Remotely Sensed Vegetation Indices to Discriminate Field-Grown Olive Cultivars

Avola, Giovanni; Gennaro, Salvatore Filippo Di; Cantini, Claudio; Riggi, Ezio; Muratore, Francesco; Tornambè, C.; Matese, Alessandro

doi:10.3390/rs11101242

Cited by 44 publications

(23 citation statements)

References 34 publications

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“…As multispectral and thermal cameras become increasingly available for UAV-based photography (Casana et al 2017; McLeester et al 2018), these data are likely to become more common. UAVs are already successfully used for high-resolution mapping of agricultural fields and precise analyses that can differentiate crop varieties (Avola et al 2019), promising exciting potential for more complex land-cover mapping in the future. However, the fairly short flight times of UAVs and the time necessary to create high-resolution orthophotos prevented us from using them to map every survey unit.…”

Section: Discussionmentioning

confidence: 99%

Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

Plekhov

Gosner

Smith

et al. 2020

Adv. archaeol. pract.

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Satellite imagery has long been recognized as well suited for the regional and ecological questions of many archaeological surveys. One underexplored aspect of such data is their temporal resolution. It is now possible for areas to be imaged on an almost daily basis, and this resolution offers new opportunities for studying landscapes through remote sensing in parallel with ground-based survey. This article explores the applications of these data for visibility assessment and land-cover change detection in the context of the Sinis Archaeological Project, a regional archaeological survey of west-central Sardinia. We employ imagery provided by Planet, which has a spatial resolution of 3 m, in four spectral bands, and is collected daily. Using Normalized Difference Vegetation Index (NDVI) values calculated for each survey unit, we find that there is a relationship between NDVI values and field-reported visibility in general, though the strength of this correlation differs according to land-cover classes. We also find the data to be effective at tracking short-term changes in field conditions that allow us to differentiate fields of similar land cover and visibility. We consider limitations and potentials of these data and encourage further experimentation and development.

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Section: Discussionmentioning

confidence: 99%

Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

Plekhov

Gosner

Smith

et al. 2020

Adv. archaeol. pract.

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“…The combination of multi-satellite an These findings support our hypothesis that remote sensing data could be used to identify olive cultivars. Unmanned aerial vehicle (UAV) imagery was used by Avola et al [95] to distinguish two olive scions using vegetation indexes. Images obtained by UAV were also used by Kyratzis et al [96] for durum wheat phenotyping in Mediterranean drylands.…”

Section: Discussionmentioning

confidence: 99%

Hyperspectral Reflectance as a Basis to Discriminate Olive Varieties—A Tool for Sustainable Crop Management

et al. 2020

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Worldwide sustainable development is threatened by current agricultural land change trends, particularly by the increasing rural farmland abandonment and agricultural intensification phenomena. In Mediterranean countries, these processes are affecting especially traditional olive groves with enormous socio-economic costs to rural areas, endangering environmental sustainability and biodiversity. Traditional olive groves abandonment and intensification are clearly related to the reduction of olive oil production income, leading to reduced economic viability. Most promising strategies to boost traditional groves competitiveness—such as olive oil differentiation through adoption of protected denomination of origin labels and development of value-added olive products—rely on knowledge of the olive varieties and its specific properties that confer their uniqueness and authenticity. Given the lack of information about olive varieties on traditional groves, a feasible and inexpensive method of variety identification is required. We analyzed leaf spectral information of ten Portuguese olive varieties with a powerful data-mining approach in order to verify the ability of satellite’s hyperspectral sensors to provide an accurate olive variety identification. Our results show that these olive varieties are distinguishable by leaf reflectance information and suggest that even satellite open-source data could be used to map them. Additional advantages of olive varieties mapping were further discussed.

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“…The category of spectral indexes which may be used in this modelling is extremely large and varied, being mainly conditioned by the type of satellite images used as input data, as well as by the objective. Their description and applicability may be found in different articles, either making a synthesis (Bannari et al, 1995;Chen, 1996;Xue et al, 2017), or dedicated to specific researches (Agapiou et al, 2012;Heiskanen et al, 2013;Avola et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

Assessment of the Forest Health Through Remote Sensing Techniques in Valea Roșie Natura 2000 Site, Bihor County, Romania

Blaga

Josan

Herman

et al. 2019

Journal of Applied Engineering Sciences

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The present study deals with the estimation of the evolution tendency of the environmental stage of a protected habitat with predominant forest vegetation, during a short period of time, using techniques specific to remote sensing. Therefore, two important spectral indexes were tested while assessing the health of the forest ecosystems: i.e. the Normalized Difference Vegetation Index (NDVI) and the Structure Insensitive Pigment Index (SIPI). The period of time taken into consideration for the study was, 2013 - 2019, having used medium resolution satellite photos, Landsat 8 OLI, having initially undergone standard pre-processing operations (resize data, radiometric calibration, atmospheric correction). The satellite images modified according to the Top of Atmosphere Reflectance and corrected topographically resulted into getting values for the two before mentioned indexes. The quantity-spatial results obtained, correlated to the monthly values of the precipitations processed in order to obtain the SPI (Standardized Precipitation Index), mostly reveal, in what SIPI and also NDVI are concerned, a slight decrease in the quality of the forest on the analysed area in the sense that the vegetation stress is increased under meteorological factors, expressed differently depending on the morphometric and pedological parameters of the habitat.

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Remotely Sensed Vegetation Indices to Discriminate Field-Grown Olive Cultivars

Cited by 44 publications

References 34 publications

Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

Hyperspectral Reflectance as a Basis to Discriminate Olive Varieties—A Tool for Sustainable Crop Management

Assessment of the Forest Health Through Remote Sensing Techniques in Valea Roșie Natura 2000 Site, Bihor County, Romania

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