the gravity center of goods, guarantees the stability of transport.

The invention relates to the technical field of monitoring, in particular to a hydroelectric power plant surrounding ecological environment monitoring system and method.The hydroelectric power plant surrounding ecological environment monitoring system comprises a water area monitoring module, a land area monitoring module, a remote communication module, a remote server, a data processing module and an early warning module; the method comprises the following steps: selecting a plurality of proper point locations in regions such as a reservoir, a downstream river channel and a diversion canal to arrange water area monitoring modules, and collecting water quality hydrological data and underwater biological activity data; selecting a plurality of appropriate point locations in the reservoir bank hydro-fluctuation belt, the side slope and the surrounding forest land to arrange land area monitoring modules, and collecting soil, vegetation and land biological activity data; the collected data are uploaded to a remote server for storage in real time through the remote communication module; the data processing module analyzes and processes the data, and immediately controls the early warning module to give an early warning to a worker after an abnormality is found; therefore, all-weather automatic monitoring and early warning can be carried out on the surrounding ecological environment of the hydroelectric power station.

The application discloses a forest disturbance detection method and device, electronic equipment, storage medium and product, relates to the technical field of land scene detection, and discloses a forest disturbance detection method, which comprises the following steps: inputting an optical image of a target forest area into an optical feature extraction branch of a preset disturbance detection model to obtain optical features, wherein the optical features comprise spatial texture features and spectral features; inputting a radar image of the target forest area into a radar feature extraction branch of the disturbance detection model to obtain radar features, wherein the radar features comprise scattering features and terrain features; performing cross-modal feature fusion on the optical features and the radar features to obtain fusion features; and performing classification and identification based on the fusion features to determine the disturbance state of the target forest area. The application can optimize the forest disturbance change detection effect.

The invention discloses an ecological real estate mode and an application method, and belongs to the technical field of ecological funeral and interment and comprehensive utilization of land resources. Aiming at the problems of land resource waste, ecological destruction, insufficient culture inheritance and the like of a traditional funeral and interment mode, the invention provides an ecological real estate mode integrating cemetery and woodland, which comprises the following core contents: (1) renovating barren mountains, shrubs and the like into special forests taking commemoration as a theme through ecological restoration; dividing a commemorative area, an ecological restoration area and a public green land; (2) a three-dimensional cadastral model is created for the first time, the earth surface forest right, the underground burial right and the spatial information right are defined, and earth ownership sharing is achieved; (3) introducing a digital technology, binding an entity tree and virtual information through a digital tombstone and an Internet of Things system, and supporting RFID / two-dimensional code label tracking, block chain evidence storage and carbon sink real-time metering; (4) in combination with a carbon sink transaction mechanism, forest land carbon sink benefits are converted into economic benefits, and green transformation of the funeral and interment industry is promoted; and (5) providing a personalized service module which comprises a tree seed selection platform, a funeral self-service platform and an intelligent management platform so as to meet diversified requirements. According to the mode, through the three-in-one design of ecological restoration, culture inheritance and economic sustainability, the land saving rate is 1: 10, collaborative development of biodiversity protection and rural economy is promoted, and a full-chain solution is provided for ecological funeral and interment.