Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications
The Athabasca River watershed plays a dominant role in both the economy and the environment in Alberta, Canada. Natural and anthropogenic factors rapidly changed the landscape of the watershed in recent decades. The dynamic of such changes in the landscape characteristics of the watershed calls for...
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ftdoajarticles:oai:doaj.org/article:3dc3191f7cd74704bed89c0fb41ff34c 2023-05-15T15:26:01+02:00 Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications Sadia Afrin Anil Gupta Babak Farjad M. Razu Ahmed Gopal Achari Quazi Hassan 2019-11-01T00:00:00Z https://doi.org/10.3390/s19224891 https://doaj.org/article/3dc3191f7cd74704bed89c0fb41ff34c EN eng MDPI AG https://www.mdpi.com/1424-8220/19/22/4891 https://doaj.org/toc/1424-8220 1424-8220 doi:10.3390/s19224891 https://doaj.org/article/3dc3191f7cd74704bed89c0fb41ff34c Sensors, Vol 19, Iss 22, p 4891 (2019) land use and land cover hydrology ecology wetland athabasca river watershed isodata clustering post-classification modification Chemical technology TP1-1185 article 2019 ftdoajarticles https://doi.org/10.3390/s19224891 2022-12-30T22:10:33Z The Athabasca River watershed plays a dominant role in both the economy and the environment in Alberta, Canada. Natural and anthropogenic factors rapidly changed the landscape of the watershed in recent decades. The dynamic of such changes in the landscape characteristics of the watershed calls for a comprehensive and up-to-date land-use and land-cover (LULC) map, which could serve different user-groups and purposes. The aim of the study herein was to delineate a 2016 LULC map of the Athabasca River watershed using Landsat-8 Operational Land Imager (OLI) images, Moderate Resolution Imaging Spectroradiometer (MODIS)-derived enhanced vegetation index (EVI) images, and other ancillary data. In order to achieve this, firstly, a preliminary LULC map was developed through applying the iterative self-organizing data analysis (ISODATA) clustering technique on 24 scenes of Landsat-8 OLI. Secondly, a Terra MODIS-derived 250-m 16-day composite of 30 EVI images over the growing season was employed to enhance the vegetation classes. Thirdly, several geospatial ancillary datasets were used in the post-classification improvement processes to generate a final 2016 LULC map of the study area, exhibiting 14 LULC classes. Fourthly, an accuracy assessment was carried out to ensure the reliability of the generated final LULC classes. The results, with an overall accuracy and Cohen’s kappa of 74.95% and 68.34%, respectively, showed that coniferous forest (47.30%), deciduous forest (16.76%), mixed forest (6.65%), agriculture (6.37%), water (6.10%), and developed land (3.78%) were the major LULC classes of the watershed. Fifthly, to support the data needs of scientists across various disciplines, data fusion techniques into the LULC map were performed using the Alberta merged wetland inventory 2017 data. The results generated two useful maps applicable for hydro-ecological applications. Such maps depicted two specific categories including different types of burned (approximately 6%) and wetland (approximately 30%) classes. In fact, ... Article in Journal/Newspaper Athabasca River Directory of Open Access Journals: DOAJ Articles Athabasca River Canada Sensors 19 22 4891 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
land use and land cover hydrology ecology wetland athabasca river watershed isodata clustering post-classification modification Chemical technology TP1-1185 |
spellingShingle |
land use and land cover hydrology ecology wetland athabasca river watershed isodata clustering post-classification modification Chemical technology TP1-1185 Sadia Afrin Anil Gupta Babak Farjad M. Razu Ahmed Gopal Achari Quazi Hassan Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications |
topic_facet |
land use and land cover hydrology ecology wetland athabasca river watershed isodata clustering post-classification modification Chemical technology TP1-1185 |
description |
The Athabasca River watershed plays a dominant role in both the economy and the environment in Alberta, Canada. Natural and anthropogenic factors rapidly changed the landscape of the watershed in recent decades. The dynamic of such changes in the landscape characteristics of the watershed calls for a comprehensive and up-to-date land-use and land-cover (LULC) map, which could serve different user-groups and purposes. The aim of the study herein was to delineate a 2016 LULC map of the Athabasca River watershed using Landsat-8 Operational Land Imager (OLI) images, Moderate Resolution Imaging Spectroradiometer (MODIS)-derived enhanced vegetation index (EVI) images, and other ancillary data. In order to achieve this, firstly, a preliminary LULC map was developed through applying the iterative self-organizing data analysis (ISODATA) clustering technique on 24 scenes of Landsat-8 OLI. Secondly, a Terra MODIS-derived 250-m 16-day composite of 30 EVI images over the growing season was employed to enhance the vegetation classes. Thirdly, several geospatial ancillary datasets were used in the post-classification improvement processes to generate a final 2016 LULC map of the study area, exhibiting 14 LULC classes. Fourthly, an accuracy assessment was carried out to ensure the reliability of the generated final LULC classes. The results, with an overall accuracy and Cohen’s kappa of 74.95% and 68.34%, respectively, showed that coniferous forest (47.30%), deciduous forest (16.76%), mixed forest (6.65%), agriculture (6.37%), water (6.10%), and developed land (3.78%) were the major LULC classes of the watershed. Fifthly, to support the data needs of scientists across various disciplines, data fusion techniques into the LULC map were performed using the Alberta merged wetland inventory 2017 data. The results generated two useful maps applicable for hydro-ecological applications. Such maps depicted two specific categories including different types of burned (approximately 6%) and wetland (approximately 30%) classes. In fact, ... |
format |
Article in Journal/Newspaper |
author |
Sadia Afrin Anil Gupta Babak Farjad M. Razu Ahmed Gopal Achari Quazi Hassan |
author_facet |
Sadia Afrin Anil Gupta Babak Farjad M. Razu Ahmed Gopal Achari Quazi Hassan |
author_sort |
Sadia Afrin |
title |
Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications |
title_short |
Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications |
title_full |
Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications |
title_fullStr |
Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications |
title_full_unstemmed |
Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications |
title_sort |
development of land-use/land-cover maps using landsat-8 and modis data, and their integration for hydro-ecological applications |
publisher |
MDPI AG |
publishDate |
2019 |
url |
https://doi.org/10.3390/s19224891 https://doaj.org/article/3dc3191f7cd74704bed89c0fb41ff34c |
geographic |
Athabasca River Canada |
geographic_facet |
Athabasca River Canada |
genre |
Athabasca River |
genre_facet |
Athabasca River |
op_source |
Sensors, Vol 19, Iss 22, p 4891 (2019) |
op_relation |
https://www.mdpi.com/1424-8220/19/22/4891 https://doaj.org/toc/1424-8220 1424-8220 doi:10.3390/s19224891 https://doaj.org/article/3dc3191f7cd74704bed89c0fb41ff34c |
op_doi |
https://doi.org/10.3390/s19224891 |
container_title |
Sensors |
container_volume |
19 |
container_issue |
22 |
container_start_page |
4891 |
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1766356593039900672 |