• Journal of Korean Society of Forest Science
• /
• v.103 no.4
• /
• pp.639-645
• /
• 2014

This study was conducted to evaluate the management efficiency of oak mushroom farms in Korea using the Data Envelopment Analysis (DEA), which is one of the non-parametric estimation methods. The data that was analyzed in this study was from the result of 2013 survey entitled "Standard Diagnostic Table for Oak Mushroom Management", which was conducted from March 2012 to October 2012. This survey was based on the inputs and outputs of 20 oak mushroom farms. Specifically, this study analyzed the technical efficiency, pure-technical efficiency and scale efficiency using CCR and BCC model of the DEA methods. Furthermore, this study compares the management efficiency between the full time oak mushroom production farms and part time oak mushroom production farms. Results showed that mean value for the technical efficiency was 0.655 which is considered as inefficient in general. For the pure-technical efficiency and scale efficiency, the mean values were 0.830 and 0.747, respectively which showed that inefficiency in the management was observed in the mushroom farms. Results also showed that there were seven farms with a total efficiency of 1, namely Decision Making Unit(DMU)2, DMU5, DMU6, DMU8, DMU10, DMU15 and DMU20. The management efficiency of DMU7 specifically the inputs for production was analyzed and compared to DMU5 and DMU6 and results showed that the DMU7 had an excessive inoculation and site development cost. Lastly, it was also observed that the full time mushroom production farms were more efficient as compared to the part time mushroom farms because of the lower scale efficiency value or smaller area for mushroom production allotted in the part time farms.

• Journal of Korean Society of Forest Science
• /
• v.87 no.2
• /
• pp.300-307
• /
• 1998

It is not an easy task for forest managers to make sound decisions on forest management and operations planning because of huge sets of spatial and temporal data and complex decision-making processes involved. However, as an efficient tool, GIS techniques enable them to enhance broad understandings on forest inventory and management conditions. In this study, we developed a GIS model for field use in forest management. In building the model, we have chosen MapInfo version 4.0 as the basic engine of the model. The model also includes an interface module to help forest managers use MapInfo functions easily. It handles MapInfo functions required to manage inventory data and analyze spatial distributions of forest stands. For testing field applicability of the model, we have build field data sets for a district of Chunchun National Forest. Then, we tested functions through quarrying stand attributes and constructing thematic maps. In this paper, the structures and functions of the model as well as the results of field applications are discussed.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_2
• /
• pp.1031-1035
• /
• 2019

Nowadays, the utilization infrastructure of domestic satellite information is expanding rapidly. Especially, the development of agriculture and forestry satellite is expected to drastically change the utilization of satellite information in the forest sector. The launch of the satellite is expected in 2023. Therefore, NIFoS and academic experts in forest sectors have prepared "Special Issue on Forest Management Research using Optical Sensors and Remote Sensing Technologies" in order to understand new remote sensing technologies and suggest the future direction of forest research and decision-making. This special issue is focused on a variety of fields in forest remote sensing research, including forest resources survey, forest disaster detection, and forest ecosystem monitoring. The new research topics for remote sensing technologies in forest sector focuses on three points: development of new indicators and information for accurate detection of forest conditions and changes, the use of new information sources such as UAV and new satellites, and techniques for improving accuracy through the use of artificial intelligence techniques.

• Journal of Ecology and Environment
• /
• v.45 no.4
• /
• pp.255-263
• /
• 2021

Background: Ecosystem service mapping is an important tool for decision-making in landscape planning and natural resource management. Today, pollination service mapping is based on the Lonsdorf model (InVEST software) that determines the availability of nesting and floral resources for each land cover and estimates pollination according to the foraging range of the desired species. However, it is argued that the Lonsdorf model has significant limitations in estimating pollination in a landscape that can affect the results of this model. Results: This paper presents a free software, named PollMap, that does not have the limitations of the Lonsdorf model. PollMap estimates the pollination service according to a modified version of the Lonsdorf model and assumes that only cells within the flight range of bees are important in the pollination mapping. This software is produced for estimating and mapping crop pollination in agricultural landscapes. The main assumption of this software is that in the agricultural landscapes, which are dominated by forest and agriculture ecosystems, forest patches serve only as a nesting habitat for wild bees and the surrounding fields provide floral resources. Conclusion: The present study provided new software for mapping crop pollination in agricultural landscapes that does not have the limitations of the Lonsdorf model. We showed that the use of the Lonsdorf model for pollination mapping requires attention to the limitations of this model, and by removing these limitations, we will need new software to obtain a reliable mapping of pollination in agricultural landscapes.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.4 no.3
• /
• pp.41-50
• /
• 2001

