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Remote Sensing of Woodland Structure and Composition in the Sudano-Sahelian zone: Application of WorldView-2 and Landsat 8
Linköping University, Department of Thematic Studies, Tema Environmental Change. Linköping University, Faculty of Arts and Sciences.ORCID iD: 0000-0002-3926-3671
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 [en]
Remote sensing; Sudano-Sahel; woodland; agroforestry; WorldView-2; Landsat 8; tree attributes; tree canopy cover; aboveground biomass; Random Forest
Keyword [sv]
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: urn:nbn:se:liu:diva-121536DOI: 10.3384/diss.diva-121536ISBN: 978-91-7685-927-8 (print)OAI: oai:DiVA.org:liu-121536DiVA: diva2:856253
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
List of papers
1. Remote sensing of vegetation in the Sudano-Sahelian zone: A literature review from 1975 to 2014
Open this publication in new window or tab >>Remote sensing of vegetation in the Sudano-Sahelian zone: A literature review from 1975 to 2014
2016 (English)In: Journal of Arid Environments, ISSN 0140-1963, E-ISSN 1095-922X, Vol. 124, 257-269 p.Article, review/survey (Refereed) Published
Abstract [en]

Scarcity of in situ vegetation data inhibits research and natural resource management in the Sudano- Sahelian zone (SSZ). Satellite and aerial remote sensing (RS) constitute key technologies for improving the availability of vegetation data, and consequently the preconditions for scientific analysis and monitoring. The aim of this paper was to investigate how the hands-on application of RS for vegetation analysis has developed in the SSZ by reviewing the scientific literature published between 1975 and 2014. The paper assesses the usages and the users of RS by focusing on four aspects of the material (268 peer-reviewed articles), including publication details (time of publication, scientific discipline of journals and author nationality), geographic information (location of study areas and spatial scale of research), data usage (application of RS systems and procedures for accuracy assessments), and research topic (scientific objective of the research). Three key results were obtained: i) the application of RS to analyze vegetation in the SSZ has increased consistently since 1977 and it seems to become adopted by a growing number of scientific disciplines; ii) the contribution of African authors is low, potentially signalling a need for an increased transfer of knowledge and technology from developed countries; iii) RS has pri- marily been used to analyze changes in vegetation productivity and broad vegetation types, whereas its use for studying interactions between vegetation and environmental factors has been relatively low. This calls for stronger collaborative RS research that enables the mapping of additional vegetation variables of high relevance for the environmental problems facing the SSZ. Remotely sensed vegetation data are needed at spatial scales that suits the requirements of both research and natural resource management in order to further enhance the usefulness of this technology. 

Place, publisher, year, edition, pages
London, UK: Academic Press, 2016
Keyword
Remote sensing, Vegetation, Drylands, Sudano-Sahel, Monitoring, Natural resource management
National Category
Other Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:liu:diva-121292 (URN)10.1016/j.jaridenv.2015.08.022 (DOI)000364245200030 ()
Funder
Swedish Research Council, 348-2013-6547Sida - Swedish International Development Cooperation Agency, SWE-2009-176Swedish Energy Agency, 35586-1
Note

Funding agencies: Swedish International Development Cooperation Agency (Sida) [SWE-2009-176]; Swedish Energy Agency [35586-1]; Swedish Research Council (VR/Sida) [348-2013-6547]

Available from: 2015-09-13 Created: 2015-09-13 Last updated: 2017-12-04Bibliographically approved
2. Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis
Open this publication in new window or tab >>Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis
2014 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 12, 22643-22669 p.Article in journal (Refereed) Published
Abstract [en]

Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35–100 m2) and large (>100 m2) trees compared to small (<35 m2) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas. 

Place, publisher, year, edition, pages
Basel: M D P I AG, 2014
Keyword
remote sensing; high spatial resolution; WorldView-2; tree crown mapping; tree crown delineation; geographic object based image analysis; woodland; agroforestry; parkland; Burkina Faso
National Category
Other Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:liu:diva-113526 (URN)10.3390/s141222643 (DOI)000346794300026 ()25460815 (PubMedID)
Funder
Sida - Swedish International Development Cooperation Agency
Available from: 2015-01-20 Created: 2015-01-20 Last updated: 2017-12-05Bibliographically approved
3. Assessing the potential of multi-seasonal WorldView-2 imagery for mapping West African agroforestry tree species
Open this publication in new window or tab >>Assessing the potential of multi-seasonal WorldView-2 imagery for mapping West African agroforestry tree species
Show others...
2016 (English)In: International Journal of Applied Earth Observation and Geoinformation, ISSN 0303-2434, Vol. 50, 80-88 p.Article in journal (Refereed) Published
Abstract [en]

High resolution satellite systems enable efficient and detailed mapping of tree cover, with high potential to support both natural resource monitoring and ecological research. This study investigates the capability of multi-seasonal WorldView-2 imagery to map five dominant tree species at the individual tree crown level 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 WorldView-2 predictors. The classification accuracies from using wet season, dry season and multi-seasonal datasets are compared to gain insights about the optimal timing for image acquisition. The multi-seasonal dataset produced the most accurate classifications, with an overall accuracy (OA) of 83.4%. For classifications based on single date imagery, the dry season (OA=78.4%) proved to be more suitable than the wet season (OA=68.1%). The predictors that contributed most to the classification success were based on the red edge band and visible wavelengths, in particular green and yellow. It was therefore conchided that WorldView-2, with its unique band configuration, represents a suitable data source for tree species mapping in West African parklands. These results are particularly promising when considering the recently launched WorldView-3, which provides data both at higher spatial and spectral resolution, including shortwave infrared bands. (C) 2016 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
Elsevier, 2016
Keyword
Tree species mapping; WorldView-2; Agroforestry; Parkland; Sudano-Sahel
National Category
Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:liu:diva-128916 (URN)10.1016/j.jag.2016.03.004 (DOI)000375819200008 ()
Note

Funding Agencies|Swedish Research Council; Swedish International Development Cooperation Agency (Sida); Swedish Energy Agency.

The previous status of this article was Manuscript and the working title was Assessing the potential of multi-temporal WorldView-2 imagery for mapping West African agroforestry tree species.

Available from: 2016-06-09 Created: 2016-06-07 Last updated: 2017-11-30Bibliographically approved
4. Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest
Open this publication in new window or tab >>Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest
Show others...
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
Keyword
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:nbn:se:liu:diva-120409 (URN)10.3390/rs70810017 (DOI)000360818800025 ()
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

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