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WO2003069315A1 - Procede d'evaluation de la biomasse des forets et des arbres a l'aide de donnees a resolution elevee detectees a distance - Google Patents

Procede d'evaluation de la biomasse des forets et des arbres a l'aide de donnees a resolution elevee detectees a distance Download PDF

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Publication number
WO2003069315A1
WO2003069315A1 PCT/JP2003/001460 JP0301460W WO03069315A1 WO 2003069315 A1 WO2003069315 A1 WO 2003069315A1 JP 0301460 W JP0301460 W JP 0301460W WO 03069315 A1 WO03069315 A1 WO 03069315A1
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WO
WIPO (PCT)
Prior art keywords
biomass
trees
tree
crown
forests
Prior art date
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Ceased
Application number
PCT/JP2003/001460
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English (en)
Japanese (ja)
Inventor
Jiro Suekuni
Makoto Nogami
Katsushi Hatayama
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Kansai Electric Power Co Inc
Kansai Environmental Engineering Center Co Ltd
Original Assignee
Kansai Electric Power Co Inc
Kansai Environmental Engineering Center Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Kansai Electric Power Co Inc, Kansai Environmental Engineering Center Co Ltd filed Critical Kansai Electric Power Co Inc
Priority to AU2003211938A priority Critical patent/AU2003211938B2/en
Priority to JP2003568386A priority patent/JP4219819B2/ja
Publication of WO2003069315A1 publication Critical patent/WO2003069315A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/188—Vegetation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

