Skip to main content

Evaluating Land Cover Change on the Island of Santa Cruz, Galapagos Archipelago of Ecuador Through Cloud-Gap Filling and Multi-sensor Analysis

  • Chapter
  • First Online:
Land Cover and Land Use Change on Islands

Abstract

Human migration and tourism in the Galapagos archipelago have rapidly increased since the 1980s. Accordingly, several Galapagos islands have experienced significant urban and agricultural development. Despite such dynamics, land cover map products currently available for the Galapagos Archipelago are limited in both spatial and temporal extents, mainly due to persistent cloud coverage for the area. This study characterizes approximately 20 years of land cover change on the Santa Cruz Island of the Galapagos archipelago through multi-sensor satellite data analyses using a rich Landsat archive as well as SPOT and Sentinel-2 imagery. To address the issue of satellite data availability in this cloud-prone region, this study examines two radiometric normalization and cloud gap-filling approaches on partially cloudy Landsat-7 SLC-off images. Compared to a commonly used Major Axis regression method, Random forest-based radiometric normalization shows superior performance in this complex tropical island setting, indicated by reduced differences of subject-reference image pairs and improved land cover mapping. Our land cover mapping focuses on characterizing urban and built-up, agriculture, and invasive plant species over time. Training data points are identified in the common ‘no-change’ areas for the years of 2000, 2009, and 2019, thus these data points could be used in all three image classification training processes. Overall accuracy for the 2019 land cover map (Landsat-8/Sentinel-2 derived) is 84% (Kappa = 0.81). For the study period, the total areas of invasive plant species substantially increased from 5.79 km2 to 19.16 km2. Distributions of urban and built-up and agriculture classes also slightly increased, suggesting an increased amount of direct human impacts on the island.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Baine, M., Howard, M., Kerr, S., Edgar, G., & Toral, V. (2007). Coastal and marine resource management in the Galapagos Islands and the Archipelago of San Andres: Issues, problems and opportunities. Ocean & Coastal Management, 50(3–4), 148–173.

    Article  Google Scholar 

  • Benítez, F., Mena, C., & Zurita-Arthos, L. (2018). Urban land cover change in ecologically fragile environments: The case of the Galapagos Islands. Land, 7(1), 21.

    Article  Google Scholar 

  • Bivand, R., Keitt, T., Rowlingson, B., & Pebesma, E. (2014). rgdal: Bindings for the geospatial data abstraction library. R package version 0.8-16.

    Google Scholar 

  • Brewington, L., Frizzelle, B. G., Walsh, S. J., Mena, C. F., & Sampedro, C. (2014). Remote sensing of the marine environment: Challenges and opportunities in the Galapagos Islands of Ecuador. In The Galapagos marine reserve (pp. 109–136). Springer.

    Google Scholar 

  • Chander, G., Xiong, X. J., Choi, T. J., & Angal, A. (2010). Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites. Remote Sensing of Environment, 114, 925–939.

    Article  Google Scholar 

  • Chen, J., Zhu, X., Vogelmann, J. E., Gao, F., & Jin, S. (2011). A simple and effective method for filling gaps in Landsat ETM+ SLC-off images. Remote Sensing of Environment, 115(4), 1053–1064.

    Article  Google Scholar 

  • Du, Y., Cihlar, J., Beaubien, J., & Latifovic, R. (2001). Radiometric normalization, compositing, and quality control for satellite high resolution image mosaics over large areas. IEEE Transactions on Geoscience and Remote Sensing, 39(3), 623–634.

    Article  Google Scholar 

  • Epler, B., 2007. Tourism, the economy, population growth, and conservation in Galapagos. Charles Darwin Foundation.

    Google Scholar 

  • Gong, P., Wang, J., Yu, L., Zhao, Y., Zhao, Y., Liang, L., … Li, C. (2013). Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. International Journal of Remote Sensing, 34(7), 2607–2654.

    Article  Google Scholar 

  • Goslee, S. C. (2011). Analyzing remote sensing data in R: The landsat package. Journal of Statistical Software, 43(4), 1–25.

    Article  Google Scholar 

  • Grant, P. R. (1985). Climatic fluctuations on the Galapagos Islands and their influence on Darwin’s finches. Ornithological Monographs, 36, 471–483.

