• 제목/요약/키워드: Precision forestry

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원격탐사 기술의 국내 정밀 임업 가능성 검토: 임업분야의 원격탐사 적용사례 분석을 중심으로 (Precision Forestry Using Remote Sensing Techniques: Opportunities and Limitations of Remote Sensing Application in Forestry)

  • 우희성;조승완;정건휘;박주원
    • 대한원격탐사학회지
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    • 제35권6_2호
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    • pp.1067-1082
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    • 2019
  • 본 논문은 현재 산림 분야 연구에 적용되고 향후 적용가능한 원격탐사 기술에 대한 국내외 발행된 peer-reviewed 논문의 리뷰를 바탕으로 원격탐사 기술의 국내 산림분야 적용에 대한 가능성과 한계점을 서술하였다. 원격탐사 기술은 정밀한 분석과 정교한 자료 수집을 바탕으로 대단위 산림면적 분석에 있어 필수적이며, 정보통신기술과의 융합으로 향후 임업의 새로운 시대를 열어갈 핵심 기술이다. 본 리뷰 논문에서는 다양한 원격탐사 기술 가운데 레이저 스캐닝 기술, 위성영상을 이용한 산림 측정 기술, 그리고 무인항공기를 이용한 기존 국내·외 연구사례를 분석하여 국내 산림분야 적용 가능성에 대한 기회와 한계점에 대해 서술하였다.

Study on Aboveground Biomass of Pinus sylvesris var. mongolica Plantation Forest in Northeast China Based on Prediction Equations

  • Jia, Weiwei;Li, Lu;Li, Fengri
    • Journal of Forest and Environmental Science
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    • 제28권2호
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    • pp.68-74
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    • 2012
  • A total of 45 Pinus sylvestnis var. mongolica trees from 9 plots in northeast China were destructively sampled to develop aboveground prediction equations for inventory application. Sampling plots covered a range of stand ages (12-47-years-old) and densities (450-3,840/ha). The distribution of aboveground biomass of whole-trees and tree component (stems, branches and leaves) of individual trees were studied and 4 equations were developed as functions of diameter at breast height (DBH), total height (HT). All the equations have good estimation effect with high prediction precision over 90%. Forest biomass was estimated based on the individual biomass prediction equations. It was found forest biomass of all organs increased with the increasing of stand age and density. And the period of 45-50 years was the suitable harvest time for Pinus sylvesris plantation.

Individual Tree Growth Models for Natural Mixed Forests in Changbai Mountains, Northeast China

  • Lu, Jun;Li, Fengri
    • 한국산림과학회지
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    • 제96권2호
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    • pp.160-169
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    • 2007
  • The data used to develop distance-independent individual models for natural mixed forests were collected from 712 remeasured permanent sample plots (25,526 trees) of 10-year periodic from 1990 to 2000 in Baihe Forest Bureau of Changbai Mountains, northeast China. Based on analyzing relationship between diameter increment of individual trees with tree size, competitive status, and site condition, the diameter growth models for individual trees of 15 species growing in mixed-species uneven-aged forest stands, that have simple form, good predicting precision, and easily applicable, were developed using stepwise regression method. The main variables influencing on diameter increment of individual trees were tree size and competition, however, the site conditions were not significantly related with diameter increment. The tree size variables (lnDBH and $DBH^2$) were the most significant and important predictors of diameter growth existing in all 15 growth models. The diameter increment was directly proportional to tree diameter for each species. For the competitive factors in growth model, the relative diameter (RD), canopy closure (P), and the ratio of diameter of subject tree with maximum diameter (DDM) were contributed to the diameter increment at a certain extent. Other measures of stand density, such as basal area of stand (G) and stand density index (SDI), were not significantly influenced on diameter increment. Site factors, such as site index, slope and aspect were not important to diameter increment and excluded in the final models. The total variance explained by the final models of squared diameter increment ($R^2$) for all 15 species ranged from 35% to 72% and these results compared quit closely with those of Wykoff (1990) for mixed conifer stands. Using independent data set, validation measures were evaluated for predicting models of diameter increment developed in this study. The result indicated that the estimated precision was all greater than 94% and the models were suitable to describe diameter increment.