Definitions

  • Biomass estimation method for forests and trees by remote sensing high-resolution data technology Field of the Invention
  • the present invention relates to a method for estimating biomass of forests and trees by remote sensing high-resolution data processing.
  • Background Technology Various adverse effects due to global warming are regarded as problems on a global scale. On the other hand, it is said that the assimilation of carbon dioxide by forests and trees also has the effect of preventing global warming.
  • biomass is estimated from forests' trees, but the biomass in forests.trees depends on the type of forest and trees, canopy size (area, major axis, minor axis) and their spectral characteristics.
  • problems to be Solved by the Invention Therefore, remote sensing using satellite photographs and aerial photographs has been implemented to measure the species of forests and trees, the crown size (area, major axis, minor axis) and spectral characteristics. I have.
  • Fig. 7 (a) in general, trees grow from the seedling stage, like saplings, young trees, and mature trees, and as shown in Fig. 7 (b).
  • P is a pixel
  • J is a canopy
  • E soil and other parts other than the canopy. Therefore, in forests and trees where the canopy is closed, as shown in C and D in Fig. 7 (c), the conventional remote sensing method can be used, as shown in Fig. 7 (c).
  • the crown J is small and not closed, so the soil and other non-canopy parts E existing between crown J and crown J, that is, It is difficult to distinguish from the ground, roads, trees of other species, vegetation, etc., and trees of tree types other than the planted specific trees, and the ground, roads, vegetation, etc., become noise. Canopy size (area, major axis, minor axis) and its spectral properties could not be measured. In addition, depending on the species, even for mature trees, the crown is not blocked. For example, in the case of planting eucalyptus trees in Australia, the canopy often does not close even when the tree matures.
  • the forest-tree biomass estimation method according to claim 1 of the present invention by remote sensing high-resolution data processing includes: The method is characterized in that the biomass of a specific tree is estimated from the size and spectral characteristics of the crown occupying the predetermined area by taking an image and masking a portion other than the crown portion of the specific tree within the predetermined area based on the photograph. .
  • the term “high-resolution data” is obtained by analyzing high-resolution photos by high-resolution satellites or by analyzing ultra-high-resolution photos by airplanes or wireless Helicopters. Data.
  • the term “canopy size” includes the area, major axis, and minor axis of the canopy part, and is hereinafter referred to as canopy size (area, major axis, minor axis). However, it is not always necessary to include all of the area, the major axis and the minor axis, and only the area may be included. By measuring the major axis and the minor axis, it is possible to estimate the biomass with higher accuracy.
  • the above-mentioned “masking other than the crown portion of the specific tree within the predetermined area” means that the portion other than the specific tree planted within the predetermined area (in the image in the photograph), that is, This refers to erasing trees, ground and roads, vegetation and agricultural products, etc., other than the specified tree species as image data, and cutting out the crown of the specified tree species along the edge of the crown on a photo taken on a computer. The other part says to erase the data on your computer.
  • the work of erasing the part other than the canopy part at the time of the combi-up is to cut out the crown of a specific tree species in the picture image on the monitor while looking at the photograph actually taken by the worker, and erase the other parts
  • the spectral characteristics or the like corresponding to a specific tree species may be grasped in advance, and the other spectral characteristics may be automatically deleted by the combination process.
  • the masking operation requires a relatively long time, but since it is possible to cut out the tree while checking the specific tree species in the actually photographed image, there is an advantage that the crown of the specific tree species can be cut out with high accuracy.
  • the biomass estimation method for forests and trees as described above, if the canopy is not obstructed, that is, within a specific area in the field, in other words, in the image on the photo,
  • the canopy size (area, long diameter, short diameter) of trees of a specific species even if there are different types of trees other than the specific species, as well as the ground, roads, vegetation and crops Diameter can be measured with high accuracy, and together with the measurement of the spectral characteristics of the canopy, the biomass of a particular tree species can be estimated with high accuracy.
  • the manager will decide whether the canopy size should be set annually according to the age of the plantation, or every specified age. (Area, major axis, minor axis) and / or changes in the spectral characteristics of the canopy, estimating the extent of biomass increase and annual biomass accumulation in the area, and reporting the results to investors. Can be. Investors can use the reported data to check the effects of planting their own trees on global warming, as well as forecasting the timing of logging and the expected selling price of timber at the time of logging.
  • the forest-tree biomass estimation method according to claim 2 of the present invention by remote sensing high-resolution data is characterized in that the photograph is a photograph taken in a specific wavelength band.
  • a photograph that emphasizes trees of a tree type that matches or approximates the spectral characteristics based on the spectral characteristics of a specific tree species This makes it possible to blur or easily mask other spectral characteristics, leaving only the crown of a specific tree species, which not only improves masking accuracy but also speeds up masking work. It can be implemented at low cost.
  • the forest-tree biomass estimation method using remote sensing high-resolution data according to claim 3 of the present invention is characterized in that the photograph includes a plurality of tree crowns in one pixel. .
  • the forest-tree biomass estimation method according to the remote sensing high-resolution data set forth in claim 4 of the present invention, wherein the photograph is an ultra-high-resolution photograph, and one canopy extends over a plurality of pixels. It is characterized by the following.
  • FIG. 1 is a schematic flow chart in a method for estimating biomass of a forest / tree using remote sensing high-resolution data according to an embodiment of the present invention.
  • FIG. 2 is a schematic explanatory diagram of each step in the forest / tree biomass estimation method using remote sensing high-resolution data according to the embodiment of the present invention.
  • Figures 3 (a) to 3 (c) illustrate the relationship between the crown and the pixel size.
  • Figure 3 (a) shows the pixel crown diagram when the crown ratio is 100%.
  • FIG. 3 (c) is a pixel crown diagram by a high-resolution photograph when the crown ratio is less than 100%.
  • Figures 4 (a) to 4 (d) show the relationship between various tree factors and biomass based on the local ground-based tree survey.
  • Figure 4 (a) shows the relationship between tree height and biomass.
  • Figure 4 (b) is a characteristic diagram showing the relationship between canopy thickness and biomass
  • Figure 4 (c) is a characteristic diagram showing the relationship between average crown ratio and biomass
  • Figure 4 (d) is the canopy area and biomass.
  • FIG. 4 is a characteristic diagram showing a relationship between
  • Figures 5 (a) to 5 (d) show the relationship between various tree factors and biomass based on the aerial image of the site.
