FORMATH SAPPORO 2024
Program: March 16 (Sat) - 17 (Sun)March 16, 2024
09:50 ～ 10:00 Opening Remarks
1.

Dr. Matsumura

Session 1

Coordinator: Dr. Sokh

Improving rice production estimates using
10:00 ～ 10:30 hybrid method of multivariate time series andmachine learning
Forecasting of Cocoa beans export-import valuesof Indonesia and exchange rate data using vector
10:30 ～ 11:00
error-correction and long short term memory
hybrid models

Bustanul Arifin*, Warsono,
Dian Kurniasari, Ririn
Aristiyani, Fitri Yunilestari

University of Lampung,Indonesia

Warsono*, Dian
Kurniasari ,Mawar Alhani

University of Lampung,Indonesia

11:00 ～ 11:10 Break2.

Session 2
Intensive monitoring plots in forest ecosystems:
11:10 ～ 11:40 Data rational and first results in cork oak forest
systems
Competition indices further improve the model's
11:40 ～ 12:10
predictive ability

Coordinator: Dr. Takahashi
Nuno de Almeida Ribeiro*

University of Evora,PortugalShes Kanta Bhandari**

Tribhuvan University,
Nepal

12:10 ～ 13:30 Lunch
3.

Session 3
Measurement and calculation of emissions
reduction in the North Central Coast region of
13:30 ～ 14:00
Vietnam to help receiving REDD+ result-based
payment
Countries understanding of current and future
14:00 ～ 14:30 GHG emissions for the Agriculture, Forestry andOther Land use sector
Impact of carbon market on timber and14:30 ～ 15:00 non-timber resources under sustainable forest
ecosystem management

Coordinator: Dr. Ribeiro
Nguyen Dinh Hung*

Forestry Inventory andPlanning Institute,
Viet Nam

Nicklas Forsell*International Institute ofApplied Systems
Analysis, Austria

Patrick Asante*

Ministry of Forests, BC,
Canada

15:00 ～ 15:20 Break4.

Session 4
Coordinator: Dr. Konoshima
Optimal Reserve Site Selection of Gotjawal
15:20 ～ 15:50
Ara Seol*
Forests in Jeju Island, Korea
Distance Constraints to Create Green-Pathway as
15:50 ～ 16:20 Environmental Concerns for SpatiallyAtsushi Yoshimoto*Constrained Harvest Scheduling
16:20 ～ 16:30 Break5.

16:30 ～ 17:00

Session 5

Institute of Statistical
Mathematics, Japan

Coordinator: Dr. Surový

Has Economic Growth Been Reducing Natural
Disaster Damages in Vietnam?
Developing a Landslide Probability Model Using

17:00 ～ 17:30 Similarity-Based Sampling of Absence Data: A Case

Study in Itsuki Village, Kumamoto Prefecture, Japan

17:30 ～ 19:00 Dinner
19:00 ～ 20:30

National Institute ofForest Science, Korea

FORMATH Research Society Annual General
Meeting

1

Tetsuya Michinaka*, Ehara
FFPRI, Japan
Makoto, VU Tan Phuong,
Nguyen Thuy My Linh,
Okamoto Takashi, Shimizu
Katsuto, HA Van Tiep, VU Van
Tuan
Yasushi Mitsuda*
Univ. of Miyazaki. Japan

March 17, 2024
6.

Session 6
Using social media big data to assesstourism pressure and its impact on
10:00 ～ 10:25
conserved animals - Shei-Pa National
Park as an example
Analysis of Economic Utilization on
10:25 ～ 10:50 Domestic Timber of Larix kaempferi inSouth Korea
Spatial and temporal pattern of wildlife
10:50 ～ 11:15
mortality in vehicle collisions in Nepal
Analysis of the geographic and vegetation
factors influencing predation damage on sea
11:15 ～ 11:40 turtle eggs by alien Japanese wild boar (Sus
scrofa leucomystax) on Tokashiki Island,
Okinawa, Japan

Coordinator: Dr. Mitsuda
Chih-Lin Liu*

National Chung Hsing University,
TaiwanHee Han*Seoul National University,
Korea

Narayan Prasad Gautam*

Tribhuvan University, Nepal

Takahiro Hirai,
Masashi Konoshima*,
Takeshi Eto,
Ikuo Ota

University of the Ryukyus, Japan

11:40 ～ 12:40 Lunch
7.

Session 7

Coordinator: Dr. Han

12:40 ～ 13:05

Seed Orchard Establishment in
Cambodia: Experiences and Challenge

Heng Sokh*

13:05 ～ 13:30

Establishment of High Value Tree
Species Breeding Center in Cambodia.

Ma Vuthy*

Potential improving of local livelihood
relating to Non-Timber Forest Products(NTFPs) commercial utilization in
13:30 ～ 13:55
Laos: A case study in the northern partof Laos, Phieng District Xayaboury
Province.

