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Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest
Linköping University, Department of Thematic Studies, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Thematic Studies, Centre for Climate Science and Policy Research.ORCID iD: 0000-0002-3926-3671
Linköping University, Department of Thematic Studies, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Thematic Studies, Centre for Climate Science and Policy Research. Centre for Environment and Sustainability (GMV), University of Gothenburg and Chalmers University of Technology, Gothenburg, Sweden.ORCID iD: 0000-0002-4484-266X
Section of Forest Remote Sensing, Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
Institut de l'Environnement et de Recherches Agricoles (INERA), Département Productions Forestières, Burkina Faso.
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2015 (English)In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 7, 10017-10041 p.Article in journal (Refereed) Published
Abstract [en]

Accurate and timely maps of tree cover attributes are important tools for environmental research and natural resource management. We evaluate the utility of Landsat 8 for mapping tree canopy cover (TCC) and aboveground biomass (AGB) in a woodland landscape in Burkina Faso. Field data and WorldView-2 imagery were used to assemble the reference dataset. Spectral, texture, and phenology predictor variables were extracted from Landsat 8 imagery and used as input to Random Forest (RF) models. RF models based on multi-temporal and single date imagery were compared to determine the influence of phenology predictor variables. The effect of reducing the number of predictor variables on the RF predictions was also investigated. The model error was assessed using 10-fold cross 

validation. The most accurate models were created using multi-temporal imagery and variable selection, for both TCC (five predictor variables) and AGB (four predictor variables). The coefficient of determination of predicted versus observed values was 0.77 for TCC (RMSE = 8.9%) and 0.57 for AGB (RMSE = 17.6 tons∙ha−1). This mapping approach is based on freely available Landsat 8 data and relatively simple analytical methods, and is therefore applicable in woodland areas where sufficient reference data are available. 

Place, publisher, year, edition, pages
MDPI AG , 2015. Vol. 7, 10017-10041 p.
Keyword [en]
Landsat 8; woodland; Sudano-Sahel; tree canopy cover; aboveground biomass; multi-temporal imagery; Random Forest; variable selection; phenology
National Category
Environmental Sciences related to Agriculture and Land-use
Identifiers
URN: urn:nbn:se:liu:diva-120409DOI: 10.3390/rs70810017ISI: 000360818800025OAI: oai:DiVA.org:liu-120409DiVA: diva2:844520
Funder
Sida - Swedish International Development Cooperation AgencySwedish Research CouncilSwedish Energy Agency
Note

Funding text: Swedish International Development Cooperation Agency (Sida); Swedish Energy Agency; Swedish Research Council (VR/Sida)

Available from: 2015-08-06 Created: 2015-08-06 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Remote Sensing of Woodland Structure and Composition in the Sudano-Sahelian zone: Application of WorldView-2 and Landsat 8
Open this publication in new window or tab >>Remote Sensing of Woodland Structure and Composition in the Sudano-Sahelian zone: Application of WorldView-2 and Landsat 8
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Woodlands constitute the subsistence base of the majority of people in the Sudano-Sahelian zone (SSZ), but low availability of in situ data on vegetation structure and composition hampers research and monitoring. This thesis explores the utility of remote sensing for mapping and analysing vegetation, primarily trees, in the SSZ. A comprehensive literature review was first conducted to describe how the application of remote sensing has developed in the SSZ between 1975 and 2014, and to identify important research gaps. Based on the gaps identified in the literature review, the capabilities of two new satellite systems (WorldView-2 and Landsat 8) for mapping woodland structure and composition were tested in an area in central Burkina Faso.

The results shows that WorldView-2 represents a useful data source for mapping individual trees: 85.4% of the reference trees were detected in the WorldView-2 data and tree crown area was estimate with an average error of 45.6%. In addition, WorldView-2 data produced high classification accuracies for five locally important tree species. The highest overall classification accuracy (82.4%) was produced using multi-temporal WorldView-2 data. Landsat 8 data proved more suitable for mapping tree canopy cover as compared to aboveground biomass in the woodland landscape. Tree canopy cover and aboveground biomass was predicted with 41% and 66% root mean square error, respectively, at pixel level.

This thesis demonstrates the potential of easily accessible data from two satellite systems for mapping important tree attributes in woodland areas, and discusses how the usefulness of remote sensing for analyzing vegetation can be further enhanced in the SSZ.

Abstract [sv]

Merparten av befolkningen i Sudano-Sahel zonen (SSZ) är beroende av naturresurser och ekosystemtjänster från woodlands (öppen torrskog) för att säkra sin försörjning. Tillgången av fältmätningar av vegetationens struktur och sammansättning är mycket låg i detta område, vilket utgör ett problem för forskning och miljöövervakning. Denna avhandling undersöker nyttan av fjärranalys för att kartlägga och analysera vegetation, främst träd, i SSZ. En omfattande litteraturöversikt genomfördes först för att undersöka hur tillämpningen av fjärranalys har utvecklats i SSZ mellan 1975 och 2014, samt att identifiera viktiga forskningsluckor. Några av de luckor som konstaterades i litteraturgenomgången låg till grund för de följande studierna där två nya satellitsystem (Worldview-2 och Landsat 8) utvärderades för deras användbarhet att kartlägga trädtäckets struktur och artsammansättning i ett woodland-område i centrala Burkina Faso.

Resultaten visar att Worldview-2 är en värdefull datakälla för kartering av enskilda träd: 85.4% av referensträden detekterades och trädkronornas storlek uppskattades med ett medelfel av 45.6%. Worldview-2-data producerade även hög klassificeringsnoggrannhet för de fem lokalt viktigaste trädslagen. Den högsta noggrannheten (82.4%) uppnåddes med multi-temporal Worldview-2-data. Landsat 8 data visade sig mer lämpade för kartering av krontäcke, jämfört med biomassa. Medelfelet för karteringen var 41% för krontäcke och 66% för biomassa, på pixelnivå.

Avhandlingen visar att lättillgängliga data från två satellitsystem är användbara för kartläggning av viktiga trädattribut i woodlands, samt diskuterar hur nyttan av fjärranalys för vegetationsanalys kan ökas ytterligare i SSZ.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 68 p.
Series
Linköping Studies in Arts and Science, ISSN 0282-9800 ; 658
Keyword
Remote sensing; Sudano-Sahel; woodland; agroforestry; WorldView-2; Landsat 8; tree attributes; tree canopy cover; aboveground biomass; Random Forest, Fjärranalys; Sudano-Sahel; woodland; WorldView-2; Landsat 8; trädattribut; trädtäcke; biomassa; Random Forest
National Category
Environmental Sciences related to Agriculture and Land-use
Identifiers
urn:nbn:se:liu:diva-121536 (URN)10.3384/diss.diva-121536 (DOI)978-91-7685-927-8 (ISBN)
Public defence
2015-10-23, TEMCAS, Hus T, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2015-09-23 Created: 2015-09-23 Last updated: 2017-01-11Bibliographically approved

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