Development of Software to Measure Tree Heights on the Smartphone.

Itoh, Takuya; Eizawa, Junji; Yano, Nobukazu; Matsue, Keigo; Naito, Kenji

doi:10.4005/jjfs.92.221

Cited by 8 publications

(8 citation statements)

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“…Itoh et al (2010) uses an iPhone and calculates a Root Mean Square Error of 0.7 m for measurements of 10 m in height from a distance of 20 m. In the present study the value for Root Mean Square Error obtained for the same variables is 0.63 for Note and 0.86 for Desire (without calibration), very similar to the above.…”

Section: Discussionsupporting

confidence: 73%

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Measurement errors in the use of smartphones as low-cost forestry hypsometers

Villasante¹,

Fernandez²

2014

Silva Fenn.

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Measurement errors in the use of smartphones as lowcost forestry hypsometersVillasante A., Fernandez C. (2014). Measurement errors in the use of smartphones as low-cost forestry hypsometers. Silva Fennica vol. 48 no. 5 article id 1114. 11 p. Highlights• We analysed two smartphones (HTC Desire and Samsung Galaxy Note) to determine the errors in the height measurements.• The calibration included with the Android applications is insufficient.• After appropriate calibration, the smartphone errors are similar to other forest hypsometers (Blume Leiss and Vertex). AbstractVarious applications currently available for Android allow the estimation of tree heights by using the 3D accelerometer on smartphones. Some make the estimation using the image on the screen, while in others, by pointing with the edges of the terminal. The present study establishes the measurement errors obtained with HTC Desire and Samsung Galaxy Note compared to those from Blume Leiss and Vertex IV. Six series of 12 measurements each were made with each hypsometer (for heights of 6 m, 8 m, 10 m and 12 m). A Kruskall Wallis test is applied to the relative errors to determine whether there are significant differences between the devices. The results indicate that the errors of the uncalibrated smartphones significantly exceed those of traditional forestry apparatus. However, calibration is a very easy procedure that can be done by means of a linear regression line between real angles (obtained with a Digital Angle Finder or with a series of measurements taken independently of the experiment), and the angles of the accelerometer. With this adjustment, the smartphones achieve adequate quality levels although the bias was not totally eliminated. The relative errors when pointing with the edges of the terminal show no significant differences compared to Blume Leiss. Applications that use the screen image give better results (no significant differences were detected with Vertex). There is currently no application that offers calibration of the linear regression slope, which is an essential requirement for ensuring the accuracy of height measurements obtained with smartphones.

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Section: Discussionsupporting

confidence: 73%

“…Itoh et al (2010) analysed the accuracy of the iPhone by comparing the heights obtained with TruPulse 200 with the heights obtained with a laser telemeter. In this case the application used is based on the rotation of the Z axis when aiming with the upper edge of the iPhone.…”

Section: Introductionmentioning

confidence: 99%

Measurement errors in the use of smartphones as low-cost forestry hypsometers

Villasante¹,

Fernandez²

2014

Silva Fenn.

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“…According to current experimental data and analytical results, the LAISmart method can produce acceptable coniferous forest LAI, and it may be a promising prospective for forest management to reduce intensive field labor and to improve the working efficiency. Furthermore, by combining the camera and gyro of the smartphone, besides LAI, more interested parameters e.g., canopy height, stand basal area, and stand volume can be calculated through the method of photogrammetry [46]. When connected to the internet cloud server as stated by the concept of smart forest [47], the smartphone method may highly facilitate the data collecting in the forest survey application.…”

Section: Discussionmentioning

confidence: 99%

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

Qu¹,

Wang²,

Song³

et al. 2017

Forests

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Forest leaf area index (LAI) is a key characteristic affecting a field canopy microclimate. In addition to traditional professional measuring instruments, smartphone-based methods have been used to measure forest LAI. However, when smartphone methods were used to measure conifer forest LAI, very different performances were obtained depending on whether the smartphone was held at the zenith angle or at a 57.5 • angle. To further validate the potential of smartphone sensors for measuring conifer LAI and to find the limits of this method, this paper reports the results of a comparison of two smartphone methods with an LAI-2000 instrument. It is shown that the method with the smartphone oriented vertically upwards always produced better consistency in magnitude with LAI-2000. The bias of the LAI between the smartphone method and the LAI-2000 instrument was explained with regards to four aspects that can affect LAI: gap fraction; leaf projection ratio; sensor field of view (FOV); and viewing zenith angle (VZA). It was concluded that large FOV and large VZA cause the 57.5 • method to overestimate the gap fraction and hence underestimate conifer LAI. For the vertically upward method, the bias caused by the overestimated gap fraction is compensated for by an underestimated leaf projection ratio.

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“…For example, "Smart Measure" and "Measure Height" are used to measure tree height to make field determination easy, fast, and accurate (Bijak and Sarzyński 2015). Itoh et al (2010) developed an iPhone app to measure tree height using an accelerometer function. A number of studies examined the accuracy of other built-in smartphone functions used in apps of GeoTrees, Smart tools, and Trestima.…”

Section: Introductionmentioning

confidence: 99%

An Exploratory Study of Smartphone and Smartphone Application Use in the U.S. Forest Products Industry

2017

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This work conducted market research on the use of smartphones and smartphone applications (apps) in the forest products industry and academia. Scholarly literature was reviewed, and related apps were considered. An online survey was conducted to collect data adopting a convenience sampling method. Participants were individuals who work with wood or wood-based products. The sample was compiled from publicly available online and offline sources. A questionnaire was specifically developed for this study. Out of 1,221 email invitations, 311 responses were returned at the response rate of 27.2%. Descriptive statistics and analysis of variance were used for analysis. Nearly all of the respondents (95.7%) had smartphones, and over half of them were iOS users (52.3%). A higher personal use, as compared to work use, of smartphone apps was observed. Respondents of Millennials and Generation X indicated higher personal app use than Baby Boomers. Academia and research users showed higher app uses. More respondents had purchased paid apps (45.2%) than in-app services on free apps (28.5%). This finding indicates that paid apps may be of more interest to respondents than in-app purchases.

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Development of Software to Measure Tree Heights on the Smartphone.

Cited by 8 publications

References 0 publications

Measurement errors in the use of smartphones as low-cost forestry hypsometers

Measurement errors in the use of smartphones as low-cost forestry hypsometers

Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method

An Exploratory Study of Smartphone and Smartphone Application Use in the U.S. Forest Products Industry

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