Use of Smartphone Technology for Small-Scale Silviculture: A Test of Low-Cost Technology in Eastern Ontario

Kennedy, Richard R.; McLeman, Robert; Sawada, M.; Smigielski, Jan

doi:10.1007/s11842-013-9243-5

Cited by 11 publications

(8 citation statements)

References 12 publications

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“…Considering the above, another important aspect to be underlined is the possibility of using these technologies in small-scale forestry, though with rather lower level of accuracy. A feasible example of this could be smartphone use for improving forest utilization [52]. Smartphones are able to act as low-cost GNSS receivers, also under forest canopy cover, with sufficient precision, i.e., about 9 m of accuracy, which should be sufficient for small-scale forestry use [52,53].…”

Section: Discussionmentioning

confidence: 99%

Applications of GIS-Based Software to Improve the Sustainability of a Forwarding Operation in Central Italy

et al. 2020

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Reducing potential soil damage due to the passing of forest machinery is a key issue in sustainable forest management. Limiting soil compaction has a significant positive impact on forest soil. With this in mind, the aim of this work was the application of precision forestry tools, namely the Global Navigation Satellite System (GNSS) and Geographic Information System (GIS), to improve forwarding operations in hilly areas, thereby reducing the soil surface impacted. Three different forest study areas located on the slopes of Mount Amiata (Tuscany, Italy) were analyzed. Extraction operations were carried out using a John Deere 1410D forwarder. The study was conducted in chestnut (Castanea sativa Mill.) coppice, and two coniferous stands: black pine (Pinus nigra Arn.) and Monterey pine (Pinus radiata D. Don). The first stage of this work consisted of field surveys collecting data concerning new strip roads prepared by the forwarder operator to extract all the wood material from the forest areas. These new strip roads were detected using a GNSS system: specifically, a Trimble Juno Sb handheld data collector. The accumulated field data were recorded in GIS Software Quantum GIS 2.18, allowing the creation of strip road shapefiles followed by a calculation of the soil surface impacted during the extraction operation. In the second phase, various GIS tools were used to define a preliminary strip road network, developed to minimize impact on the surface, and, therefore, environmental disturbance. The results obtained showed the efficiency of precision forestry tools to improve forwarding operations. This electronic component, integrated with the on-board GNSS and GIS systems of the forwarder, could assure that the machine only followed the previously-planned strip roads, leading to a considerable reduction of the soil compaction and topsoil disturbances. The use of such tool can also minimize the risks of accidents in hilly areas operations, thus allowing more sustainable forest operations under all the three pillars of sustainability (economy, environment and society).

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Section: Discussionmentioning

confidence: 99%

Applications of GIS-Based Software to Improve the Sustainability of a Forwarding Operation in Central Italy

et al. 2020

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“…While the dedicated GNSS devices described in the previous section were ubiquitous in natural resources until recent years, positioning via the GNSS chip present in most modern mobile devices and tablets is now increasingly common [55][56][57]. Mobile-based apps such as Avenza Maps ® store georeferenced, custom maps in GeoTIFF or GeoPDF format on mobile devices, allowing users to view positions on a smartphone or tablet rather than on a conventional, dedicated GNSS unit [58,59].…”