  • Figure 5 (b) is a characteristic diagram showing the relationship between canopy area and biomass
  • Figure 5 (c) is a distribution diagram of the difference between the biomass estimation result using the average canopy diameter and the measured value from the field survey
  • 5 (d) is the distribution map of the difference between the biomass estimation result using the canopy area and the actual measurement value from the field survey.
  • FIG. 6 is a correlation estimation characteristic diagram of the evaluation index IR * G / R and biomass.
  • FIG. 7 (a) to 7 (c) show the growth stages of trees after planting
  • Figure 7 (a) is a side view of trees showing the growth stages of trees after planting
  • Figure 7 (b) is Tree crown diagram at the growth stage of trees after planting
  • Fig. 7 (c) is a pixel crown diagram showing the change in crown ratio with the growth stage of trees after planting.
  • FIG. 1 is an overall schematic flowchart according to a forest / tree biomass estimation method 10 according to the present invention.
  • Fig. 1 photographs of the forests and trees are taken from a high place using a Landsat satellite or a high-resolution satellite (IKONOS), or an aerial vehicle or a radio helicopter. It can take pictures with a resolution of 30 m on each side, and a high-resolution satellite (IKONOS) can take high-resolution pictures with a side of about 4 m. In the case of one, it is possible to take an ultra-high resolution photograph with a side of several cn!
  • IKONOS high-resolution satellite
  • the canopy size (area, major axis, minor axis) of a particular tree species obtained by masking is measured (14). In measuring the canopy size, only the area of the canopy may be measured, but by measuring the major and minor diameters of the canopy, more accurate analysis can be performed.
  • the spectral characteristics of the canopy of the specific tree species cut out as described above are measured (15). The measurement of the spectral characteristics is performed, for example, for each of R, G, B, and IR.
  • NVDI Normalized Difference Vegetation Index
  • This NVD I is one of the indexes of vitality in forest trees, called the “Normalized Difference Vegetation Index”.
  • the reference data and remote sensing data are used in the infrared (R) and near infrared (NIR) regions.
  • NDVI (NIR-R) / (NIR + R).
  • GEMI Global Environment Monitoring Index
  • rj which is an index that reduces the effects of soil background and atmospheric costs
  • V [2 (NIR 2 ⁇ R 2 ) +1.5 NIR + 0.5 R].
  • NI + R + 0.5 the biomass of the specific tree species is calculated from the above measurement results of the crown size (area, major axis, minor axis) and spectral characteristics (vegetation index) (16).
  • biomass refers to the dry weight of stems, branches and leaves. The larger the canopy size (area, major axis, minor axis), the larger the size and the more mature trees.
  • FIG. 2 is a schematic diagram of each step in the method for estimating the biomass of forests and trees using high-resolution remote sensing data according to the present invention. That is, FIG. 2A shows a situation when a high-resolution color infrared photograph (for example, a scale of 1 / 7,000) of the tree 21 is taken by the aircraft 20 or the like.
  • a high-resolution color infrared photograph for example, a scale of 1 / 7,000
  • (B) shows the capture of a photograph into a computer.
  • an analog photograph 22 taken by film is read by a scanner 23 and digitized (for example, 1,200 dpi).
  • Shows the case of taking in (C) is a pre-analysis process such as geometric correction that corrects image distortion caused by the inclination of the attitude of the aircraft during observation. is there.
  • (D) is the extraction of the crown information. For example, by blackening the part 26 other than the crown 25 of the specific tree on a computer, only the crown 25 of the specific tree remains as an image. Based on the crown information, the size (area, major axis, minor axis) of the crown and its spectral characteristics are measured.
  • (E) is a model formula creation process based on the canopy information obtained as described above and on-site data.
  • the horizontal axis is the vegetation index, and the vertical axis is the biomass.
  • the analysis results are output as shown in (f), and the biomass per area and the annual biomass accumulation can be found.
  • Figure 3 shows the difference in crown ratio depending on the size of the crown.
  • Figure 3 (a) shows the state of a mature forest in which the crown 25 is closed in the pixel 30. However, its spectral characteristics can be measured.
  • Fig. 3 (b) shows the number of pixels in a tree 3
  • biomass estimation formula was created from the biomass measurement values in the field survey and tree crown information based on aerial images.
  • biomass measurement value in the field survey refers to the value obtained by measuring the DBH (breast height diameter) of all target trees in the field and calculating the biomass individually from this value using the relative growth formula. .
  • FIG. 4 (a) to (d) show the relationship between biomass and the results of each tree survey by field survey.
  • Fig. 4 (a) is a characteristic diagram showing the relationship between tree height and biomass.
  • Figure 4 (b) is a characteristic diagram showing the relationship between canopy thickness and biomass.
  • Fig. 4 (c) is a characteristic diagram showing the relationship between the average crown diameter and biomass.The average crown diameter has a higher correlation with biomass than the tree height in Fig. 4 (a) (the crown thickness in Fig. 4 (b). You can see that.
  • Fig. 4 (d) is a characteristic diagram showing the relationship between canopy area and biomass, and it can be seen that there is also a high correlation. Analysis results based on aerial images
  • FIG. 4 is a characteristic diagram showing the relationship between the average crown diameter and biomass, and is in good agreement with the characteristic diagram of the average crown diameter and biomass in FIG.
  • Fig. 5 (b) is a characteristic diagram showing the relationship between canopy area and biomass, and also agrees well with the characteristic diagram of canopy area and biomass shown in Fig. 4 (d). Therefore, an equation for calculating biomass was created from the average canopy diameter and canopy area, which have a high correlation with biomass.
  • the accuracy of the biomass estimation formula was verified by comparing the biomass measurement value obtained from the field survey with the biomass obtained by the above estimation formula.
  • the verification was performed using trees different from the trees used in the estimation formula creation.
  • Total biomass in the test trees 1, 06 1.9 kg
  • the distribution of the difference between the biomass estimation result using the average canopy diameter and the actual measurement value from the field survey is shown in Figure 5 (c). It is concentrated on small parts and shows high correlation.
  • the distribution of the difference between the biomass estimation result using the canopy area and the actual measurement value from the field survey is concentrated on the part with a small error, as shown in Fig. 5 (d). ing.
  • the total biomass in the test tree was 1,061.9 kg
  • the biomass obtained from the estimation formula using the average crown diameter was 1,036.8 kg.
  • the estimation accuracy based on the average crown diameter is 97.6%.
  • the present invention captures a photograph of a forest or a tree from a high place, and masks a portion other than a crown portion of a specific tree within a predetermined area based on the photograph to obtain the above-described image.
  • the feature is to estimate the pyomas of a specific tree from the size (area, major axis, minor axis) and spectral characteristics of the canopy occupying a given area, so that the crown is not blocked shortly after planting. Or even mature trees, the crown will not be blocked

