Cost-plus-loss analyses of forest inventory strategies based on kNN-assigned reference sample plot data

Holmström, Hampus; Kallur, Hans; Ståhl, Göran

doi:10.14214/sf.496

Cited by 55 publications

(63 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Real observed errors have been used, for example, by Eid et al (2004), Duvemo et al (2007), Juntunen (2006), Väisänen (2008) and simulated errors by Eid (2000), Holmström et al (2003), Holopainen & Talvitie (2006), Borders et al (2008), Islam et al (2009). One of the strengths of the case-study approach is that the observed errors are realistic and can be used as such.…”

Section: Analysing the Uncertaintymentioning

confidence: 99%

Uncertainty in forest simulators and forest planning systems

Mäkinen¹

2010

Diss. For.

View full text Add to dashboard Cite

The forest simulator is a computerized model for predicting forest growth and future development as well as effects of forest harvests and treatments. The forest planning system is a decision support tool, usually including a forest simulator and an optimisation model, for finding the optimal forest management actions.The information produced by forest simulators and forest planning systems is used for various analytical purposes and in support of decision making. However, the quality and reliability of this information can often be questioned. Natural variation in forest growth and estimation errors in forest inventory, among other things, cause uncertainty in predictions of forest growth and development. This uncertainty stemming from different sources has various undesirable effects. In many cases outcomes of decisions based on uncertain information are something else than desired.The objective of this thesis was to study various sources of uncertainty and their effects in forest simulators and forest planning systems. The study focused on three notable sources of uncertainty: errors in forest growth predictions, errors in forest inventory data, and stochastic fluctuation of timber assortment prices. Effects of uncertainty were studied using two types of forest growth models, individual tree-level models and stand-level models, and with various error simulation methods. New method for simulating more realistic forest inventory errors was introduced and tested. Also, three notable sources of uncertainty were combined and their joint effects on stand-level net present value estimates were simulated.According to the results, the various sources of uncertainty can have distinct effects in different forest growth simulators. The new forest inventory error simulation method proved to produce more realistic errors. The analysis on the joint effects of various sources of uncertainty provided interesting knowledge about uncertainty in forest simulators. Metsäsimulaattori on tietokoneistettu malli, jolla ennustetaan metsän kasvua ja tulevaa kehitystä, sekä hakkuiden ja käsittelyiden vaikutuksia metsiin. Metsäsuunnittelujärjestelmä on päätöstukijärjestelmä, joka yleisesti koostuu metsäsimulaattorista ja optimointimallista ja jonka avulla metsien käsittelyitä voidaan optimoida.Metsäsimulaattoreilla ja metsäsuunnittelujärjestelmillä tuotettua tietoa käytetään monenlaisiin analyyseihin sekä metsien käyttöä koskevan päätöksenteon perustaksi. Tiedon laatu ja luotettavuus on kuitenkin usein kyseenalaista. Esimerkiksi metsien kasvun luontainen vaihtelu sekä virheet metsien nykytilaa koskevissa tiedoissa aiheuttavat metsien tulevan kehityksen ennusteissa epävarmuutta. Epävarmuudella, tai tiedon puutteella on monia epäedullisia seurauksia. Epävarmalle tiedolle perustuvat päätökset johtavat usein ei-toivottuun lopputulokseen.Tämän väitöskirjan tarkoituksen oli tarkastella erilaisia epävarmuuden lähteitä sekä niiden vaikutuksia metsäsimulaattoreissa ja metsäsuunnittelujärjestelmissä. Tutkimuksessa tarkasteltiin pääasiassa kolmea m...

show abstract

Section: Analysing the Uncertaintymentioning

confidence: 99%

Uncertainty in forest simulators and forest planning systems

Mäkinen¹

2010

Diss. For.

View full text Add to dashboard Cite

show abstract

“…Most of the applications of CPL in forestry have dealt with defining the expected losses from a given data acquisition method, such as sampling-based forest inventory, traditional visual forest inventory, photo interpretation-based forest inventory, and ALS-based forest inventory (Holmström et al 2003;Eid et al 2004;Mäkinen et al 2010;Borders et al 2010). In some of the analyses, also other sources of error, such as error in the estimation of diameter distributions has been included (Bergseng et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…In most cases, analysis has been carried out by assuming that the utility of the decision maker only consists of the net present value (NPV) of the decision without any area-level constraints, such as even-flow or end inventory constraints. The time horizon has varied from 10 years (Holmström et al 2003) to 100 years (Eid et al 2004) and the interest rate from 2% to 4%. The calculations have been carried out with local planning systems, with either stand-level or single-tree level growth models.…”

Section: Introductionmentioning

confidence: 99%

Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making

Kangas¹,

Gobakken²,

Puliti³

et al. 2018

Silva Fenn.

