@article{afrin_development_2019,
	title = {Development of {Land}-{Use}/{Land}-{Cover} {Maps} {Using} {Landsat}-8 and {MODIS} {Data}, and {Their} {Integration} for {Hydro}-{Ecological} {Applications}},
	volume = {19},
	issn = {1424-8220},
	url = {https://www.mdpi.com/1424-8220/19/22/4891},
	doi = {10.3390/s19224891},
	abstract = {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, these maps could serve as important decision support tools for policy-makers and local regulatory authorities in the sustainable management of the Athabasca River watershed.},
	number = {22},
	journal = {Sensors},
	author = {Afrin, Sadia and Gupta, Anil and Farjad, Babak and Ahmed, M. and Achari, Gopal and Hassan, Quazi K.},
	month = nov,
	year = {2019},
	pmid = {31717509},
	note = {Publisher: MDPI AG},
	keywords = {NALCMS},
	pages = {4891},
}

{"_id":"KdfnkzJGjNhs7HDQk","bibbaseid":"afrin-gupta-farjad-ahmed-achari-hassan-developmentoflanduselandcovermapsusinglandsat8andmodisdataandtheirintegrationforhydroecologicalapplications-2019","author_short":["Afrin, S.","Gupta, A.","Farjad, B.","Ahmed, M.","Achari, G.","Hassan, Q. K."],"bibdata":{"bibtype":"article","type":"article","title":"Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications","volume":"19","issn":"1424-8220","url":"https://www.mdpi.com/1424-8220/19/22/4891","doi":"10.3390/s19224891","abstract":"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, these maps could serve as important decision support tools for policy-makers and local regulatory authorities in the sustainable management of the Athabasca River watershed.","number":"22","journal":"Sensors","author":[{"propositions":[],"lastnames":["Afrin"],"firstnames":["Sadia"],"suffixes":[]},{"propositions":[],"lastnames":["Gupta"],"firstnames":["Anil"],"suffixes":[]},{"propositions":[],"lastnames":["Farjad"],"firstnames":["Babak"],"suffixes":[]},{"propositions":[],"lastnames":["Ahmed"],"firstnames":["M."],"suffixes":[]},{"propositions":[],"lastnames":["Achari"],"firstnames":["Gopal"],"suffixes":[]},{"propositions":[],"lastnames":["Hassan"],"firstnames":["Quazi","K."],"suffixes":[]}],"month":"November","year":"2019","pmid":"31717509","note":"Publisher: MDPI AG","keywords":"NALCMS","pages":"4891","bibtex":"@article{afrin_development_2019,\n\ttitle = {Development of {Land}-{Use}/{Land}-{Cover} {Maps} {Using} {Landsat}-8 and {MODIS} {Data}, and {Their} {Integration} for {Hydro}-{Ecological} {Applications}},\n\tvolume = {19},\n\tissn = {1424-8220},\n\turl = {https://www.mdpi.com/1424-8220/19/22/4891},\n\tdoi = {10.3390/s19224891},\n\tabstract = {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, these maps could serve as important decision support tools for policy-makers and local regulatory authorities in the sustainable management of the Athabasca River watershed.},\n\tnumber = {22},\n\tjournal = {Sensors},\n\tauthor = {Afrin, Sadia and Gupta, Anil and Farjad, Babak and Ahmed, M. and Achari, Gopal and Hassan, Quazi K.},\n\tmonth = nov,\n\tyear = {2019},\n\tpmid = {31717509},\n\tnote = {Publisher: MDPI AG},\n\tkeywords = {NALCMS},\n\tpages = {4891},\n}\n\n\n\n","author_short":["Afrin, S.","Gupta, A.","Farjad, B.","Ahmed, M.","Achari, G.","Hassan, Q. K."],"key":"afrin_development_2019","id":"afrin_development_2019","bibbaseid":"afrin-gupta-farjad-ahmed-achari-hassan-developmentoflanduselandcovermapsusinglandsat8andmodisdataandtheirintegrationforhydroecologicalapplications-2019","role":"author","urls":{"Paper":"https://www.mdpi.com/1424-8220/19/22/4891"},"keyword":["NALCMS"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/zotero/NAAtlas2024","dataSources":["yRJdyJoax6GFubwNS","3fS6y29xitMxSyCmw","SmeabbQSEFozkXJuC","3cx6m8LrzQx6SsjF2","qLjf8q88GSLZ5dAmC"],"keywords":["nalcms"],"search_terms":["development","land","use","land","cover","maps","using","landsat","modis","data","integration","hydro","ecological","applications","afrin","gupta","farjad","ahmed","achari","hassan"],"title":"Development of Land-Use/Land-Cover Maps Using Landsat-8 and MODIS Data, and Their Integration for Hydro-Ecological Applications","year":2019}