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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  • General Health & Medical Sciences (AREA)
  • Electromagnetism (AREA)
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  • Computer Networks & Wireless Communication (AREA)
  • Image Processing (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

L'invention concerne un procédé permettant d'évaluer la biomasse des forêts et des arbres à l'aide de données à résolution élevée détectées à distance à des points élevés. On évalue la biomasse de types d'arbres spécifiques avec une précision élevée même lorsque les houppiers des forêts et des arbres ne sont pas rapprochés suite à la croissance naturelle nouvelle d'arbres jeunes ou venant d'être plantés, ou lorsque les houppiers des forêts et des arbres adultes ne sont pas rapprochés. (11) Des images à résolution élevée passant à une résolution très élevée sont prises (11) à l'aide de satellites à résolution élevée, d'aéronefs, d'hélicoptères radio et sont capturées dans des parties d'ordinateurs (46), d'autres parties différentes des types d'arbres spécifiques étant masquées (13). On mesure (14) les dimensions des houppiers (zones, petits diamètres, grands diamètres) des types d'arbres spécifiques restant après le masquage. On mesure (15) également les caractéristiques spectrales des types d'arbres spécifiques. On calcule la biomasse des types d'arbres spécifiques à partir des dimensions des houppiers ainsi que les caractéristiques spectrales (16). Puis, on calcule la quantité de biomasse annuelle cumulée en fonction de ces quantités de biomasse et on imprime (18) le résultat.
PCT/JP2003/001460 2002-02-13 2003-02-13 Procede d'evaluation de la biomasse des forets et des arbres a l'aide de donnees a resolution elevee detectees a distance Ceased WO2003069315A1 (fr)

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AU2003211938A AU2003211938B2 (en) 2002-02-13 2003-02-13 Method of biomass estimation for forests and trees by remote sensing high-resolution data
JP2003568386A JP4219819B2 (ja) 2002-02-13 2003-02-13 リモートセンシング高解像度データによる森林・樹木のバイオマス推定方法

