Monitoring diseases of chestnut stands by small format aerial photography

Ambrosini, I.; Gherardi, Lodovico; Viti, Maria Laura; Maresi, G.; Turchetti, T.

doi:10.1080/10106049709354595

Cited by 13 publications

(8 citation statements)

References 4 publications

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“…Previous studies (Ambrosini et al 1997;Martins et al 2001) have shown that the evaluation of damage caused by soil-borne P. cinnamomi using SFAP did not present significantly different results from those obtained by field observations. Colour near-infrared images (CIR) or visible normal colour images (NC) obtained with 35 mm or 70 mm cameras have also been used in similar forestry pathology studies for many years (Meyer 1982;Bissegger and Heiniger 1994;Warner et al 1996).…”

Section: Introductioncontrasting

confidence: 69%

Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods

et al. 2007

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Chestnut ink disease, caused by Phytophthora cinnamomi and P. cambivora, is responsible for important economic losses and limits the establishment of new chestnut (Castanea sativa) groves in Portugal. Although the differences in soil properties and in cropping practices affect ink severity, the regional spread of disease is not known. Data for monitoring C. sativa decline were obtained by using field surveys and Small Format Aerial Photography (SFAP), a reliable tool which provides large-scale imagery obtained at low altitude. Visible colour and near-infrared images were obtained with different cameras with an average ground resolution of 22, 14 and 39 cm. The spatial distribution of ink disease in northern Portugal for the years 1995-2004 was estimated through a geostatistical method, and the estimation of precision was determined. From 1995-2002, the chestnut population in the study area increased by 18.5% due to new orchard plantations. After 2002 the population decreased because the new plantations were not sufficient to recover the number of dead chestnut trees, killed mostly by ink disease. The directional semivariograms indicated anisotropy with a greater disease spread in the NE-SW direction. This direction corresponds to site areas at the same altitude, where soil tillage and human mobility are higher.

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Section: Introductioncontrasting

confidence: 69%

Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods

et al. 2007

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“…As the beetle infestation can be detected physically from a transparent crown with few foliage on surviving branches, accompanied by a decrease in infrared reflectance of leaves caused by stress conditions [2,3] these characteristics can be identified using CIR-imagery [46][47][48].…”

Section: Discussionmentioning

confidence: 99%

Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels

Lehmann

Nieberding

Prinz

et al. 2015

Forests

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Abstract:The detection of pest infestation is an important aspect of forest management. In the case of the oak splendour beetle (Agrilus biguttatus) infestation, the affected oaks (Quercus sp.) show high levels of defoliation and altered canopy reflection signature. These critical features can be identified in high-resolution colour infrared (CIR) images of the tree crown and branches level captured by Unmanned Aerial Systems (UAS). In this study, we used a small UAS equipped with a compact digital camera which has been calibrated and modified to record not only the visual but also the near infrared reflection (NIR) of possibly infested oaks. The flight campaigns were realized in August 2013, covering two study sites which are located in a rural area in western Germany. Both locations represent small-scale, privately managed commercial forests in which oaks are economically valuable species. Our workflow includes the CIR/NIR image acquisition, mosaicking, georeferencing and pixel-based image enhancement followed by object-based image classification techniques. A modified Normalized Difference Vegetation Index (NDVImod) derived classification was used to distinguish between five vegetation health classes, i.e., infested, healthy or dead branches, other vegetation and canopy gaps. We achieved an overall Kappa Index of Agreement (KIA) OPEN ACCESSForests 2015, 6 595 of 0.81 and 0.77 for each study site, respectively. This approach offers a low-cost alternative to private forest owners who pursue a sustainable management strategy.

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“…[72], two decades after its first detection in Portugal, hypovirulence began to be observed in some locations. Many of the sub-populations of C. parasitica belong to the well characterized and specific vegetative compatibility type EU-11 -in spite of having a spectral response that can be similar to other chestnut disorders caused by, for example, abiotic factors, inadequate pruning practice, or insect defoliation-that appears only in some orchards in Italy [73]. Successful treatment depends on the way the fungus population propagates in the area of interest.…”

Section: Chestnut Health Monitoringmentioning

confidence: 99%

Multi-Temporal Analysis of Forestry and Coastal Environments Using UASs

et al. 2017

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Due to strong improvements and developments achieved in the last decade, it is clear that applied research using remote sensing technology such as unmanned aerial vehicles (UAVs) can provide a flexible, efficient, non-destructive, and non-invasive means of acquiring geoscientific data, especially aerial imagery. Simultaneously, there has been an exponential increase in the development of sensors and instruments that can be installed in UAV platforms. By combining the aforementioned factors, unmanned aerial system (UAS) setups composed of UAVs, sensors, and ground control stations, have been increasingly used for remote sensing applications, with growing potential and abilities. This paper's overall goal is to identify advantages and challenges related to the use of UAVs for aerial imagery acquisition in forestry and coastal environments for preservation/prevention contexts. Moreover, the importance of monitoring these environments over time will be demonstrated. To achieve these goals, two case studies using UASs were conducted. The first focuses on phytosanitary problem detection and monitoring of chestnut tree health (Padrela region, Valpaços, Portugal). The acquired high-resolution imagery allowed for the identification of tree canopy cover decline by means of multi-temporal analysis. The second case study enabled the rigorous and non-evasive registry process of topographic changes that occurred in the sandspit of Cabedelo (Douro estuary, Porto, Portugal) in different time periods. The obtained results allow us to conclude that the UAS constitutes a low-cost, rigorous, and fairly autonomous form of remote sensing technology, capable of covering large geographical areas and acquiring high precision data to aid decision support systems in forestry preservation and coastal monitoring applications. Its swift evolution makes it a potential big player in remote sensing technologies today and in the near future.

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Monitoring diseases of chestnut stands by small format aerial photography

Cited by 13 publications

References 4 publications

Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods

Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods

Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels

Multi-Temporal Analysis of Forestry and Coastal Environments Using UASs

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