    Google Scholar 

  • Guézou, A., Trueman, M., Buddenhagen, C. E., Chamorro, S., Guerrero, A. M., Pozo, P., & Atkinson, R. (2010). An extensive alien plant inventory from the inhabited areas of Galapagos. PLoS One, 5, e10276.

    Article  Google Scholar 

  • Helmer, E. H., & Ruefenacht, B. (2007). A comparison of radiometric normalization methods when filling cloud gaps in Landsat imagery. Canadian Journal of Remote Sensing, 33(4), 325–340.

    Article  Google Scholar 

  • Hijmans, R. J., van Etten, J., Cheng, J., Mattiuzzi, M., Sumner, M., Greenberg, J. A., … Hijmans, M. R. J. (2015). Package ‘raster’. R package.

    Google Scholar 

  • Izurieta, J. C. (2017). Behavior and trends in tourism in Galapagos between 2007 and 2015. Galapagos Report 2015–2016 (pp. 83–39). Puerto Ayora, Galapagos, Ecuador: GNPD, GCREG, CDF and GC.

    Google Scholar 

  • Janzen, D. T., Fredeen, A. L., & Wheate, R. D. (2006). Radiometric correction techniques and accuracy assessment for Landsat TM data in remote forested regions. Canadian Journal of Remote Sensing, 32(5), 330–340.

    Article  Google Scholar 

  • Kuhn, M. (2008). Building predictive models in R using the caret package. Journal of Statistical Software, 28(5), 1–26.

    Article  Google Scholar 

  • Martinuzzi, S., Gould, W. A., & González, O. M. R. (2007). Creating cloud-free Landsat ETM+ data sets in tropical landscapes: Cloud and cloud-shadow removal. Gen. Tech. Rep. IITF-32., 32. US Department of Agriculture, Forest Service, International Institute of Tropical Forestry.

    Google Scholar 

  • Maxwell, S. K., Schmidt, G. L., & Storey, J. C. (2007). A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images. International Journal of Remote Sensing, 28(23), 5339–5356.

    Article  Google Scholar 

  • McCleary, A. L. (2013). Characterizing contemporary land use/cover change on Isabela Island, Galapagos. In Science and Conservation in the Galapagos Islands (pp. 155-172). Springer, New York, NY.

    Google Scholar 

  • Qiu, S., He, B., Zhu, Z., Liao, Z., & Quan, X. (2017). Improving Fmask cloud and cloud shadow detection in mountainous area for Landsats 4–8 images. Remote Sensing of Environment, 199, 107–119.

    Article  Google Scholar 

  • Rivas-Torres, G. F., Benítez, F. L., Rueda, D., Sevilla, C., & Mena, C. F. (2018). A methodology for mapping native and invasive vegetation coverage in archipelagos: An example from the Galápagos Islands. Progress in Physical Geography: Earth and Environment, 42(1), 83–111.

    Article  Google Scholar 

  • Rodriguez-Galiano, V. F., Ghimire, B., Rogan, J., Chica-Olmo, M., & Rigol-Sanchez, J. P. (2012). An assessment of the effectiveness of a random forest classifier for land-cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 67, 93–104.

    Article  Google Scholar 

  • Roy, D. P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M., & Lindquist, E. (2008). Multi-temporal MODIS–Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data. Remote Sensing of Environment, 112(6), 3112–3130.

    Article  Google Scholar 

  • Sadeghi, V., Ebadi, H., & Ahmadi, F. F. (2013). A new model for automatic normalization of multitemporal satellite images using Artificial Neural Network and mathematical methods. Applied Mathematical Modelling, 37(9), 6437–6445.

    Article  Google Scholar 

  • Schofield, E. K. (1989). Effects of introduced plants and animals on island vegetation: Examples from Galápagos Archipelago. Conservation Biology, 3, 227–239.

    Article  Google Scholar 

  • Seo, D., Kim, Y., Eo, Y., Park, W., & Park, H. (2017). Generation of radiometric, phenological normalized image based on random forest regression for change detection. Remote Sensing, 9(11), 1163.

    Article  Google Scholar 

  • Shao, Y., Campbell, J. B., Taff, G. N., & Zheng, B. (2015). An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data. International Journal of Applied Earth Observation and Geoinformation, 38, 78–87.