Section: Gnss-smartphone and Tablet-based Mappingmentioning

confidence: 99%

Positioning Methods and the Use of Location and Activity Data in Forests

Keefe

Wempe

Becker

et al. 2019

Forests

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In this paper, we provide an overview of positioning systems for moving resources in forest and fire management and review the related literature. Emphasis is placed on the accuracy and range of different localization and location-sharing methods, particularly in forested environments and in the absence of conventional cellular or internet connectivity. We then conduct a second review of literature and concepts related to several emerging, broad themes in data science, including the terms location-based services (LBS), geofences, wearable technology, activity recognition, mesh networking, the Internet of Things (IoT), and big data. Our objective in this second review is to inform how these broader concepts, with implications for networking and analytics, may help to advance natural resource management and science in the future. Based on methods, themes, and concepts that arose in our systematic reviews, we then augmented the paper with additional literature from wildlife and fisheries management, as well as concepts from video object detection, relative positioning, and inventory-tracking that are also used as forms of localization. Based on our reviews of positioning technologies and emerging data science themes, we present a hierarchical model for collecting and sharing data in forest and fire management, and more broadly in the field of natural resources. The model reflects tradeoffs in range and bandwidth when recording, processing, and communicating large quantities of data in time and space to support resource management, science, and public safety in remote areas. In the hierarchical approach, wearable devices and other sensors typically transmit data at short distances using Bluetooth, Bluetooth Low Energy (BLE), or ANT wireless, and smartphones and tablets serve as intermediate data collection and processing hubs for information that can be subsequently transmitted using radio networking systems or satellite communication. Data with greater spatial and temporal complexity is typically processed incrementally at lower tiers, then fused and summarized at higher levels of incident command or resource management. Lastly, we outline several priority areas for future research to advance big data analytics in natural resources.

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“…The results of this study show that the ground measurement tool can provide effective assistance for forest GIS surveys, especially when undertaking accurate surveys of artificial forests in small areas. In the measurement of tree position, the RMSEs of the two plots are 0.222 m and 0.229 m. When using mobile GIS to perform collection works, references [3,7,11,19,41] rely on only mobile phone to locate the position, and the RMSE of the position is between 5 m and 8 m. Compared with the traditional method, the method presented in this paper shows the advantages of high precision and high integration. References [10,42,43] use devices such as those employed in traditional GPS or RTK, and cannot directly transmit positioning data to a mobile GIS system.…”

Section: Discussionmentioning

confidence: 99%

Development and Testing of a New Ground Measurement Tool to Assist in Forest GIS Surveys

Fan

Chen

et al. 2019

Forests

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In present forest surveys, some problems occur because of the cost and time required when using external tools to acquire tree measurement. Therefore, it is of great importance to develop a new cost-saving and time-saving ground measurement method implemented in a forest geographic information system (GIS) survey. To obtain a better solution, this paper presents the design and implementation of a new ground measurement tool in which mobile devices play a very important role. Based on terrestrial photogrammetry, location-based services (LBS), and computer vision, the tool assists forest GIS surveys in obtaining important forest structure factors such as tree position, diameter at breast height (DBH), tree height, and tree species. This paper selected two plots to verify the accuracy of the ground measurement tool. Experiments show that the root mean square error (RMSE) of the position coordinates of the trees was 0.222 m and 0.229 m, respectively, and the relative root mean square error (rRMSE) was close to 0. The rRMSE of the DBH measurement was 10.17% and 13.38%, and the relative Bias (rBias) of the DBH measurement was −0.88% and −2.41%. The rRMSE of tree height measurement was 6.74% and 6.69%, and the rBias of tree height measurement was −1.69% and −1.27%, which conforms to the forest investigation requirements. In addition, workers usually make visual observations of trees and then combine their personal knowledge or experience to identify tree species, which may lead to the situations when they cannot distinguish tree species due to insufficient knowledge or experience. Based on MobileNets, a lightweight convolutional neural network designed for mobile phone, a model was trained to assist workers in identifying tree species. The dataset was collected from some forest parks in Beijing. The accuracy of the tree species recognition model was 94.02% on a test dataset and 93.21% on a test dataset in the mobile phone. This provides an effective reference for workers to identify tree species and can assist in artificial identification of tree species. Experiments show that this solution using the ground measurement tool saves time and cost for forest resources GIS surveys.

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Use of Smartphone Technology for Small-Scale Silviculture: A Test of Low-Cost Technology in Eastern Ontario

Cited by 11 publications

References 12 publications

Applications of GIS-Based Software to Improve the Sustainability of a Forwarding Operation in Central Italy

Applications of GIS-Based Software to Improve the Sustainability of a Forwarding Operation in Central Italy

Positioning Methods and the Use of Location and Activity Data in Forests

Development and Testing of a New Ground Measurement Tool to Assist in Forest GIS Surveys

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