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Analyzing Remote Sensing Data in R: The landsat Package

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  • Goslee, Sarah C.

Abstract

Research and development on atmospheric and topographic correction methods for multispectral satellite data such as Landsat images has far outpaced the availability of those methods in geographic information systems software. As Landsat and other data become more widely available, demand for these improved correction methods will increase. Open source R statistical software can help bridge the gap between research and implementation. Sophisticated spatial data routines are already available, and the ease of program development in R makes it straightforward to implement new correction algorithms and to assess the results. Collecting radiometric, atmospheric, and topographic correction routines into the landsat package will make them readily available for evaluation for particular applications.

Suggested Citation

  • Goslee, Sarah C., 2011. "Analyzing Remote Sensing Data in R: The landsat Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i04).
    • Handle: RePEc:jss:jstsof:v:043:i04
    DOI: http://hdl.handle.net/10.18637/jss.v043.i04
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    Cited by:

    1. Uday Pimple & Asamaporn Sitthi & Dario Simonetti & Sukan Pungkul & Kumron Leadprathom & Amnat Chidthaisong, 2017. "Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand," Sustainability, MDPI, vol. 9(2), pages 1-26, February.
    2. Alencar, Paulo Gustavo de & Espindola, Giovana Mira de & Carneiro, Eduilson Lívio Neves da Costa, 2018. "Dwarf cashew crop expansion in the Brazilian semiarid region: Assessing policy alternatives in Pio IX, Piauí," Land Use Policy, Elsevier, vol. 79(C), pages 1-9.
    3. Bivand, Roger, 2011. "Geocomputation and open source software: components and software stacks," Discussion Paper Series in Economics 23/2011, Norwegian School of Economics, Department of Economics.
    4. Lalan Kumar Jha & Deepak Khare, 2017. "Detection and delineation of glacial lakes and identification of potentially dangerous lakes of Dhauliganga basin in the Himalaya by remote sensing techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(1), pages 301-327, January.
    5. Giovana Mira Espindola & Elayne Silva Figueredo & Péricles Picanço Júnior & Antonio Aderson Reis Filho, 2021. "Cropland expansion as a driver of land-use change: the case of Cerrado-Caatinga transition zone in Brazil," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 17146-17160, November.
    6. Pebesma, Edzer & Bivand, Roger & Ribeiro, Paulo Justiniano, 2015. "Software for Spatial Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i01).

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