Evaluation of a Nutrition Model in Predicting Performance of Vietnamese Cattle

  • Parsons, David;Van, Nguyen Huu;Malau-Aduli, Aduli E.O.;Ba, Nguyen Xuan;Phung, Le Dinh;Lane, Peter A.;Ngoan, Le Duc;Tedeschi, Luis O.
    • Asian-Australasian Journal of Animal Sciences
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    • 제25권9호
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    • pp.1237-1247
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    • 2012
  • The objective of this study was to evaluate the predictions of dry matter intake (DMI) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant nutrition system (LRNS) model. Animal information and feed chemical characterization were obtained from five studies. The initial mean body weight (BW) of the animals was 186, with standard deviation ${\pm}33.2$ kg. Animals were fed ad libitum commonly available feedstuffs, including cassava powder, corn grain, Napier grass, rice straw and bran, and minerals and vitamins, for 50 to 80 d. Adequacy of the predictions was assessed with the Model Evaluation System using the root of mean square error of prediction (RMSEP), accuracy (Cb), coefficient of determination ($r^2$), and mean bias (MB). When all treatment means were used, both levels of solution predicted DMI similarly with low precision ($r^2$ of 0.389 and 0.45 for level 1 and 2, respectively) and medium accuracy (Cb of 0.827 and 0.859, respectively). The LRNS clearly over-predicted the intake of one study. When this study was removed from the comparison, the precision and accuracy considerably increased for the level 1 solution. Metabolisable protein was limiting ADG for more than 68% of the treatment averages. Both levels differed regarding precision and accuracy. While level 1 solution had the least MB compared with level 2 (0.058 and 0.159 kg/d, respectively), the precision was greater for level 2 than level 1 (0.89 and 0.70, respectively). The accuracy (Cb) was similar between level 1 and level 2 (p = 0.8997; 0.977 and 0.871, respectively). The RMSEP indicated that both levels were on average under-or over-predicted by about 190 g/d, suggesting that even though the accuracy (Cb) was greater for level 1 compared to level 2, both levels are likely to wrongly predict ADG by the same amount. Our analyses indicated that the level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known.

A Study on the Status and Future Directions of IT Convergence Policy by the Ministry of Food, Agriculture, Forestry and Fisheries in Korea

  • Huang, Minghao;Park, Heun Dong;Moon, Junghoon;Choe, Young Chan
    • Agribusiness and Information Management
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    • 제4권2호
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    • pp.22-31
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    • 2012
  • Research and technology has been transforming the agriculture to agribusiness which encompasses all operations with all the connections from faming per se, to manufacture & distribution of production supplies and farm commodities. Further, with the revolutionary development of information technology in the last two decades, we cannot talk about agribusiness process alone without considering the information technology embedded in the artifact, process, and structure. Despite the emergence of precision agriculture (PA) which is supported by IT based innovations which can not only improve efficiency in farming operations but also contribute to environmental sustainability, the adoption of IT among farmers and in agriculture industry are rather low than expected. Thus, Korean government has been seeking to converge IT into food, agriculture, forestry and fisheries to improve the competency of the agribusiness, and much progress has been made. This paper investigated the status quo of the current IT convergence with Food, Agriculture, Forestry and Fisheries in Korea, and further proposed future policy directions.

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농가경제조사의 현황과 개선 방향 (The current status and the improvable directions of the farm household economy survey)

  • 김규성
    • 응용통계연구
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    • 제11권1호
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    • pp.29-39
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    • 1998
  • 농림부에서 실시하고 있는 농가경제조사의 현황을 살펴보고, 표본조사의 결과로서 발표되는 농가경제통계의 통계적 신뢰도를 분석하였으며 통계결과의 신뢰도를 향상시킬 수 있는 개선방향을 제시하였다. 그리고 향후 농가경제조사가 지향해야 할 방향을 제시하고 이를 실현하기 위한 몇가지 방법을 제안하였다.

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Estimate Site Index Equations for Pinus densiflora Based on Soil Factors in Gyeonggi Province

  • Jun, Il-Bin;Nor, Dea-Kyun;Jeong, Jin-Hyun;Kim, Sung-Ho;Chung, Dong-Jun;Han, Seung-Hoon;Choi, Jung-Kee;Chung, Dong-Jun
    • Journal of Forest and Environmental Science
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    • 제24권3호
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    • pp.155-158
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    • 2008
  • Site index is the essential tool for forest management to estimate the productivity of forest land Generally, site index equation is developed and used by relationship between stand age and dominant tree heights. However, there is a limit to use the site index equation in the application of variable ages, environmental influence, and estimation of site index for unstocked land. Therefore, it was attempted to develop a new site index equations based on various environmental factors including site and topographical variables. This study was conducted to develop regional site index equations based on the relationship between site index and soil factors for Pinus densiflora. Environmental factors that obtained from GIS application, were selected by stepwise-regression. Site index Equation was estimated by multiple regression from selected factors. Four environmental factors were selected in the final site index equations by stepwise regression. It was observed that coefficients of determination for site index equations were ranged from 0.34 which seem to be relatively low but good enough for estimation of forest stand productivity. The site index equations developed in this study were also verified to be useful by three evaluation statistics such as model's estimation bias, model's precision and mean square error type of measure.