Phongxiong Wanneng*

Institute of Forest and Wildlife
Research and Development,
Cambodia
Institute of Forest and Wildlife
Research and Development,
Cambodia
National University of Laos,
Laos

13:55 ～ 14:15 Break8.

Session 8
Estimation tree growth from bitemporal
14:15 ～ 14:40 LiDAR data: A case study in the
Bohemian Switzerland National Park
Remote sensing-based monitoring of
14:40 ～ 15:05 natural disturbances in forest ecosystemusing modern high-tech data
Applications of AI in forest
15:05 ～ 15:30
management. Examples and opinions
Selection of time varying
15:30 ～ 15:55
Height-Diameter curves

Coordinator: Dr. Forsell
Zlatica Melichová*

Czech University of Life Sciences
Prague, Czech Republic

Tereza Hüttnerová*

Czech University of Life Sciences
Prague, Czech RepublicPeter Surový*Tetsuji Tonda*

15:55 ～ 16:00 Closing Remarks

Dr. Yoshimoto

Czech University of Life Sciences
Prague, Czech Republic
Prefectural University ofHiroshima, Japan
ISM, Japan

16:00 ～ 19:00 Dinner* indicates those invited speaker, while ** indicates online presentation.

ONLINE:Topic FORMATH 2024 SAPPORO, Date: 2024/3/16-17 09:00 - 18:00
https://us06web.zoom.us/j/84685191514?pwd=c2t5sKHGrPS8Iibt4bZrFmwUeEmbGn.1
Meeting ID: 846 8519 1514, Passcode: 917799

2

March 16, 2024
Session 1
Improving Rice Production Estimates Using Hybrid Method of Multivariate Time Series and Machine Learning
Bustanul Arifin (University of Lampung, Indonesia), Warsono, Dian Kurniasari, Ririn Aristiyani, Fitri Yunilestar
The objective of this study is to improve rice production estimates using a hybrid method of multivariate time series andmachine learning. Specifically, the study reviews the potential figures for rice production for the past 6 years, which arecalculated using the area sampling frame (KSA) method, and examines the pattern of relationship between several
variables that determine the figures of harvested areas, productivity, and rice production. The study employs a hybrid
method of multivariate time series techniques and machine learning by analyzing monthly data on harvested area,
productivity, and rice production collected from over 23 thousand segment samples across Indonesia. The study findsthat the existing actual and potential data on harvested area of rice, productivity, and rice production is problematic
because the deviation from the actual figures is quite large. The performance of productivity and technological changes
has not been fully captured in the rice production figures and other relevant publications on the Indonesian riceeconomy. The new rice estimates using a hybrid method of multivariate time series and machine learning have
improved the consistency of potential and actual data of harvested areas, thereby improving productivity and riceproduction estimates. The new estimates using the hybrid method are also able to capture the farmers’ initiatives,
community efforts, and government programs to increase rice productivity, thereby reflecting the efficiency of
productivity-increasing and farmers’ welfare-improving programs in Indonesia.
Forecasting of Cocoa beans export-import values of Indonesia and exchange rate data using vector
error-correction and long short term memory hybrid models
Warsono (Department of Mathematics, University of Lampung, Indonesia), Dian Kurniasari ,Mawar Alhani
In this research, we investigate the predictive capability of a hybrid model combining Vector Error Correction Model(VECM) and Long Short-Term Memory (LSTM) networks for forecasting the dynamics of cocoa export-import value
and exchange rate of Indonesia fluctuations. The study employs monthly data on cocoa export and import values frommajor producing and consuming countries, alongside exchange rate fluctuations, spanning from 2010 to 2023. Ourevaluation focuses on forecasting accuracy, using metrics such as Root Mean Square Error (RMSE), Mean Absolute
Percentage Error (MAPE), and Accuracy. The VECM-LSTM hybrid model produces an RMSE of 8040.11, a MAPE of
0.595, and Accuracy of 99.405 with 80% training data and 20% 5esting data.

