Synergy of airborne LiDAR and Worldview-2 satellite imagery for landcover and habitat mapping: A BIO SOS-EODHaM case study for the Netherlands

C. A. Mücher; L. Roupioz; H. Kramer; M. M. B. Bogers; R. H. G. Jongman; R. M. Lucas; V. E. Kosmidou; Z. Petrou; I. Manakos; E. Padoa-Schioppa; M. Adamo; P. Blonda

doi:10.1016/j.jag.2014.09.001

Synergy of airborne LiDAR and Worldview-2 satellite imagery for landcover and habitat mapping: A BIO SOS-EODHaM case study for the Netherlands

C. A. Mücher, L. Roupioz, H. Kramer, M. M. B. Bogers, R. H. G. Jongman, R. M. Lucas, V. E. Kosmidou, Z. Petrou, I. Manakos, E. Padoa-Schioppa, M. Adamo, P. Blonda

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of all vegetated objects in the Netherlands from LiDAR data, in preparation for new habitat classifications.

Original language	English
Pages (from-to)	48-55
Number of pages	8
Journal	International Journal of Applied Earth Observation and Geoinformation
Volume	37
Early online date	16 Oct 2014
DOIs	https://doi.org/10.1016/j.jag.2014.09.001
Publication status	Published - 01 May 2015
Externally published	Yes

Keywords

LiDAR
optical remote sensing
vegetation structure
land cover
general habitat categories

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jag.2014.09.001

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Mücher, C. A., Roupioz, L., Kramer, H., Bogers, M. M. B., Jongman, R. H. G., Lucas, R. M., Kosmidou, V. E., Petrou, Z., Manakos, I., Padoa-Schioppa, E., Adamo, M., & Blonda, P. (2015). Synergy of airborne LiDAR and Worldview-2 satellite imagery for landcover and habitat mapping: A BIO SOS-EODHaM case study for the Netherlands. International Journal of Applied Earth Observation and Geoinformation, 37, 48-55. https://doi.org/10.1016/j.jag.2014.09.001

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abstract = "A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of all vegetated objects in the Netherlands from LiDAR data, in preparation for new habitat classifications.",

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Mücher, CA, Roupioz, L, Kramer, H, Bogers, MMB, Jongman, RHG, Lucas, RM, Kosmidou, VE, Petrou, Z, Manakos, I, Padoa-Schioppa, E, Adamo, M & Blonda, P 2015, 'Synergy of airborne LiDAR and Worldview-2 satellite imagery for landcover and habitat mapping: A BIO SOS-EODHaM case study for the Netherlands', International Journal of Applied Earth Observation and Geoinformation, vol. 37, pp. 48-55. https://doi.org/10.1016/j.jag.2014.09.001

TY - JOUR

T1 - Synergy of airborne LiDAR and Worldview-2 satellite imagery for landcover and habitat mapping: A BIO SOS-EODHaM case study for the Netherlands

AU - Mücher, C. A.

AU - Roupioz, L.

AU - Kramer, H.

AU - Bogers, M. M. B.

AU - Jongman, R. H. G.

AU - Lucas, R. M.

AU - Kosmidou, V. E.

AU - Petrou, Z.

AU - Manakos, I.

AU - Padoa-Schioppa, E.

AU - Adamo, M.

AU - Blonda, P.

N1 - cited By 5

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N2 - A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of all vegetated objects in the Netherlands from LiDAR data, in preparation for new habitat classifications.

AB - A major challenge is to develop a biodiversity observation system that is cost effective and applicable in any geographic region. Measuring and reliable reporting of trends and changes in biodiversity requires amongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification results for a Dutch case study. The EODHaM system was developed within the BIO_SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each land cover and habitat class based on spectral and height information. One of the main findings is that canopy height models, as derived from LiDAR, in combination with very high resolution satellite imagery provides a powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping for any location across the globe. The assessment of the EODHaM classification results based on field data showed an overall accuracy of 74% for the land cover classes as described according to the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while the overall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC) system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping unit on the basis of the composition of the individual life forms and height measurements. The classification showed very good results for forest phanerophytes (FPH) when individual life forms were analyzed in terms of their percentage coverage estimates per mapping unit from the LCCS classification and validated with field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might also be due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification results encouraged us to derive the heights of all vegetated objects in the Netherlands from LiDAR data, in preparation for new habitat classifications.

KW - LiDAR

KW - optical remote sensing

KW - vegetation structure

KW - land cover

KW - general habitat categories

U2 - 10.1016/j.jag.2014.09.001

DO - 10.1016/j.jag.2014.09.001

M3 - Article

SN - 0303-2434

VL - 37

SP - 48

EP - 55

JO - International Journal of Applied Earth Observation and Geoinformation

JF - International Journal of Applied Earth Observation and Geoinformation

ER -

Synergy of airborne LiDAR and Worldview-2 satellite imagery for landcover and habitat mapping: A BIO SOS-EODHaM case study for the Netherlands

Abstract

Keywords

UN SDGs

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