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An Improved Fast Camera Calibration Method for Mobile Terminals

  • Guan, Fang-li;Xu, Ai-jun;Jiang, Guang-yu
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1082-1095
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    • 2019
  • Camera calibration is an important part of machine vision and close-range photogrammetry. Since current calibration methods fail to obtain ideal internal and external camera parameters with limited computing resources on mobile terminals efficiently, this paper proposes an improved fast camera calibration method for mobile terminals. Based on traditional camera calibration method, the new method introduces two-order radial distortion and tangential distortion models to establish the camera model with nonlinear distortion items. Meanwhile, the nonlinear least square L-M algorithm is used to optimize parameters iteration, the new method can quickly obtain high-precise internal and external camera parameters. The experimental results show that the new method improves the efficiency and precision of camera calibration. Terminals simulation experiment on PC indicates that the time consuming of parameter iteration reduced from 0.220 seconds to 0.063 seconds (0.234 seconds on mobile terminals) and the average reprojection error reduced from 0.25 pixel to 0.15 pixel. Therefore, the new method is an ideal mobile terminals camera calibration method which can expand the application range of 3D reconstruction and close-range photogrammetry technology on mobile terminals.

지상 LiDAR를 활용한 침엽수림의 수고 및 흉고직경 측정 (Measurement of Tree Height and Diameter Using Terrestrial Laser Scanner in Coniferous Forests)

  • 고병준;박세익;박희정;이상현
    • 한국환경과학회지
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    • 제31권6호
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    • pp.479-490
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    • 2022
  • This study was to evaluate the utilization of terrestrial light detection and ranging for forest inventory in coniferous forests. Heights and diameter of the stand trees were measured manually using the traditional measurement method and the method using terrestrial LiDAR. The results of two methods were compared and analyzed to evaluate accuracy and feasibility. The terrestrial LiDAR used fixed and handy types to compare the accuracy between different operational methods. Comparative analyses used a paired t-test and Bland-Altman plot analysis. In the case of tree heights, the average of difference between the traditional method and terrestrial LiDAR for each plot was 0.81 m, -0.07 m, and 0.13 m for fixed type; 2.88 m, 1.19 m, and 0.93 m for the handy type. In the case of tree diameter at breast height, the average value of the difference between traditional methods and terrestrial LiDAR for each plot was 0.13 cm, -0.66 cm, and -0.03 cm for fixed type; 2.36 cm, 2.13 cm, and 1.92 cm for the handy type. The values from the method using the fixed type was highly consistent with that using the traditional measurement methods; the average difference was closer to zero. The crown density influences the precision of the height measurement using terrestrial LiDAR in coniferous forests. Therefore, future studies should focus on verifying the accuracy of terrestrial LiDAR in forests and on expanding the utilization of terrestrial LiDARs according to their operational methods.

Allometric equation for estimating aboveground biomass of Acacia-Commiphora forest, southern Ethiopia

  • Wondimagegn Amanuel;Chala Tadesse;Moges Molla;Desalegn Getinet;Zenebe Mekonnen
    • Journal of Ecology and Environment
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    • 제48권2호
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    • pp.196-206
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    • 2024
  • Background: Most of the biomass equations were developed using sample trees collected mainly from pan-tropical and tropical regions that may over- or underestimate biomass. Site-specific models would improve the accuracy of the biomass estimates and enhance the country's measurement, reporting, and verification activities. The aim of the study is to develop site-specific biomass estimation models and validate and evaluate the existing generic models developed for pan-tropical forest and newly developed allometric models. Total of 140 trees was harvested from each diameter class biomass model development. Data was analyzed using SAS procedures. All relevant statistical tests (normality, multicollinearity, and heteroscedasticity) were performed. Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). The root mean square error (RMSE) was used for measuring model bias, precision, and accuracy. The coefficient of determination (R2 and adjusted [adj]-R2), the Akaike Information Criterion (AIC) and the Schwarz Bayesian information Criterion was employed to select most appropriate models. Results: For the general total AGB models, adj-R2 ranged from 0.71 to 0.85, and model 9 with diameter at stump height at 10 cm (DSH10), ρ and crown width (CW) as predictor variables, performed best according to RMSE and AIC. For the merchantable stem models, adj-R2 varied from 0.73 to 0.82, and model 8) with combination of ρ, diameter at breast height and height (H), CW and DSH10 as predictor variables, was best in terms of RMSE and AIC. The results showed that a best-fit model for above-ground biomass of tree components was developed. AGBStem = exp {-1.8296 + 0.4814 natural logarithm (Ln) (ρD2H) + 0.1751 Ln (CW) + 0.4059 Ln (DSH30)} AGBBranch = exp {-131.6 + 15.0013 Ln (ρD2H) + 13.176 Ln (CW) + 21.8506 Ln (DSH30)} AGBFoliage = exp {-0.9496 + 0.5282 Ln (DSH30) + 2.3492 Ln (ρ) + 0.4286 Ln (CW)} AGBTotal = exp {-1.8245 + 1.4358 Ln (DSH30) + 1.9921 Ln (ρ) + 0.6154 Ln (CW)} Conclusions: The results demonstrated that the development of local models derived from an appropriate sample of representative species can greatly improve the estimation of total AGB.