[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

Terrace extraction based on remote sensing images and digital elevation model in the loess plateau, China

  • Research Article
  • Published:
Earth Science Informatics Aims and scope Submit manuscript

Abstract

Terraces are important objects of soil and water conservation and land use surveys in the Loess Plateau and considerably impact soil erosion and agricultural production. Obtaining the spatial distribution of terraces has great significance for soil and water conservation research and government policy-making. A new method of terrace extraction was proposed in this study based on remote sensing images and digital elevation model (DEM) used as experimental data. The extraction method combines Fourier transform and digital terrain analysis. First, by analyzing the spatial and frequency domain characteristics of the terraced image, we determined the analysis window to be 50 × 50, whereas the area having a direction maximum energy value greater than 0.25 and image standard deviation greater than 2000 was considered as the terraced candidate. Then, the positive terrain was automatically extracted from the DEM based on the regional growth method, and the terraces on the positive terrain were obtained. After a series of morphological image processing methods were conducted, the final terraces were extracted. The results showed that the accuracy of drawing and user accuracy of terrace extraction were 79.0% and 73.5%, respectively. Compared with the object-oriented method, it was found that the proposed method was more reliable and accurate. This method developed in this study has the characteristics of simple operation, strong universality, and high precision and can be applied to soil and water conservation monitoring and land use surveys in the Loess Plateau.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Agnoletti M, Cargnello G, Gardin L, Santoro A, Bazzoffi P, Sansone L, Pezza L, Belfiore N (2011) Traditional landscape and rural development: comparative study in three terraced areas in northern, central and southern Italy to evaluate the efficacy of GAEC standard 4.4 of cross compliance. Ital J Agron 6:121–139

  • Capolupoa A, Kooistrab L, Bocciaa L (2018) A novel approach for detecting agricultural terraced landscapes from historical and contemporaneous photogrammetric aerial photos. Int J Appl Earth Obs Geoinformation 73:800–810

    Article  Google Scholar 

  • Clarke JDA, Gibson D, Apps H (2010) The use of LiDAR in applied interpretive landform mapping for natural resource management, Murray River alluvial plain, Australia. Int J Remote Sens 31(23):6275–6296

    Article  Google Scholar 

  • Dai W, Na JM, Huang N, Hu GH, Yang X, Tang GA, Xiong LY, Li FY (2019) Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images. Int J Geogr Inf Sci. https://doi.org/10.1080/13658816.2019.1650363

  • Dai W, Na JM, Yang X, Cao JJ (2017) An automatic retrieval method for artificial terrace based on illumination model of DEM shading. Journal of Geo-information Science 19(6):754–762

    Google Scholar 

  • Demoulin A, Bovy B, Rixhon G, Cornet Y (2007) An automated method to extract fluvial terraces from digital elevation models: the Vesdre valley, a case study in eastern Belgium. Geomorphology 91(1–2):0–64

  • Diaz-Varela RA, Zarco-Tejada PJ, Angileri V, Loudjani P (2014) Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle. J Environ Manag 134:117–126

    Article  Google Scholar 

  • Eckert S, Tesfay GS, Hurni H, Kohler T (2017) Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data. J Environ Manag 193:592–606

    Article  Google Scholar 

  • European Commission (2012) The common agricultural policy a partnership between Europe and farmers. Luxembourg: Directorate General Agriculture and Rural Development, Publications Office of the European Union

  • Faulkner H, Ruiz J, Zukowskyj P, Downward S (2003) Erosion risk associated with rapid and extensive agricultural clearances on dispersive materials in Southeast Spain. Environ Sci Pol 6(1):115–127

  • Fu B, Chen L, Ma K, Zhou H, Wang J (2000) The relationships between land use and soil conditions in the hilly area of the loess plateau in northern Shaanxi, China. Catena 39(1):69–78

    Article  Google Scholar 

  • Fu B (1989) Soil erosion and its control in the loess plateau of China. Soil Use Manag 5:76–82

    Article  Google Scholar 

  • Gao H, Li ZB, Li P, Jia LL, Zhang X (2012) Quantitative study on influences of terraced field construction and check-dam siltation on soil erosion. J Geogr Sci 22(5):946–960

  • Hou QQ (2013) Soil conservation practices information extraction from remote sensing images object-oriented method. Dissertation, Northwest A&F university

  • Karydas CG, Sekuloska T, Sarakiotis I (2005) Fine scale mapping of agricultural landscape features to be used in environmental risk assessment in an olive cultivation area. IASME Transactions 2(4):582–589

    Google Scholar 

  • Karydas CG, Sekuloska T, Silleos GN (2009) Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete. Environ Monit Assess 149(1–4):19–28

    Article  Google Scholar 

  • Kou Q, Wang YC, Mu ZL, Wang ZH (2006) Study on terrace monitoring method based on SPOT5 satellite image. Soil and water conservation in China 10:65–66

