Remote sensing characterisation of the forest-tundra ecotone
The transition zone between the boreal forest and Arctic tundra, the Forest-tundra ecotone (FTE), is an area of high ecological and climatological significance. Satellite remote sensing has the potential to enable accurate circumarctic mapping and characterisation of both latitudinal and altitudinal...
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ftdatacite:10.17863/cam.44713 2023-05-15T15:19:25+02:00 Remote sensing characterisation of the forest-tundra ecotone Guo, Wenkai 2019 https://dx.doi.org/10.17863/cam.44713 https://www.repository.cam.ac.uk/handle/1810/297659 en eng Apollo - University of Cambridge Repository https://www.rioxx.net/licenses/all-rights-reserved/ All Rights Reserved All rights reserved remote sensing forest-tundra ecotone vegetation continuous fields texture analysis image classification google earth engine Text Thesis article-journal ScholarlyArticle 2019 ftdatacite https://doi.org/10.17863/cam.44713 2021-11-05T12:55:41Z The transition zone between the boreal forest and Arctic tundra, the Forest-tundra ecotone (FTE), is an area of high ecological and climatological significance. Satellite remote sensing has the potential to enable accurate circumarctic mapping and characterisation of both latitudinal and altitudinal FTEs. This study aims at a multi-platform, multi-scale characterisation of the FTE phenomenon and an evaluation of the response of the interface to climate change. This involves three main steps: FTE delineation, FTE categorisation based on the spatial characteristics of the interface, and the investigation of the relationship between FTE dynamics and spatial configuration in the circumarctic region. FTE delineation is conducted using an image texture-based classification scheme developed to statistically exploit the spatial patterns of the interface. Image texture statistics for tree cover density are derived from the grey-level co-occurrence matrix (GLCM), and the Landsat Vegetation Continuous Fields (VCF) product is used as the primary data source. The outcome offers advantages, both visually and statistically, over traditional image classification methods and can be applied to different parts of the circumarctic region. Several globally occurring primary spatial ‘forms’ are recognised for altitudinal FTEs which are found to have linkages to the sensitivity of the interface to shift with climate change. A technique is developed to categorise the FTEs into these spatial forms by the degree of fragmentation of the interface. The technique involves a texture extraction algorithm named FOurier-based Textural Ordination (FOTO) and supervised classification. Normalised Difference Vegetation Index (NDVI) calculated from Sentinel-2 imagery is used for FTE derivation and categorisation. Finally, the relationship between the response of circumarctic latitudinal FTE to climate change and its spatial characteristics is investigated at MODIS (MOderate Resolution Image Spectroradiometer) resolution utilising the data availability and computing powers of the Google Earth Engine (GEE) platform. Building on the theory of treeline ‘forms’, a continuous measurement of fragmentation is developed based on window spectral analysis to represent the spatial characteristics of the FTE. Statistical relationship between FTE fragmentation, dynamics and continentality is analysed. This provides insight into how FTE spatial configuration links to interactions between the interface position and outside forcing, which can potentially contribute to the optimisation of future climate modelling as well as the modelling of vegetation reactions to climate change. : the cambridge trust, trinity college, china scholarship council Thesis Arctic Climate change Tundra DataCite Metadata Store (German National Library of Science and Technology) Arctic |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
remote sensing forest-tundra ecotone vegetation continuous fields texture analysis image classification google earth engine |
spellingShingle |
remote sensing forest-tundra ecotone vegetation continuous fields texture analysis image classification google earth engine Guo, Wenkai Remote sensing characterisation of the forest-tundra ecotone |
topic_facet |
remote sensing forest-tundra ecotone vegetation continuous fields texture analysis image classification google earth engine |
description |
The transition zone between the boreal forest and Arctic tundra, the Forest-tundra ecotone (FTE), is an area of high ecological and climatological significance. Satellite remote sensing has the potential to enable accurate circumarctic mapping and characterisation of both latitudinal and altitudinal FTEs. This study aims at a multi-platform, multi-scale characterisation of the FTE phenomenon and an evaluation of the response of the interface to climate change. This involves three main steps: FTE delineation, FTE categorisation based on the spatial characteristics of the interface, and the investigation of the relationship between FTE dynamics and spatial configuration in the circumarctic region. FTE delineation is conducted using an image texture-based classification scheme developed to statistically exploit the spatial patterns of the interface. Image texture statistics for tree cover density are derived from the grey-level co-occurrence matrix (GLCM), and the Landsat Vegetation Continuous Fields (VCF) product is used as the primary data source. The outcome offers advantages, both visually and statistically, over traditional image classification methods and can be applied to different parts of the circumarctic region. Several globally occurring primary spatial ‘forms’ are recognised for altitudinal FTEs which are found to have linkages to the sensitivity of the interface to shift with climate change. A technique is developed to categorise the FTEs into these spatial forms by the degree of fragmentation of the interface. The technique involves a texture extraction algorithm named FOurier-based Textural Ordination (FOTO) and supervised classification. Normalised Difference Vegetation Index (NDVI) calculated from Sentinel-2 imagery is used for FTE derivation and categorisation. Finally, the relationship between the response of circumarctic latitudinal FTE to climate change and its spatial characteristics is investigated at MODIS (MOderate Resolution Image Spectroradiometer) resolution utilising the data availability and computing powers of the Google Earth Engine (GEE) platform. Building on the theory of treeline ‘forms’, a continuous measurement of fragmentation is developed based on window spectral analysis to represent the spatial characteristics of the FTE. Statistical relationship between FTE fragmentation, dynamics and continentality is analysed. This provides insight into how FTE spatial configuration links to interactions between the interface position and outside forcing, which can potentially contribute to the optimisation of future climate modelling as well as the modelling of vegetation reactions to climate change. : the cambridge trust, trinity college, china scholarship council |
format |
Thesis |
author |
Guo, Wenkai |
author_facet |
Guo, Wenkai |
author_sort |
Guo, Wenkai |
title |
Remote sensing characterisation of the forest-tundra ecotone |
title_short |
Remote sensing characterisation of the forest-tundra ecotone |
title_full |
Remote sensing characterisation of the forest-tundra ecotone |
title_fullStr |
Remote sensing characterisation of the forest-tundra ecotone |
title_full_unstemmed |
Remote sensing characterisation of the forest-tundra ecotone |
title_sort |
remote sensing characterisation of the forest-tundra ecotone |
publisher |
Apollo - University of Cambridge Repository |
publishDate |
2019 |
url |
https://dx.doi.org/10.17863/cam.44713 https://www.repository.cam.ac.uk/handle/1810/297659 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Tundra |
genre_facet |
Arctic Climate change Tundra |
op_rights |
https://www.rioxx.net/licenses/all-rights-reserved/ All Rights Reserved All rights reserved |
op_doi |
https://doi.org/10.17863/cam.44713 |
_version_ |
1766349600548978688 |