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JP2007149104A (ja) * 2005-11-29 2007-06-14 National Arboretum Korea Forest Service Ｇｉｓを用いた植物資源数量化方法
CN105158413A (zh) * 2015-07-22 2015-12-16 兰州大学 一种用于遥感监测高寒草地基准样地的建立方法
WO2018034166A1 (fr) * 2016-08-17 2018-02-22 ソニー株式会社 Dispositif de traitement d'un signal et procédé de traitement d'un signal, et programme
CN108921885A (zh) * 2018-08-03 2018-11-30 南京林业大学 一种综合三类数据源联合反演森林地上生物量的方法
US20190166765A1 (en) * 2016-08-18 2019-06-06 Tevel Advanced Technologies Ltd. System and method for mapping and building database for harvesting-dilution tasks using aerial drones
CN110162872A (zh) * 2019-05-17 2019-08-23 中国科学院城市环境研究所 一种多源数据融合的森林资源清查生物量估算模型
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JP2007149104A (ja) * 2005-11-29 2007-06-14 National Arboretum Korea Forest Service Ｇｉｓを用いた植物資源数量化方法
US10607078B2 (en) 2013-03-25 2020-03-31 Sony Corporation Method, system, and medium having stored thereon instructions that cause a processor to execute a method for obtaining image information of an organism comprising a set of optical data
US12198425B2 (en) 2013-03-25 2025-01-14 Sony Group Corporation Method, system, and medium having stored thereon instructions that cause a processor to execute a method for obtaining image information of an organism comprising a set of optical data
US12014538B2 (en) 2013-03-25 2024-06-18 Sony Group Corporation Method, system, and medium having stored thereon instructions that cause a processor to execute a method for obtaining image information of an organism comprising a set of optical data
US11875562B2 (en) 2013-03-25 2024-01-16 Sony Group Corporation Method, system, and medium having stored thereon instructions that cause a processor to execute a method for obtaining image information of an organism comprising a set of optical data
US11699286B2 (en) 2013-03-25 2023-07-11 Sony Corporation Method, system, and medium having stored thereon instructions that cause a processor to execute a method for obtaining image information of an organism comprising a set of optical data
US11443509B2 (en) 2013-03-25 2022-09-13 Sony Corporation Method, system, and medium having stored thereon instructions that cause a processor to execute a method for obtaining image information of an organism comprising a set of optical data
CN105158413A (zh) * 2015-07-22 2015-12-16 兰州大学 一种用于遥感监测高寒草地基准样地的建立方法
US11047793B2 (en) 2016-08-17 2021-06-29 Sony Corporation Signal processing apparatus, signal processing method, and progress
JPWO2018034166A1 (ja) * 2016-08-17 2019-06-13 ソニー株式会社 信号処理装置および信号処理方法、並びにプログラム
WO2018034166A1 (fr) * 2016-08-17 2018-02-22 ソニー株式会社 Dispositif de traitement d'un signal et procédé de traitement d'un signal, et programme
US11846946B2 (en) * 2016-08-18 2023-12-19 Tevel Advanced Technologies Ltd. System and method for mapping and building database for harvesting-dilution tasks using aerial drones
US20190166765A1 (en) * 2016-08-18 2019-06-06 Tevel Advanced Technologies Ltd. System and method for mapping and building database for harvesting-dilution tasks using aerial drones
JP2019144607A (ja) * 2018-02-15 2019-08-29 西日本高速道路株式会社 衛星画像を用いた樹種推定方法、および、樹種推定された樹木の健全度判定方法
JP7046432B2 (ja) 2018-02-15 2022-04-04 西日本高速道路株式会社 衛星画像を用いた樹種推定方法、および、樹種推定された樹木の健全度判定方法
CN108921885B (zh) * 2018-08-03 2020-05-12 南京林业大学 一种综合三类数据源联合反演森林地上生物量的方法
CN108921885A (zh) * 2018-08-03 2018-11-30 南京林业大学 一种综合三类数据源联合反演森林地上生物量的方法
CN110162872A (zh) * 2019-05-17 2019-08-23 中国科学院城市环境研究所 一种多源数据融合的森林资源清查生物量估算模型
US11978227B2 (en) 2021-08-19 2024-05-07 Forest Carbon Works, PBC Systems and methods for forest surveying
US11481904B1 (en) * 2022-01-04 2022-10-25 Natural Capital Exchange, Inc. Automated determination of tree inventories in ecological regions using probabilistic analysis of overhead images

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