3

March 16, 2024
Session 2
Intensive monitoring plots in forest ecosystems: Data rational and first results in cork oak forest systems
Nuno de Almeida Ribeiro (University of Évora, Portugal)
In Iberian Peninsula, the effects of climate change altered both precipitation and temperature regimes increasing thearidity in all territory. The extreme events are also increased with particular relevance to high temperature periods andprolonged drought. The new climatic dynamics and its unknow contribution to the forest systems functioning led to thenecessity of new modelling approaches based on structural functional rational, more in line with basic sciences. For thatmodelling purpose, a set of intensive monitoring plots where installed with continuous monitoring systems of radiation
absorption, interception of precipitation, evapotranspiration, nutrient uptake, photosynthesis, respiration, photosynthate
allocation, senescence and mortality in addition with the tree 3D periodic dendrometric data all collected in long term
ecological Mediterranean forest research plots. In the present work it is presented the complex data structure rational
and the synchronic/diachronic statistics used for the presentation and analysis of the first results in cork oak forest
systems. The results show the contribution of the functional structural variables on tree growth responses and permitted
to develop presented new with modelling strategies.
Competition indices further improve the model's predictive ability
Shes Kanta Bhandari (Tribhuvan University, Nepal)
This study aims to analyse the growth of individual trees of jarrah (Eucalyptus marginata), a wide-spread species
having ecological and economic importance in Western Australia. Specifically, tried to find 1) Does tree size predict thetree growth, 2) whether this prediction could be improved by accounting for competition, 3) how many neighbouring
trees or what neighbourhood distance needed to be considered when accounting for competition; and 4) whether
neighbouring tree growth could be a potential predictor variable. Tree size was significantly predicted the growth.
Prediction was improved when competition was included in the models. A new spatial competition index (CI)developed in this study performed better than previously developed CIs. Prediction of diameter growth was optimized
by accounting for competition from the 10 to 12 closest competitors or competitors within ~10 m from the base of thesubject tree. As competition from neighbours had a significant negative effect on growth, we recommend including
neighbourhood competition when explaining/predicting growth and considering thinning treatments to minimize theeffect of competition on growth. The modelling approaches developed in this study are likely to be useful tools forunderstanding and managing individual tree growth of any species in the world where competition among trees restricts
individual growth. Novelties include the first model explaining individual jarrah growth; an effective new competitionindex; an approach to testing how many neighbouring trees or what neighbourhood distance needs to be consideredwhen accounting for competition.
Key words: competition, growth, jarrah, model, thinning.

4March 16, 2024
Session 3
Measurement and Calculation of emissions reduction in the North Central Coast region of Vietnam to help
receiving REDD+ result-based payment
Nguyen Dinh Hung (Forest Inventory and Planning Institute, Vietnam)
In this work, we used the sample plots data collected in the North Central Coast region of Vietnam during periods
2001-2005, 2006-2010 and 2016-2020 taken from the national forest inventory, monitoring and assessment project tocalculate the emission/removal factors and the regional forest cover maps of the years 2005, 2010, 2015 and 2019 togenerate the activity data. The emission/removal factors were then used in combination with the activity data tocalculate the emissions reduction for the period 2018-2019. To meet the requirement from the Forest Carbon
Partnership Facility (FCPF), the uncertainty of the emission reduction was calculated using the Monte Carlo simulation
method. The results of this work have helped Vietnam to get the first REDD+ result-based payment of 51.5 million
USD, which will be used to promote better forest protection and management in Vietnam.
Countries understanding of current and future GHG emissions for the Agriculture, Forestry and Other Land use
sectorNicklas Forsell (International Institute of Applied Systems Analysis, Austria)
In this presentation I will share our latest work related to the global GHG emissions for the Agriculture, Forestry andOther Land use (AFOLU) sector. We have created a database of countries historically reported estimates and targets as
submitted to the UNFCCC in terms of their Nationally Determined Contribution (NDCs) and Long-Term strategies(LTS). From these databases we will discuss the current state of the sector and which countries/regions are taking realactions in terms of setting ambitious and real targets for the sector.
Impact of carbon market on timber and non-timber resources under sustainable forest ecosystem management
Patrick Asante (Ministry of Forests, Government of British Columbia, Canada)
Although there is considerable interest in the potential for forests to sequester carbon in British Columbia, Canada, theimpact of carbon market on timber and non-timber resources has received relatively little attention in literature. This
paper examines the impact of a particular form of carbon market on timber and non-timber values when sustainable
forest ecosystem management is practiced. Using a forest in Northeastern British Columbia as a study area and aconstrained optimization model, the results show that the presence of co-benefits depends upon ecological parameters,
the harvest flow regulation faced by the landowner and the incentives for timber supply provided by the carbon market.
The results also show that a landowner who agrees to enter contracts for carbon sequestration will do so at the expenseof a decline in timber supply.
Keywords: Carbon Market, Non-Timber Values, Co-Benefits, Sustainable Ecosystem Management, Constraint
Optimization