Recently our nature of environment has destroyed by a large scaled forest fire. In order to manage these forest fires, forecasting of it is considered as the most important thing. In this paper the database related to forest fire was first built and the efficient forest fire information management system was implemented by using GIS. The main goal of this system is that forest fire managers have GUI(graphic user interface) to analyze data of forest fire effectively and update and retrieve information in database. For the efficient GUI, this system is built in Visual Basic 6.0 and Map Object 2.0. Map Object 2.0 is combined to have various and powerful functionality of GIS analysis as component ware. The Oracle 8.0 is used as DBMS in this study to manage all the spatial and attributed information in database effectively. In the future, this system will play a critical role as making a decision supporting system for scientific forest fire protection and help real time forest fire hazard information offers service for public welfare administration business management.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.2
• /
• pp.11-22
• /
• 2009

Recently the integration and development of ST(Spatial Technology) and forest geographic information have been used very efficiently for the forest administration. However, even though many application system related to forest information have been developed and improved, there are still paper based inventories management and hand work for data construction and upgrade. In this study the forest information warehouse, which is mapped and managed at work-site operations, was constructed based GIS technology so that the standardization and consistency of current data could be acquired in real time. In addition, these thematic maps were conducted on high resolution satellite images and managed in web based forest information data warehouse form and finally shared through Internet for the very first-line administration officials. This study shows that the forest information standardization service of municipal governments very first time in the Korea and provides the unified decision making support and enterprise formed forest database so that is expected to be the very successful sample to suggest the prototype of national forest spatial data infrastructure.

• Journal of Korean Society of Forest Science
• /
• v.104 no.4
• /
• pp.649-656
• /
• 2015

The objective of this study was to analyze the optimal thinning regimes for timber or carbon managements in Cryptomeria japonica stands of Hannam Experimental Forest, Korea Forest Research Institute. In solving the problem, PATH algorithm, developed by Paderes and Brodie, was used as the decision-making tool and the individual-tree/distance-free stand growth simulator for the species, developed by Kwon et al., was used to predict the stand growth associated with density control by thinning regimes and mortality. The results of this study indicate that the timber management for maximum net present value (NPV) needs less number of but higher intensity thinnings than the carbon management for maximum carbon absorption does. In case of carbon management, the amount of carbon absorption is bigger than that of timber management by about 6% but NPV is reduced by about 3.2%. On the other hand, intensive forest managements with thinning regimes promotes net income and carbon absorption by about 60% compared with those of the do-nothing option.

• Journal of Forest and Environmental Science
• /
• v.16 no.1
• /
• pp.119-123
• /
• 2000

This paper studies the methods to support decision making for forest management Using GIS. Specially, most important is selecting restrict area to timber harvest suitable on scheduling its harvest in experimental forest of kangwon national university. Because timber harvesting causes water pollution, land sliding and soil erosion, it is necessary to restrict area to be harvest. The study is analyzed with Buffering modules and overlay modules which are an function of Arcinfo 7.1. As a result, restricted area is 52.64ha in total area. Of which Hardwood stand 13.21ha, pinus Pinus koraiensis stand 26.44ha, Larix leptolepis stand 12.38ha and Pinus rigida stand 0.61ha.

• Journal of Korean Society of Forest Science
• /
• v.111 no.2
• /
• pp.302-310
• /
• 2022

Here we aimed to classify the major coniferous tree species (Pinus densiflora, Pinus koraiensis, and Larix kaempferi) by tree measurement information and machine learning algorithms to establish an efficient forest management plan. We used national forest monitoring information amassed over nine years for the measurement information of trees, and random forest (RF), XGBoost (XGB), and light GBM (LGBM) as machine learning algorithms. We compared and evaluated the accuracy of the algorithm through performance evaluation using the accuracy, precision, recall, and F1 score of the algorithm. The RF algorithm had the highest performance evaluation score for all tree species, and highest scores for Pinus densiflora, with an accuracy of about 65%, a precision of about 72%, a recall of about 60%, and an F1 score of about 66%. The classification accuracy for the dominant trees was higher than about 80% in the crown classes, but that of the co-dominant trees, the intermediate trees, and the overtopper trees was evaluated as low. We consider that the results of this study can be used as reference data for decision-making in the selection of thinning trees for forest management.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.454-454
• /
• 2022

Residents near the fire site are more anxious as they rely only on media information and the government's evacuation order due to the lack of information to understand the progress of the wildfire. Therefore, in the event of a wildfire, we try to understand the inconvenience of not being able to know the progress of the fire and solve it. This makes it possible to check the progress of wildfires and the spread of debris using the system interface (API) and weather data of the thermal infrared satellite image data (NASA FIRMS, Fire Information for Resource Management System), and finally, the purpose of this study. The results are provided through the Web including GIS-based visualization to provide decision-making reference information for evacuation in the event of a forest fire from the perspective of residents.