Relascope sum of Sitka spruce Picea sitchensis in Fusa and Tysnes

Sampling event
Последняя версия опубликовано Norwegian University of Life Sciences (NMBU) дек. 13, 2019 Norwegian University of Life Sciences (NMBU)
Дата публикации:
13 декабря 2019 г.
Лицензия:
CC-BY 4.0

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Описание

Invasive species can be considered a threat to biodiversity, and remote sensing has been proposed as a tool for detection and monitoring of invasive species. In this study, we test the ability to discriminate between two tree species of the same genera, using data from Landsat 8 satellite imagery, aerial images, and airborne laser scanning. Ground observations from forest stands dominated by either Norway spruce (Picea abies) or Sitka spruce (Picea sitchensis) were coupled with variables derived from each of the three sets of remote sensing data. Random forest, support vector machine, and logistic regression classification models were fit to the data, and the classification accuracy tested by performing a cross-validation. Classification accuracies were compared for different combinations of remote sensing data and classification methods. The overall classification accuracy varied from 0.53 to 0.79, with the highest accuracy obtained using logistic regression with a combination of data derived from Landsat imagery and aerial images. The corresponding kappa value was 0.58. The contribution to the classification accuracy from using airborne data in addition to Landsat imagery was not substantial in this study. The classification accuracy varied between models using data from individual Landsat images.

The study area is within the Fusa and Tysnes municipalities on the western coast of Norway (60°2′N, 5°46′E, 0–500 m above sea level, Figure 1). The forest is naturally dominated by Scots pine and deciduous species, mainly birch (Betula pubescens). From the 1940s and throughout the second part of the twentieth century, regeneration using non-native tree species—such as Sitka spruce—was common in this region on the west coast of Norway. Note that Norway spruce is also considered non-native in parts of this region. The productive forest area is about 260 km2, and the species composition is approximately 13% spruce, 66% pine, and 20% deciduous trees. Three sets of field observations were utilized in the present study, with observations from a total of 240 individual locations. All locations were situated in a spruce-dominated forest, and the proportions of Sitka spruce and Norway spruce were recorded for all locations. A total of 113 locations were dominated by Sitka spruce, and 127 were dominated by Norway spruce. Two of the sets were initially collected as a part of the data acquisition in other research and forest inventory projects.

Field measurements with the main purpose of increasing the number of observations from locations dominated by Sitka spruce was carried out during the summer of 2015. From an initial set of all forest stands in the study area dominated by Sitka spruce, 30 stands were subjectively chosen for measurements. With an initial goal of having the observations evenly spread out in the study area, the selection was ultimately guided by accessibility from, e.g., forest roads. The selection of the 30 stands were carried out prior to visiting the stands in the field, with the exception of a few occasions in which a nearby stand was measured instead due to severe storm felling in the originally chosen stand. Within the selected stands, three locations were subjectively chosen, guided by these criteria: the locations are evenly spread out in the stand and are preferably not close to stand borders. At each of the three locations, the proportions of the basal area of Sitka spruce versus other species were recorded using a relascope.

Записи данных

Данные этого sampling event ресурса были опубликованы в виде Darwin Core Archive (DwC-A), который является стандартным форматом для обмена данными о биоразнообразии в виде набора из одной или нескольких таблиц. Основная таблица данных содержит 90 записей.

Также в наличии 2 таблиц с данными расширений. Записи расширений содержат дополнительную информацию об основной записи. Число записей в каждой таблице данных расширения показано ниже.

Event (core)
90
MeasurementOrFacts 
90
Occurrence 
87

Данный экземпляр IPT архивирует данные и таким образом служит хранилищем данных. Данные и метаданные ресурсов доступны для скачивания в разделе Загрузки. В таблице версий перечислены другие версии ресурса, которые были доступны публично, что позволяет отслеживать изменения, внесенные в ресурс с течением времени.

Версии

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Как оформить ссылку

Исследователи должны дать ссылку на эту работу следующим образом:

Hauglin, M.; Ørka, H.O. Discriminating between Native Norway Spruce and Invasive Sitka Spruce—A Comparison of Multitemporal Landsat 8 Imagery, Aerial Images and Airborne Laser Scanner Data. Remote Sens. 2016, 8, 363.

Права

Исследователи должны соблюдать следующие права:

Публикующей организацией и владельцем прав на данную работу является Norwegian University of Life Sciences (NMBU). Эта работа находится под лицензией Creative Commons Attribution (CC-BY 4.0).

Регистрация в GBIF

Этот ресурс был зарегистрирован в GBIF, ему был присвоен следующий UUID: 44ef1f04-b01c-4b42-8baa-679e26ce43bc.  Norwegian University of Life Sciences (NMBU) отвечает за публикацию этого ресурса, и зарегистрирован в GBIF как издатель данных при оподдержке GBIF Norway.

Ключевые слова

Samplingevent; tree species classification; invasive species; Sitka spruce

Контакты

Hans Ole Ørka
  • Originator
  • Point Of Contact
NMBU
Ås
NO
Mari Steinert
  • Metadata Provider
NMBU
Ås
NO
Christian Svindseth

Таксономический охват

Picea sitchensis

Species Picea sitchensis

Данные проекта

Описание отсутсвует

Название Use of remote sensing for mapping of non-native conifer species
Финансирование The project was funded by the Norwegian Environment Agency and conducted from November 2014 to November 2015.

Исполнители проекта:

Hans Ole Ørka
  • Author
Knut Marius Hauglin
  • Author

Библиографические ссылки

  1. http://www.mdpi.com/2072-4292/8/5/363
  2. http://www.umb.no/statisk/ina/publikasjoner/fagrapport/if33.pdf

Дополнительные метаданные

Альтернативные идентификаторы 44ef1f04-b01c-4b42-8baa-679e26ce43bc
https://ipt.gbif.no/resource?r=sitka