5

March 16, 2024
Session 4
Optimal Reserve Site Selection of Gotjawal Forests in Jeju Island, Korea
Ara Seol (National Institute of Forest Science, Korea)
Gotjawal is a forest created on volcanic land, playing a crucial role as a biodiversity hotspot and ecologically very
important forest in Jeju Island, South Korea. About 76.5% of Gotjawal is privately owned forests, but there is aprevalent atmosphere of inadequate forest management and a tendency to develop or use it for other purposes. To
conserve Gotjawal, the Korea Forest Service and the Jeju Provincial Government have been making efforts to purchaseprivate Gotjawal forests and manage them as national forests. Fixed budgets are allocated annually, and within thelimited budgets, priority areas are purchased based on policymakers' judgment. However, there is a lack of a clear
roadmap for purchase decisions so dissatisfaction with the results of acquisitions has been raised. This study aimed toprovide an objective roadmap using optimization techniques to assist in the decision-making process for acquiring
privately owned forests in Gotjawal.
Distance Constraints to Create Green-Pathway as Environmental Concerns for Spatially Constrained Harvest
SchedulingAtsushi Yoshimoto (Institute of Statistical Mathematics, Japan)
During last few decades, harvest scheduling has drastically changed as forest ecosystem and environmental conflicts aretaken into account deeply in the management scheme. Adjacency came in 1980’s, followed by green-up, and maximum
opening size constraints. Recent challenge is creation of wildlife corridor and buffer zone for protected area within
harvesting zones, which often disjoints continuous harvesting operation. On the one side, the problem sounds nicely
stated for environmental preservation movement, but on the other side, solution searching becomes very difficult.
Distance constraint is to keep some distance among concurrent harvesting spots. By the distance constraint,
green-pathway in the harvesting zone is guaranteed to be created by harvesting activities. In this presentation, I propose
a model to solve spatially constrained harvest scheduling with distance constraint within the aggregation framework.

6

March 16, 2024
Session 5
Has Economic Growth Been Reducing Natural Disaster Damages in Vietnam?
Tetsuya Michinaka (Forestry and Forest Products Research Institute, Japan), Ehara Makoto, VU Tan Phuong,
Nguyen Thuy My Linh, Okamoto Takashi, Shimizu Katsuto, HA Van Tiep, VU Van Tuan
Natural disasters, including floods, storms, typhoons, landslides, etc., pose significant threats, causing loss of life,
injuries, and extensive damage to property, capital, and lifeline infrastructure. While existing research indicates thatdeveloping nations tend to experience more adverse effects caused by natural disasters, it remains crucial to examine thespecific impacts within a country. This study focuses on Vietnam, a nation prone to natural disasters, utilizing annual
panel data from 2010 to 2020 at the provincial level (63 cities and provinces) sourced from GSO, Vietnam and GIS.
Analyzing both natural and human factors, including elevation, Terrain Ruggedness Index (TRI), land area,
precipitation, forest coverage, plantation forest area, population density, per capita gross regional domestic product(GRDP), and agricultural GRDP, we employed various statistical models such as the Poisson model, zero-inflated
Poisson model, and Bayesian Poisson regression model to analyze the number of deaths and missing caused by natural
disasters in Vietnam.
Scatterplot analysis revealed that higher occurrences of deaths and missing persons were observed in provinces withlower per capita GRDP. In model selection, the Poisson Pseudo Maximum Likelihood (PPML) regression with
High-Dimensional Fixed Effects model yielded the best results. However, it did not confirm the mitigating role ofeconomic development indicated by per capita GRDP. Instead, agricultural GRDP was found to mitigate damages.
Higher precipitation and plantation forests were identified as contributors to damages. Other models show that TRI andland area were associated with higher damages. Surprisingly, population density was not found to be a driver ofdamages. The finding that plantation forests could not mitigate damages may be attributed to the weak protectivefunction of planted trees at lower level of age classes against disasters.
However, further exploration is required to elucidate the nuanced effects of natural disasters on socioeconomic
development in Vietnam. This research contributes to our understanding of the complex interplay between economic
factors and disaster impacts, offering valuable insights for policymakers and disaster management authorities.
Developing a Landslide Probability Model Using Similarity-Based Sampling of Absence Data: A Case Study in
Itsuki Village, Kumamoto Prefecture, Japan
Yasushi Mitsuda (University of Miyazaki, Japan)
Landslide susceptibility maps are essential for sustainable forest management. In order to produce these maps, wedeveloped a landslide probability model using time-series LiDAR data in Itsuki Village, Kumamoto Prefecture, Japan.
To model landslide probability, both landslide presence data and landslide absence data (areas where landslides did notoccur) are necessary. The quality of the landslide presence/absence sample data is crucial for developing a reliablelandslide probability model. The landslides that occurred in July 2020 were detected by comparing high-resolution
digital elevation models (DEMs) before and after the landslide hazard, derived from airborne LiDAR data. To generate
high-quality landslide absence data, a similarity-based sampling method was applied. Additionally, we generated
another landslide absence sample dataset using simple random sampling. Logistic regression analysis was conducted on
the landslide presence/absence sample datasets, using topographic factors (slope, roughness, curvature, topographic
position index, topographic relief index, standard deviation of horizontal curvature, flow accumulation, and topographic
wetness index) as explanatory variables. Our results indicate that a landslide probability model developed using adataset derived from a similarity-based sampling method had a better performance in predicting landslide occurrence
than another model using a dataset derived from simple random sampling for generating a landslide absent dataset.

