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Identification of Terrace Boundaries from DEMs Using Multidirectional Hill-Shading

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Artificial Intelligence and Security (ICAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13338))

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Abstract

Mapping and monitoring terraces are important for maintaining agricultural production and evaluating soil-and-water conservation. However, mapping all boundaries of individual terraces is still a challenge. In this study, a multidirectional hill-shading method based on digital elevation models (DEMs) is proposed for terrace boundary mapping. First, hill-shading in four directions was simulated using 1-m DEM. Second, the mean brightness image of four hill-shading maps was calculated. Meanwhile, according to the brightness difference between terrace boundaries and terrace areas, a threshold was used to identify terrace boundaries from the mean brightness image. Third, loess shoulder lines extracted by the positive-negative terrain method were used to remove non-terraced areas (noise area). Finally, terrace boundaries were obtained by vectorization and compared with reference data. Results from two study areas in the Loess Plateau of China show that the producer’s accuracy (PA) and user’s accuracy (UA) ranged from 80.07% to 83.08% and 75.42% to 78.17%, respectively. The proposed method is practicable and applicable for terrace boundary mapping. This work is beneficial to terraced land maintenance, agricultural production management, and monitoring soil erosion.

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Author information

Authors and Affiliations

  1. School of Marine Technology and Surveying and Mapping, Jiangsu Ocean University, Lianyungang, 222000, China

    Peng Liu

  2. Department of Industrial and Mining Architecture, Bijie Vocational and Technical College, Bijie, 551700, China

    Kai Zeng & Ji Dai

  3. School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Wen Dai

  4. Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015, Lausanne, Switzerland

    Wen Dai

Authors
  1. Peng Liu
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  2. Kai Zeng
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  3. Ji Dai
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  4. Wen Dai
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Corresponding author

Correspondence to Wen Dai .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Conflicts of Interest

The authors declare that they have no conflicts of interest to report regarding the present study.

Funding Statement

We are grateful for the financial support provided by the National Natural Science Foundation of China [grant numbers 41771415 and 41871313].

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Liu, P., Zeng, K., Dai, J., Dai, W. (2022). Identification of Terrace Boundaries from DEMs Using Multidirectional Hill-Shading. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13338. Springer, Cham. https://doi.org/10.1007/978-3-031-06794-5_18

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  • DOI: https://doi.org/10.1007/978-3-031-06794-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06793-8

  • Online ISBN: 978-3-031-06794-5

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