View full text Add to dashboard Cite

Highlights• Airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) are nearly equally valuable for harvest scheduling decisions even though ALS data is more precise.• Large underestimates of stand volume are most dangerous errors for forest owner because of missed cutting probabilities.• Relative RMSE of stand volume and the mean volume in a test area explain 77% of the variation between the expected losses due to errors in the data in the published studies.• Increasing the relative RMSE of volume by 1 unit, increased the losses in average by 4.4 € ha -1 . AbstractAirborne laser scanning (ALS) has been the main method for acquiring data for forest management planning in Finland and Norway in the last decade. Recently, digital aerial photogrammetry (DAP) has provided an interesting alternative, as the accuracy of stand-based estimates has been quite close to that of ALS while the costs are markedly smaller. Thus, it is important to know if the better accuracy of ALS is worth the higher costs for forest owners. In many recent studies, the value of forest inventory information in the harvest scheduling has been examined, for instance through cost-plus-loss analysis. Cost-plus-loss means that the quality of the data is accounted for in monetary terms through calculating the losses due to errors in the data in the forest management planning context. These costs are added to the inventory costs. In the current study, we compared the losses of ALS and DAP at plot level. According to the results, the data produced using DAP are as good as data produced using ALS from a decision making point of view, even though ALS is slightly more accurate. ALS is better than DAP only if the data will be used for more than 15 years before acquiring new data, and even then the difference is quite small. Thus, the increased errors in DAP do not significantly affect the results from a decision making point of view, and ALS and DAP data can be equally well recommended to the forest owners for management planning. The decision of which data to acquire, can thus be made based on the availability of the data on first hand and the costs of acquiring it on the second hand.

show abstract

“…The latter is measured using simple tools, such as calliper and measuring tape. As these conventional field measurement techniques are expensive and labor-intensive [10,11], more cost-effective, automated techniques are needed. Even though the DBH is currently the most important attribute measured in ground surveys, it would be beneficial to measure the stem curve, or at least a part of it, as the stem curve actually defines the 3D geometry of the tree trunk.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Google Tango and Kinect for Crowdsourcing Forestry Information

Hyyppä

Virtanen

Jaakkola

et al. 2017

Forests

View full text Add to dashboard Cite

Abstract:In this paper, we demonstrate the feasibility of using the Microsoft Kinect and Google Tango frame-based depth sensors for individual tree stem measurements and reconstruction for the purpose of forest inventory. Conventionally field reference data in forest inventory are collected at tree and sample plot level by means of manual measurements (e.g., a caliper), which are both labor-intensive and time-consuming. In this study, color (i.e., red, green and blue channels, RGB) and range images acquired by a Kinect and Tango systems were processed and used to extract tree diameter measurements for the individual tree stems. For this, 121 reference stem diameter measurements were made with tape and caliper. Kinect-derived tree diameters agreed with tape measurements to a 1.90 cm root-mean-square error (RMSE). The stem curve from the ground to the diameter at breast height agreed with a bias of 0.7 cm and random error of 0.8 cm with respect to the reference trunk. For Tango measurements, the obtained stem diameters matched those from tape measurement with an RMSE of 0.73 cm, having an average bias of 0.3 cm. As highly portable and inexpensive systems, both Kinect and Tango provide an easy way to collect tree stem diameter and stem curve information vital to forest inventory. These inexpensive instruments may in future compete with both terrestrial and mobile laser scanning or conventional fieldwork using calipers or tape. Accuracy is adequate for practical applications in forestry. Measurements made using Kinect and Tango type systems could also be applied in crowdsourcing context.

show abstract

Cost-plus-loss analyses of forest inventory strategies based on kNN-assigned reference sample plot data

Cited by 55 publications

References 23 publications

Uncertainty in forest simulators and forest planning systems

Uncertainty in forest simulators and forest planning systems

Value of airborne laser scanning and digital aerial photogrammetry data in forest decision making

Feasibility of Google Tango and Kinect for Crowdsourcing Forestry Information

Contact Info

Product

Resources

About