7March 17, 2024
Session 6
Using social media big data to assess tourism pressure and its impact on conserved animals - Shei-Pa National
Park as an example
Chih-Lin Liu (National Chung Hsing University, Taiwan)
Taiwan's Shei-Pa National Park has magnificent mountains, diverse ecosystems and unique biodiversity. This study
aims to analyze the pressure of tourism on conserved organisms in Shei-Pa National Park. We use Flickr data, MaxEnt
biological prediction model, and geographic information system (GIS) to understand the spatial distribution of tourists
and their impact on the conserved organisms in Shei-Pa National Park. The results of the study are the predicteddistribution of 16 species of protected organisms (levels one to three), and overlay of the spatial distribution of tourists
within ten years (2008 to 2017). The analysis results of this study show that tourism pressure is in the recreation areas
and where the infrastructure is more convenient. The pressure in the areas (hotels, roads, trails) is relatively high andpose the most serious threat to conserved organisms. On the contrary, peaks with steep altitudes are difficult to reachdue to human footprints, which provides better habitat protection for most of the second-level protected animals,
including eagles. This study provides a reference for future management policy for sustainable tourism in Shei-Pa
National Park by analyzing the magnitude and distribution of tourism pressure.
Analysis of Economic Utilization on Domestic Timber of Larix kaempferi in South Korea
Hee Han (Seoul National University, Korea)
This study aimed to evaluate the economic utilization system to enhance the value addition of domestic Larix kaempferi
timber. Through simulation analysis of the milling process, this study identified the types and volumes of wood
products that could be generated from larch logs of various dimensions and evaluated the economic gains from different
application scenarios. The findings showed that the production of utility timber could multiply the total product value
by 6, and structural timber by as much as 8 times, in contrast to the production of solely temporary construction
materials. Moreover, larch logs with a diameter at breast height (DBH) of 26 cm or more were deemed appropriate forstructural timber use, though the spectrum of viable wood products shifted with the dimensions of the milled logs.
Consequently, it is crucial to classify logs during harvesting based on their future application and distribute them to theappropriate consumers to maximize the value chain of domestic timber.

8

March 17, 2024
Session 6
Spatial and temporal pattern of wildlife mortality in vehicle collisions in Nepal
Narayan Prasad Gautam (Tribhuvan University, Institute of Forestry, Nepal)
Wildlife-vehicle collision is a major conservation issue globally. In Nepal, wildlife mortality along the roads passing
through protected areas has been an emerging conservation problem where related studies are scanty. Therefore, thestudy aims to assess ecological and anthropogenic factors affecting wildlife roadkills and to understand its spatial andtemporal pattern in Banke (BaNP)-Bardia National Park (BNP) complex of Nepal. A 124 km long highway passed
through the study area, which was divided into 62 segments (2km each) for roadkill surveys where GPS points ofroadkills were recorded. Altogether, 101 instances of roadkills were observed, with birds being the most affected taxa
(41%). Besides these, five years (till 2022) of wildlife roadkill data were gathered from the park office, which revealed
331 roadkills, with Poisson regression modelling indicating higher likelihood near water holes (ßriver= 0.39, p =0.003)
and lower in areas with higher visibility (ßvisibility= -0.20, p=0.001) and human settlements (βsettlemet=-0.24,
p=0.0001) where eight candidate models were developed and compared using the AIC. The relative roadkill per km washigher in BaNP (0.14) than in BNP (0.13). One-way ANOVA showed no significant difference in season-wise roadkills
in BNP, but BaNP had significantly higher roadkills in winter. Kernel density estimation in ArcGIS was used for hotspot
identification and mapping of the risk zones. The findings suggest that hotspots should be identified and prioritized forwildlife-friendly infrastructures, and for better visibility, roadside vegetation should be managed. Further, it suggests
creating wildlife passages, speed-breakers, and warning signs in susceptible areas to mitigate roadkill.
Analysis of the Geographic and Vegetation Factors Influencing Predation Damage on Sea Turtle Eggs by Alien
Japanese Wild Boar (Sus scrofa leucomystax) on Tokashiki Island, Okinawa, Japan
Takahiro Hirai, Masashi Konoshima* (University of the Ryukyus, Japan), Takeshi Eto, Ikuo Ota
Tokashiki Island with convenient access from urban areas and blessed with rich marine resources, attracts numerous
tourists seeking recreational activities such as diving and snorkeling. The island heavily relies on a tourism industry
centered around marine resources. However, with the escape and rapid increase in the population of Japanese wildboars, which were initially introduced as livestock, various damages have become evident. Particularly in recent years,
a major concern for local tourism industry stakeholders is the predation of sea turtle eggs by wild boars because sea
turtles are highly popular marine creatures among snorkelers and divers. Identifying the locations of sea turtle egg
predation by wild boars and examining the conditions and situations that increase the likelihood of damage are crucial
tasks in considering measures to mitigate the impact. Therefore, in this study, we analyze the factors influencing egg
predation using a two-variable logistic regression model. The damage site data from on-site surveys conducted during
the 2023 nesting season were utilized along with topographical, land-use, and vegetation data. Explanatory variables
included in the regression analysis are the average slope angle around the damage site, predominant vegetation aroundthe damage site, distance from residential areas, distance from roads, distance from rivers, and depth of the sandy beach.
Results from the regression analysis revealed that the predominant vegetation surrounding the damage site and thedepth of the sandy beach significantly influence the risk of damage. Despite encountering challenges during theregression analysis, such as utilizing data from a single year's nesting season, relatively coarse geographical information,and limited explanatory variables, future endeavors should focus on collecting and accumulating more data for a morecomprehensive analysis. Nevertheless, this analysis underscores the value of information provided by such studies inestablishing spatial priorities for implementing measures to capture wild boars and protect sea turtle eggs in the future.

