Scaling and uncertainty in landsat remote sensing of biophysical attributes
Monitoring environmental change is of high importance in our time of global change. Remote sensing technology provides the tools to view the ecological dynamics at a landscape scale and review the change through time with time series data availability. Creating congruence between data scales and fun...
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Montana State University - Bozeman, College of Agriculture
2015
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ftmontanastateu:oai:scholarworks.montana.edu:1/8868 2023-05-15T17:57:38+02:00 Scaling and uncertainty in landsat remote sensing of biophysical attributes Johnson, Aiden Vincent Chairperson, Graduate Committee: Scott Powell Paul Stoy, Nathaniel Brunsell, Stephanie Ewing, Scott Powell and Mark Greenwood were co-authors of the article, 'Change detection in the discontinuous permafrost zone using landsat: have surface features prone to pronounced methane efflux increased in spatial extent?' submitted to the journal 'Remote sensing' which is contained within this thesis. Paul Stoy , Lucy Marshall and Joel McCorkel were co-authors of the article, 'Random uncertainty in land surface temperature calculated using landsat TM, ETM+, and TIRS' submitted to the journal 'Ecological applications' which is contained within this thesis. 2015 application/pdf https://scholarworks.montana.edu/xmlui/handle/1/8868 en eng Montana State University - Bozeman, College of Agriculture https://scholarworks.montana.edu/xmlui/handle/1/8868 Copyright 2015 by Aiden Vincent Johnson Artificial satellites Climatic changes Remote sensing Bogs Thesis 2015 ftmontanastateu 2022-06-06T07:29:35Z Monitoring environmental change is of high importance in our time of global change. Remote sensing technology provides the tools to view the ecological dynamics at a landscape scale and review the change through time with time series data availability. Creating congruence between data scales and functional scales is a long standing challenge for Earth system scientists. In this research we evaluate methods for change detection and scaling data in a discontinuous permafrost zone of central Alaska and is characterized by pronounced permafrost thaw and methane release over decadal to century timescales. The primary goal is to evaluate the applicability of Landsat satellite remote sensing for detecting bog thermal expansion over time. We implement a Random Forests classification scheme in order to separate the landscape into its various land features and bog types, many features in this landscape are developed through an aged-stage transition of thermal expansion. The results of this classification were dominated by hydrologic features, with a 0.05 increase in mean albedo, providing essentially no change in both mean Normalized Difference Vegetation Index (NDVI) and mean Brightness Temperature (BT). In addition, we attempt to capture the scales of variation within the landscape using multi-resolution methods. The scale of variance as illustrated by a wavelet analysis for NDVI show the greatest amount of variance around 4.5 km to 5 km. Brightness Temperature had three peaks of high variance between 0.06 km - 1 km including maximum variance at about 0.5 km and a pair of peaks between 3 km and 4 km. An important component of any data analysis is quantifying the uncertainty. Uncertainty quantification in remote sensing data analysis is often over looked. In a second analysis we attempt to quantify the primary sources of uncertainty in Landsat remote sensing data via simulation methods. Specifically, we evaluate the level of uncertainty contributed to the data by applying a typical atmospheric correction through Monte ... Thesis permafrost Alaska Montana State University (MSU): ScholarWorks |
institution |
Open Polar |
collection |
Montana State University (MSU): ScholarWorks |
op_collection_id |
ftmontanastateu |
language |
English |
topic |
Artificial satellites Climatic changes Remote sensing Bogs |
spellingShingle |
Artificial satellites Climatic changes Remote sensing Bogs Johnson, Aiden Vincent Scaling and uncertainty in landsat remote sensing of biophysical attributes |
topic_facet |
Artificial satellites Climatic changes Remote sensing Bogs |
description |
Monitoring environmental change is of high importance in our time of global change. Remote sensing technology provides the tools to view the ecological dynamics at a landscape scale and review the change through time with time series data availability. Creating congruence between data scales and functional scales is a long standing challenge for Earth system scientists. In this research we evaluate methods for change detection and scaling data in a discontinuous permafrost zone of central Alaska and is characterized by pronounced permafrost thaw and methane release over decadal to century timescales. The primary goal is to evaluate the applicability of Landsat satellite remote sensing for detecting bog thermal expansion over time. We implement a Random Forests classification scheme in order to separate the landscape into its various land features and bog types, many features in this landscape are developed through an aged-stage transition of thermal expansion. The results of this classification were dominated by hydrologic features, with a 0.05 increase in mean albedo, providing essentially no change in both mean Normalized Difference Vegetation Index (NDVI) and mean Brightness Temperature (BT). In addition, we attempt to capture the scales of variation within the landscape using multi-resolution methods. The scale of variance as illustrated by a wavelet analysis for NDVI show the greatest amount of variance around 4.5 km to 5 km. Brightness Temperature had three peaks of high variance between 0.06 km - 1 km including maximum variance at about 0.5 km and a pair of peaks between 3 km and 4 km. An important component of any data analysis is quantifying the uncertainty. Uncertainty quantification in remote sensing data analysis is often over looked. In a second analysis we attempt to quantify the primary sources of uncertainty in Landsat remote sensing data via simulation methods. Specifically, we evaluate the level of uncertainty contributed to the data by applying a typical atmospheric correction through Monte ... |
author2 |
Chairperson, Graduate Committee: Scott Powell Paul Stoy, Nathaniel Brunsell, Stephanie Ewing, Scott Powell and Mark Greenwood were co-authors of the article, 'Change detection in the discontinuous permafrost zone using landsat: have surface features prone to pronounced methane efflux increased in spatial extent?' submitted to the journal 'Remote sensing' which is contained within this thesis. Paul Stoy , Lucy Marshall and Joel McCorkel were co-authors of the article, 'Random uncertainty in land surface temperature calculated using landsat TM, ETM+, and TIRS' submitted to the journal 'Ecological applications' which is contained within this thesis. |
format |
Thesis |
author |
Johnson, Aiden Vincent |
author_facet |
Johnson, Aiden Vincent |
author_sort |
Johnson, Aiden Vincent |
title |
Scaling and uncertainty in landsat remote sensing of biophysical attributes |
title_short |
Scaling and uncertainty in landsat remote sensing of biophysical attributes |
title_full |
Scaling and uncertainty in landsat remote sensing of biophysical attributes |
title_fullStr |
Scaling and uncertainty in landsat remote sensing of biophysical attributes |
title_full_unstemmed |
Scaling and uncertainty in landsat remote sensing of biophysical attributes |
title_sort |
scaling and uncertainty in landsat remote sensing of biophysical attributes |
publisher |
Montana State University - Bozeman, College of Agriculture |
publishDate |
2015 |
url |
https://scholarworks.montana.edu/xmlui/handle/1/8868 |
genre |
permafrost Alaska |
genre_facet |
permafrost Alaska |
op_relation |
https://scholarworks.montana.edu/xmlui/handle/1/8868 |
op_rights |
Copyright 2015 by Aiden Vincent Johnson |
_version_ |
1766166104338595840 |