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Assessing the potential of multi-temporal WorldView-2 imagery for mapping West African agroforestry tree species
Linköping University, The Tema Institute, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences. Linköping University, The Tema Institute, Centre for Climate Science and Policy Research .ORCID iD: 0000-0002-3926-3671
Linköping University, The Tema Institute, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences.ORCID iD: 0000-0002-4484-266X
Section of Forest Remote Sensing, Department of Forest Resource Management, Swedish University of Agricultural Sciences, Sweden.
Université de Ouagadougou, Unité de Formation et Recherche en Sciences de la Vie et de la Terre, Burkina Faso.
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2015 (English)Manuscript (preprint) (Other academic)
Abstract [en]

Agroforestry tree species in the West Africa parklands are subject to increasing pressure from climate change and land use change, with potentially detrimental effects on local livelihoods and the environment. Methods that enable detailed and efficient mapping of individual trees are therefore needed, both for natural resource monitoring and ecological research. This study investigates the capability of multi-temporal WorldView-2 imagery to map five dominant tree species/groups in a parkland landscape in central Burkina Faso. The Random Forest algorithm is used for object based tree species classification and for assessing the relative importance of predictors. The classification accuracies from using wet season, dry season and multi-temporal datasets are compared to gain insights about the optimal timing for image acquisition. The multi-temporal dataset produced the most accurate classifications, with an overall accuracy (OA) of 82.4% (K = 0.77). For classifications based on single date imagery, the dry season (OA = 76.3%; K = 0.70) proved to be more suitable than the wet season (OA = 66.6%; K = 0.57). The predictors that contributed most to the classification success were based on visible wavelengths, in particular green, yellow and red, as well as the red edge band. It was therefore concluded that WorldView-2 with its unique band configuration represents a suitable data source for tree species mapping in West African parklands. Theseresults are particularly promising when considering the recently launched WorldView-3, which provides data both at higher spatial and spectral resolution, including additional shortwave infrared bands.

Place, publisher, year, edition, pages
2015.
Keyword [en]
Tree species mapping, WorldView-2, agroforestry, parkland, Sudano-Sahel
National Category
Environmental Sciences related to Agriculture and Land-use
Identifiers
URN: urn:nbn:se:liu:diva-121533OAI: oai:DiVA.org:liu-121533DiVA: diva2:856214
Available from: 2015-09-23 Created: 2015-09-23 Last updated: 2015-09-28Bibliographically 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 (print) (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: 2015-09-29Bibliographically approved

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