9March 17, 2024
Session 7
Seed Orchard Establishment in Cambodia: Experiences and Challenges
Heng Sokh (Institute of Forest and Wildlife Research and Development, Cambodia)
Amidst the alarming rates of deforestation in Cambodia, the government has undertaken a nationwide initiative toreplenish the depleted forestlands. However, this endeavor has highlighted a pressing need for adequate planting
materials to support the restoration efforts. The scarcity of high-quality germplasm for large-scale seedling production
has emerged as a significant hurdle within the forestry sector. To address this critical issue, the Institute of Forest andWildlife Research and Development (IRD) of Cambodia is spearheading the project titled "Establishment of Forest
Genetics Research Center for Restoration of Major Timber Species in Cambodia," generously funded by ASEAN-ROK
Forest Cooperation (AFoCO). This landmark project aims to execute partly a comprehensive long-term tree breedingplan, aligning with Cambodia's broader initiatives to rehabilitate degraded and deforested areas. As a starting point, theproject targets three key species: Dalbergia cochinchinensis, Pterocarpus macrocarpus, and Dipterocarpus intricatus.
During the establishment of the seed orchard, IRD conducted a series of meticulous experiments to determine the mosteffective methods for asexual propagation of the priority species, comparing cutting and grafting techniques. While P.
macrocarpus and D. cochinchinensis exhibited higher success rates, D. intricatus presented formidable challenges.
Efforts to induce root development through cutting experiments proved futile, and successful grafting proved to beelusive. Consequently, grafted seedlings were utilized for D. cochinchinensis and P. macrocarpus, while seedlings for D.
intricatus were sourced from superior plus trees. The endeavor has already borne fruit, with the seed orchard, now in its
fifth year, demonstrating promising results. Despite encountering adverse weather conditions such as strong winds andunpredictable rainfalls, the orchard has yielded moderately strong and healthy grafts. Looking ahead, the project seeks
to evaluate the viability and performance of seeds produced by grafted mother trees, including assessing seedgermination and growth in field conditions. However, several challenges persist, including the biennial fruiting patternsof certain species and the susceptibility of grafted plants to climate change-induced factors such as prolonged droughts.
Moreover, the risk of pollen contamination, particularly from naturally growing targeted tree species. Addressing thesechallenges necessitates ongoing research, collaboration, and adaptive management strategies to ensure the success ofreforestation endeavors and sustainable forest management practices in Cambodia.
Establishment of High Value Tree Species Breeding Center in Cambodia
Ma Vuthy (Institute of Forest and Wildlife Research and Development, Forestry Administration, Cambodia)
Establishment of High Value Tree Species Breeding Center in Cambodia. The project aims to conserve and develop
genetic resources of rare and endangered tree species in Cambodia while promoting green economic development inrural areas. Specific objectives include conserving and developing genetic resources through collection, propagation,and plantation of valuable tree species, enhancing the capacity and knowledge of local government staff and foresters,
promoting natural resources conservation through rural economic development via eco-forest farms, and disseminating
project experiences for sustainable management. The third year of the project focuses on constructing a high-value tree
breeding center and greenhouse, collecting valuable tree germplasm resources, producing seedlings, planting high-value
tree species, and maintaining planted trees in eco-forest farms and conservation gardens. The project has madesignificant strides in advancing tree breeding and conservation efforts in Cambodia, with major accomplishments
including the construction of the High Value Tree Species Breeding Center, the establishment of a greenhouse, and thecollection of valuable tree germplasm resources. Research and development in tissue culture for eight valuable tree
species has shown promise, despite facing budget constraints that have impacted the establishment of demonstration
high-value tree species conservation gardens and eco-forest farm projects, resulting in scaled-down planting efforts andpostponed accessory facility construction. Nonetheless, progress has been made in cultivating seedlings of precious tree
species for ex-situ conservation and cultivation across various planting sites, with a demonstration plantation of
precious tree species established to showcase sustainable land use practices. The project has also conducted domestic
training sessions for forestry officials and rural communities on various aspects of tree species management, despite
postponements of overseas training and exchange visits due to budget limitations. An eco-forest farm has been
established as a demonstration site for sustainable land use, focusing on improving livelihoods and environmental
sustainability through careful maintenance practices. Challenges faced by the project include limited funding fromsponsors and the effects of the COVID-19 pandemic, leading to delays in project activities. However, the project teamhas responded diligently to these challenges, prioritizing essential activities such as construction works, seed collection,
tree planting, and maintenance of tree plantations in Siem Reap. Despite these obstacles, the project is on track tolargely achieve its objectives, with significant progress noted in various areas. Moving forward, lessons learned fromovercoming challenges such as poor soil quality, extended germplasm collection periods, and the necessity of carefulmonitoring and technical assistance for tree plantations will be invaluable. Regular monthly meetings and field checks
have facilitated progress monitoring and issue resolution, ensuring that the project remains focused on its goals despite
obstacles. Overall, the project has demonstrated resilience and determination in the face of adversity, highlighting theimportance of flexibility and adaptability in achieving long-term conservation and sustainable land use objectives.

