Sub-metric analisis of vegetation structure in bog-heathland mosaics using very high resolution rpas imagery

Varela, Ramón Alberto Díaz; Iglesias, Silvia Calvo; Castro, Carmen Cillero; Varela, Eduardo

doi:10.1016/j.ecolind.2017.11.068

Cited by 15 publications

(18 citation statements)

References 43 publications

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“…Spatial patterns of peatlands can be tracked with remotely sensed data, but it has been argued that the spatial resolution in common mapping approaches is too coarse (Palace et al, 2018). Ultra-high spatial resolution (UHSR) remote sensing, which provides data with cm-level pixel size, can reveal such patterns in vegetation composition that are lost in coarser resolution (Díaz-Varela, Calvo Iglesias, Cillero Castro, & Díaz Varela, 2018;Gonçalves et al, 2016;Lehmann et al, 2016;Mora, Vieira, Pina, Lousada, & Christiansen, 2015). In particular, the benefits of UHSR are evident in fragmented landscapes such as peatlands (Arroyo- Mora, Kalacska, Lucanus, Soffer, & Leblanc, 2017;Lehmann et al, 2016;Lovitt et al, 2017;Palace et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Vegetation patterns have been mapped using remote sensing with multiple methods and levels of detail. A typical approach has been to map land cover, vegetation, or habitat types, such as different forest or peatland types (Díaz-Varela et al, 2018;Foody, 1997;Gonçalves et al, 2016;Mora et al, 2015;Tapia, Stein, & Bijker, 2005). There have also been efforts to map the presence of a single plant species (Dudley, Dennison, Roth, Roberts, & Coates, 2015;Roth, Roberts, Dennison, Peterson, & Alonzo, 2015), plant species grouped to communities (Duff, Bell, & York, 2014;Middleton et al, 2012;Rapinel, Rossignol, Hubert-Moy, Bouzillé, & Bonis, 2018) or plant functional types (PFTs; Cole, McMorrow, & Evans, 2014;Harris, Charnock, & Lucas, 2015;Kattenborn et al, 2017;Schmidtlein, Feilhauer, & Bruelheide, 2012;Ustin & Gamon, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Comparing ultra‐high spatial resolution remote‐sensing methods in mapping peatland vegetation

Räsänen

Juutinen

Tuittila

et al. 2019

J Vegetation Science

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Questions How to map floristic variation in a patterned fen in an ecologically meaningfully way? Can plant communities be delineated with species data generalized into plant functional types? What are the benefits and drawbacks of the two selected remote‐sensing approaches in mapping vegetation patterns, namely: (a) regression models of floristically defined fuzzy plant community clusters and (b) classification of predefined habitat types that combine vegetation and land cover information? Location Treeless 0.4 km2 mesotrophic string–flark fen in Kaamanen, northern Finland. Methods We delineated plant community clusters with fuzzy c‐means clustering based on two different inventories of plant species and functional type distribution. We used multiple optical remote‐sensing data sets, digital elevation models and vegetation height models derived from drone, aerial and satellite platforms from ultra‐high to very high spatial resolution (0.05–3 m) in an object‐based approach. We mapped spatial patterns for fuzzy and crisp plant community clusters using boosted regression trees, and fuzzy and crisp habitat types using supervised random forest classification. Results Clusters delineated with species‐specific data or plant functional type data produced comparable results. However, species‐specific data for graminoids and mosses improved the accuracy of clustering in the case of flarks and string margins. Mapping accuracy was higher for habitat types (overall accuracy 0.72) than for fuzzy plant community clusters (R2 values between 0.27 and 0.67). Conclusions For ecologically meaningful mapping of a patterned fen vegetation, plant functional types provide enough information. However, if the aim is to capture floristic variation in vegetation as realistically as possible, species‐specific data should be used. Maps of plant community clusters and habitat types complement each other. While fuzzy plant communities appear to be floristically most accurate, crisp habitat types are easiest to interpret and apply to different landscape and biogeochemical cycle analyses and modeling.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparing ultra‐high spatial resolution remote‐sensing methods in mapping peatland vegetation

Räsänen

Juutinen

Tuittila

et al. 2019

J Vegetation Science

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“…Therefore, we used a functional approach and recorded vegetation structural measures as surrogates of habitat quality (Gibbons and Freudenberger, 2006). The use of remote sensing also emerged as a valuable approach not only for habitat mapping, but also for spatially explicit habitat quality assessment over large areas, including datasets from different sensors ranging from optical (RGB, multi-spectral and hyperspectral) imagery, to products with 3D information from LiDAR, or Structure from Motion (SfM) point clouds (Corbane et al, 2015;Díaz Varela et al, 2018). In the present work, the use of multispectral/multitemporal imagery was particularly useful in the identification of seasonal (phenologic) differences in the spectral response of certain types of habitats, e.g.…”

Section: Methodological Approachmentioning

confidence: 99%

“…-Vegetation structure. The typical structure of the E. mackayana heathlands is monotonous at the landscape scale, but heterogeneous at the fine scale (Díaz-Varela et al, 2018;Fagúndez, 2018). It can be recognized as a treeless habitat that occurs in large patches, where shrub mats alternate with gaps of herbaceous species or even bare ground (Fagúndez, 2016).…”

Section: Defining Items For Habitat Qualitymentioning

confidence: 99%

“…-Erosive features and drainage problems. Overgrazing or construction work may cause the loss of vegetation cover and the subsequent soil erosion by runoff (Bokdam et al, 2000;Díaz-Varela et al, 2018). Alteration of hydrological dynamics due to different infrastructures such as paved roads are commonly associated to erosive events in areas with steep slopes.…”