    Article  Google Scholar 

  • Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2001). Classification and change detection using Landsat TM data: When and how to correct atmospheric effects? Remote Sensing of Environment, 75, 230–244.

    Article  Google Scholar 

  • Syariz, M. A., Lin, B. Y., Denaro, L. G., Jaelani, L. M., Van Nguyen, M., & Lin, C. H. (2019). Spectral-consistent relative radiometric normalization for multitemporal Landsat 8 imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 147, 56–64.

    Article  Google Scholar 

  • Taboada, T., Rodríguez-Lado, L., Ferro-Vázquez, C., Stoops, G., & Cortizas, A. M. (2016). Chemical weathering in the volcanic soils of Isla Santa Cruz (Galápagos Islands, Ecuador). Geoderma, 261, 160–168.

    Article  CAS  Google Scholar 

  • Tye, A., (2001). Invasive plant problems and requirements for weed risk assessment in the Galapagos Islands. Weed risk assessment, pp. 153–175.

    Google Scholar 

  • Velloso, M. L. F., de Souza, F. J., & Simoes, M. (2002, June). Improved radiometric normalization for land cover change detection: An automated relative correction with artificial neural network. In IEEE International Geoscience and Remote Sensing Symposium (Vol. 6, pp. 3435–3437). IEEE.

    Google Scholar 

  • Walsh, S. J., McCleary, A. L., Heumann, B. W., Brewington, L., Raczkowski, E. J., & Mena, C. F. (2010). Community expansion and infrastructure development: Implications for human health and environmental quality in the Galápagos Islands of Ecuador. Journal of Latin American Geography, 9, 137–159.

    Article  Google Scholar 

  • Walsh, S. J., McCleary, A. L., Mena, C. F., Shao, Y., Tuttle, J. P., González, A., & Atkinson, R. (2008). QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: Implications for control and land use management. Remote Sensing of Environment, 112(5), 1927–1941.

    Article  Google Scholar 

  • Walsh, S. J., & Mena, C. F. (2013). Perspectives for the study of the Galapagos Islands: Complex systems and human–environment interactions. In Science and conservation in the Galapagos Islands (pp. 49–67). Springer.

    Google Scholar 

  • Wan, H., Shao, Y., Campbell, J. B., & Deng, X. W. (2019). Mapping annual urban change using time series Landsat and NLCD. Photogrammetric Engineering and Remote Sensing, 85(10), 715–724.

    Article  Google Scholar 

  • Wang, H., Shao, Y., & Kennedy, L. M. (2014). Temporal generalization of sub-pixel vegetation mapping with multiple machine learning and atmospheric correction algorithms. International Journal of Remote Sensing, 35(20), 7118–7135.

    Article  Google Scholar 

  • White, J., Shao, Y., Kennedy, L., & Campbell, J. (2013). Landscape dynamics on the island of La Gonave, Haiti, 1990–2010. Land, 2(3), 493–507.

    Article  Google Scholar 

  • Yang, X., & Lo, C. P. (2000). Relative radiometric normalization performance for change detection from multi-date satellite images. Photogrammetric Engineering and Remote Sensing, 66, 967–980.

    Google Scholar 

  • Yu, L., Liu, X., Zhao, Y., Yu, C., & Gong, P. (2018). Difficult to map regions in 30 m global land cover mapping determined with a common validation dataset. International Journal of Remote Sensing, 39, 4077–4087.

    Article  Google Scholar 

  • Zhu, Z., Wang, S., & Woodcock, C. E. (2015). Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images. Remote Sensing of Environment, 159, 269–277.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yang Shao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Shao, Y., Wan, H., Rosenman, A., Laso, F.J., Kennedy, L.M. (2020). Evaluating Land Cover Change on the Island of Santa Cruz, Galapagos Archipelago of Ecuador Through Cloud-Gap Filling and Multi-sensor Analysis. In: Walsh, S.J., Riveros-Iregui, D., Arce-Nazario, J., Page, P.H. (eds) Land Cover and Land Use Change on Islands. Social and Ecological Interactions in the Galapagos Islands. Springer, Cham. https://doi.org/10.1007/978-3-030-43973-6_7

Download citation

Publish with us

Policies and ethics