10March 17, 2024
Session 7
Potential improving of local livelihood relating to Non-Timber Forest Products (NTFPs) commercial utilizationin Laos: A case study in the northern part of Laos, Phieng District Xayaboury Province
Phongxiong Wanneng (Faculty of Forest Science, National University of Laos, Laos)
The specific purposes of this research are to assess the potential Non-Timber Forest Products (NTFPs) species
utilization and their contributing to local people’s income in 3 Villages, Phieng District Xayabuli Province. The survey
focused on households’ interview methods. The finding showed that in general NTFPs have generated a fairly highincome to the local people compared to other income sources in the targeted villages. On average, NTFPs sharedapproximately 8.59% of the total household’s income per year by comparing to others higher incomes in the household.
These included, such as cassava and jobs tear cultivation 61.18%, cultivation 22.06% per year accordingly. The finding
indicated that on average NTFPs contributed to the household’s income of 3,249,491 Kip/household/year. The NTFPs
species that generated the highest income to the local people are red vine (khuedengdang) following by sugar palm
(Maktao), rattan shoots, broom grass flower, wild teas and wild ginger. The results showed that NTFPs promotion interms of marketing and products adding value in processing in the targeted villages are still limited. The price and value
adding to NTFPs species are still low. The marketing chain for NTFPs are still limited. The trading chains in the site aremainly limited within Phieng District and Xayabuli Province. Very few NTFPs are sold in others provinces such as
Vientiane Province. There is only sugar palm (Maktao) products are exported to sell in Vientiane Province. However,
the amount of product trading is small. The resources of Non-Timber Forest Products in the targeted villages are
currently reported in decreasing compared to the previous years due to the change of forest land to agricultural land use
and other factors. It highly recommended that the local people and related government agencies should increase NTFPs
supporting and promoting in the future. The supporting methods can be included NTFPs natural assisted management
and plantation in the suitable sites of villages such as protected forest and village forest areas. However, the supporting
program should select only some NTFPs species that have high potential within the village in terms of income andresources generations, for example, sugar palm, wild teas and vine red. These three species have well grown under the
shade of trees, which are the best NTFPs species to promote for natural management and plantation under forest shade.
The species should be promoted plantation in the Nam Phi national protected area (NPA) where is near at the target
villages. In addition, these species will benefit the local people in many ways such as food, generate income and as wellas will be an important factor in protecting the forest areas. The finding also revealed that the local people are stilllacking knowledge and information relating to NTFPs management, plantation, harvesting techniques and products
processing. Therefore, the government agencies should provide these kinds of capacity building skills to the local
people. There is also a conflict buying NTFPs in the site between traders who are registered and some people who are
not registered. For NTFPs marketing promotion in the site, the project and government agencies should build a shop or
point of sale (booth) along the main road (Vientiane-Xayabuli) where is located somewhere in the targeted villages.
This sale point should be a nice view and large area for car parking and rest, and also for passengers to drink the wild
tea. This wild tea can be promoted as a unique product to Phieng District, Xayabuli Province. This booth can also be
used to sell other types of NTFPs.