Section: Defining Items For Habitat Qualitymentioning

confidence: 99%

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Habitat quality assessment of Atlantic wet heathlands in Serra do Xistral, NW Spain

Muñoz-Barcia

Lagos

Blanco-Arias

et al. 2019

CIG

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The assessment of habitat quality, especially in semi-natural managed systems, provides a powerful tool for monitoring short and longterm conservation actions. The Erica mackayana Atlantic wet heathlands of the Serra do Xistral protected area in Galicia, NW Spain, represent a dynamic system with high conservation value associated to traditional management through grazing of free-ranging cattle and wild ponies. Here, we aimed to develop a spatially-explicit, quantitative method for Habitat Quality Assessment, defining an optimum state and the alternative states that may arise from habitat degradation. Vegetation structure, grass-shrub cover ratio, gorse cover, presence of bracken, exotic species such as pine trees and saplings, erosive events and altered hydrological dynamics were identified as the main indicators of habitat degradation. A heterogeneous vegetation structure with a dominant shrub cover of c.a. 0.5 m height and constant gaps among shrubs, with a limited cover of gorse and absence of pine trees, bramble and bracken, and absence of erosive events was recognized as the optimum state. We applied the Habitat Quality Assessment (HQA) method to a pilot area within the Xistral protected site. Wet heathland was the dominant habitat, covering 37.1% of the area. 7.0% of the assessed heathlands were recognized as in the optimum state for habitat quality. Recommendations are made for habitat management to revert low scores, mainly by the adjustment of livestock numbers and the removal of exotic pine trees. Evaluación de la calidad de hábitats de brezales húmedos atlánticos en la Serra do Xistral, NO EspañaRESUMEN. La evaluación de la calidad de hábitats constituye una herramienta muy útil para el seguimiento, a medio y largo plazo, de las acciones de conservación, especialmente en sistemas semi-naturales manejados. Los brezales húmedos atlánticos con Erica mackayana del espacio Red Natura Serra do Xistral, situado en Galicia, noroeste de España, representan un sistema dinámico con alto valor de conservación asociado al manejo tradicional mediante Muñoz-Barcia et al. 534Cuadernos de Investigación Geográfica 45 (2), 2019, pp. 533-549 ganado vacuno y caballos salvajes. En este artículo desarrollamos un método cuantitativo y espacialmente explícito para la evaluación de la calidad del hábitat en brezales húmedos. Para ello definimos un estado óptimo y los estados alternativos que pueden resultar de la degradación del hábitat. Los principales indicadores de degradación que identificamos fueron la estructura de la vegetación, la proporción de cobertura de herbáceas-arbustivas, la cobertura de tojo, la presencia de helechos (Pteridium aquilinum), especies exóticas como los pinos, eventos erosivos y la existencia de dinámicas hidrológicas alteradas. El estado óptimo se definió como una estructura de la vegetación heterogénea, con una cobertura de arbustivas dominante de entorno a 0,5 m de alto y pasillos constantes entre las matas, con cierta cobertura de tojo, ausencia de pinos, helechos, eventos erosivos y alterac...

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Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral‐ and three‐dimensional information from UAV‐based aerial imagery

Mienna

Klanderud

Ørka

et al. 2022

Remote Sens Ecol Conserv

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The alpine treeline ecotone is expected to move upwards in elevation with global warming. Thus, mapping treeline ecotones is crucial in monitoring potential changes. Previous remote sensing studies have focused on the usage of satellites and aircrafts for mapping the treeline ecotone. However, treeline ecotones can be highly heterogenous, and thus the use of imagery with higher spatial resolution should be investigated. We evaluate the potential of using unmanned aerial vehicles (UAVs) for the collection of ultra-high spatial resolution imagery for mapping treeline ecotone land covers. We acquired imagery and field reference data from 32 treeline ecotone sites along a 1100 km latitudinal gradient in Norway (60-69°N). Before classification, we performed a superpixel segmentation of the UAV-derived orthomosaics and assigned land cover classes to segments: rock, water, snow, shadow, wetland, tree-covered area and five classes within the ridge-snowbed gradient. We calculated features providing spectral, textural, three-dimensional vegetation structure, topographical and shape information for the classification. To evaluate the influence of acquisition time during the growing season and geographical variations, we performed four sets of classifications: global, seasonal-based, geographical regional-based and seasonalregional-based. We found no differences in overall accuracy (OA) between the different classifications, and the global model with observations irrespective of data acquisition timing and geographical region had an OA of 73%. When accounting for similarities between closely related classes along the ridgesnowbed gradient, the accuracy increased to 92.6%. We found spectral features related to visible, red-edge and near-infrared bands to be the most important to predict treeline ecotone land cover classes. Our results show that the use of UAVs is efficient in mapping treeline ecotones, and that data can be acquired irrespective of timing within a growing season and geographical region to get accurate land cover maps. This can overcome constraints of a short field-season or low-resolution remote sensing data.

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Sub-metric analisis of vegetation structure in bog-heathland mosaics using very high resolution rpas imagery

Cited by 15 publications

References 43 publications

Comparing ultra‐high spatial resolution remote‐sensing methods in mapping peatland vegetation

Comparing ultra‐high spatial resolution remote‐sensing methods in mapping peatland vegetation

Habitat quality assessment of Atlantic wet heathlands in Serra do Xistral, NW Spain

Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral‐ and three‐dimensional information from UAV‐based aerial imagery

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