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March 17, 2024
Session 8
Estimation tree growth from bitemporal LiDAR data: A case study in the Bohemian Switzerland National Park
Zlatica Melichová (Czech University of Life Sciences Prague, Czech Republic)
The acquisition of forest data using light detection and ranging technology (LiDAR) is currently one of the leading
methods in forest mensuration. LiDAR is able to be deployed also in worse light conditions and can even be acquired
during night flights, allowing the utilization of airspace when the traffic is lower. The laser beams are able to penetrate
canopy even in relatively closed canopies, and so provide detailed information about the ground. The groundinformation is essential for the height estimation and also other LiDAR metrics. Thanks to the modern precise GPS
mensuration the global coordinates of the surface points are also measured with centimeter accuracy. So repeated scans
can reveal the increments in the same position and can be helpful for estimating the growth of individual trees andforest stands. In remote sensing two principal methods are used to model the forest parameters. Individual tree
approaches, where the aim is to find individual trees and derive the information about each tree separately, andarea-based approaches known as ABA, where a given area is evaluated for its parameters and structural characteristics
of lidar data (metrics) and correlated with forest stand. In this work we present findings about the estimation of growthusing second mentioned approach on unmanaged territory of national part, e.g. forest without any intervention and apossibility of using such bitemporal data for growth estimates. The result indicates that growth curve parameters can besatisfactorily derived from bitemporal Lidar data.
Keywords: LiDAR, airborne laser scanning, area-based approach
Remote sensing-based monitoring of natural disturbances in forest ecosystem using modern high-tech data
Tereza Hüttnerová (Czech University of Life Sciences Prague, Czech Republic)
In recent decades, forest ecosystems have been increasingly affected by natural disturbances, including insect pests,
wind through events, and forest fires. A very effective method of mapping or detection is remote-sensing images. In thecase of recorded stress in the forest stand, in most cases, there is a change in the spectral reflectance of the vegetation;these changes can be detected based on, for example, multispectral images or hyperspectral images. In some cases, thestressed tree can remain spectrally healthy; in these cases, it is impossible to detect the degradation of the forest cover at
an early stage based on optical data. A potential stress detection method could be chemical measurement (satellite data
Sentinel-5P, electronic nose measurement, or conventional chemical detection methods). We verified the possibility ofusing chemical data for data-driven natural disturbance maps. We experimented with the 2022 summer forest fire in the
Bohemia Switzerland National Park, where around 1,000 ha were disturbed. For data validation, we collected field dataon the intensity and location of fire spread. We aimed to find a correlation between the measured chemical data and theburning intensity in the park. Our results promise the suitability of this methodology for mapping stress factors in theforest ecosystem and lead to a more extensive study with diversifying other types of natural disturbances.
Keywords: chemical mapping, natural disturbances, forest fire, satellite data, early detection.

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March 17, 2024
Session 8
Applications of AI in forest management. Examples and opinions
Peter Surový (Czech University of Life Sciences Prague, Czech Republic)
Models for artificial intelligence has gained a lot of attention in last years. AI has become a powerful tool in many
aspects of human life, and many new innovations are emerging. In forestry one of the most obvious examples ofapplication of AI is in data acquisition, especially in remote sensed materials, where AI is deployed in image analysis,
namely classification and more recently object detection and segmentation. In the first part of the presentation we will
demonstrate application of two AI models YOLO and Detectron2 for detection of dead trees in aerial remote sensed
imagery, and discuss their advantages and disadvantages. Both models perform relatively well achieving the AP50
accuracy of 60 to 80 percent. The individual models perform differently on different datasets however overall accuracy
is generally better in images with less objects (with less dead trees per hectare). In second part of the presentation wewill present current status of other models emerging from computer research, especially in generative AI research field
as image and video or moving image creation and their hypothetical application in forest management. Finally, wellknown phenomena of large language models (LLM) is going to be presented and described the bases and functionalities.
We will focus on transfer learning of the open source models (including lower versions of ChatGPT) and its potential
applications in forest management, discussing the potential of this technology together with the cost associated with
their utilization.
Selection of time varying Height-Diameter curves
Tetsuji Tonda (Prefectural University of Hiroshima, Japan)
Height-Diameter curve is a function that defines the relationship between diameter at breast height and tree height. It is
the mean trend on a scatter plot of tree height against diameter at breast height for measurements on individual tree
growth. Introducing varying coefficients into the Height-Diameter curves, we construct the statistical models to estimate
the temporal trend of Height-Diameter curves with aging. To select an appropriate model among multiple candidates,
we apply the Cross-Validation (CV) criterion. In particular, the n-hold CV criterion is adopted for the purposes offorecasting the temporal trend. We demonstrate the results for analyzing real data of Sugi (Cryptomeria japonica) stands
in even aged plantation forest in Japan by preparing five candidate models.

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