    Google Scholar 

  • Kou Q, Wang YC, Wu YH, Zhang XN, Du P (2005) Research on terrace monitoring method based on high-resolution satellite images. Soil and water conservation in China 12:24–25

    Google Scholar 

  • Li DK, Liu AL, Deng FD, Zhang JH, Zhou J (2003) The Investigation of Sloping Cultivated Land on the Loess Plateau with 3s Technology. Proceedings of SPIE-The International Society for Optical Engineering 4890:952–959

  • Li H (2014) Research on terrace DEM formation method. Dissertation, Northwest university

  • Li M, Yang X, Chen PP, Xiong LY (2016) Method of automatic shoulder line extraction in the loess hilly area based on point cloud data. Journal of Geo-information Science 18(7):869–877

    Google Scholar 

  • Li X (2017) Improved extraction method of terrace point cloud feature surface based on normal vector. Digital technology & application 4(99–100):103

    Google Scholar 

  • Li XH, Yang J, Zhao CY, Wang B (2014) Runoff and sediment from orchard terraces in southeastern China. Land Degrad Dev 25(2):184–192

    Article  Google Scholar 

  • Li Y, Gong JH, Wang DC, An LP, Li R (2013) Sloping farmland identification using hierarchical classification in the xi-He region of China. Int J Remote Sens 34(2):545–562

    Article  Google Scholar 

  • Li ZF, Zhu GC, Dong TF (2011) Application of GLCM -based texture features to remote sensing image classification. Geol Explor 47(3):456–461

    Google Scholar 

  • Li ZG, Liu XC, Liu JX, Gao YF (2010) Plan of soil and water conservation survey in national census for water resources. Bulletin of Soil & Water Conservation 30:87–91

    Google Scholar 

  • Liu K, Ding H, Tang GA, Na JM, Huang XL, Xue ZG, Yang X, Li FY (2016) Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV) on the Chinese Loess Plateau. ISPRS International Journal of Geo-Information 5(12):238

  • Liu K, Ding H, Tang GA, Zhu AX, Yang X, Jiang S, Cao JJ (2017) An object-based approach for two-level gully feature mapping using high-resolution DEM and imagery: a case study on hilly loess plateau region, China. Chin Geogr Sci 27(3):415–430

    Article  Google Scholar 

  • Liu W, Li FY, Xiong LY, Liu SL, Wang K (2016) Shoulder line extraction in the loess plateau based on region growing algorithm. Int J Georgr Inf Sci 18:220–226

    Google Scholar 

  • Liu XY, Yang ST, Wang FG, He XZ, Ma HB, Luo Y (2014) Analysis on sediment yield reduced by current terrace and shrubs-herbs-arbor vegetation in the loess plateau. J Hydraul Eng 45:1293–1300

    Google Scholar 

  • Liu YM, Yang QK, Tang GA (2004) Remote sensing classification method of slope field in loess hilly and gully area of northern Shaanxi Province. J Soil Water Conserv 24:51–54

    Google Scholar 

  • Louwagie G, Gay SH, Sammeth F, Ratinger T (2011) The potential of European Union policies to address soil degradation in agriculture. Land Degrad Dev 22(1):5–17

    Article  Google Scholar 

  • Macmillan RA, Martin TC, Earle TJ, Mcnabb DH (2003) Automated analysis and classification of landforms using high-resolution digital elevation data: applications and issues. Can J Remote Sens 29(5):592–606

  • Martínez-Casasnovas JA, Ramos MC, Cots-Folch R (2010) Influence of the EU CAP on terrain morphology and vineyard cultivation in the Priorat region of N.E. Spain. Land Use Policy 27(1):11–21

  • Modica G, Salvatore Praticò, Fazio SD (2017). Abandonment of traditional terraced landscape: A change detection approach (a case study in Costa Viola, Calabria, Italy). Land Degrad Dev 28(8):2608–2622

  • Na JM, Yang X, Dai W, Li M, Xion LY, Zhu R, Tang GA (2018) Bidirectional DEM relief shading method for extraction of gully shoulder line in loess tableland area. Phys Geogr 39(4):368–386

    Article  Google Scholar 

  • Rey Benayas JM, Martins A, Nicolau JM, Schulz JJ (2007) Abandonment of agricultural land: an overview of drivers and consequences. Cab Rev Perspect Agric Veterinary Sci Nutr Nat Resour 2(057):14

    Google Scholar 

  • Schönbrodt-Stitt S, Behrens T, Schmidt K, Shi X, Scholten T (2013) Degradation of cultivated bench terraces in the three gorges area: field mapping and data mining. Ecol Indic 34:478–493

    Article  Google Scholar 

  • Sofia G, Marinello F, Tarolli P (2014) A new landscape metric for the identification of terraced sites: the slope local length of auto-correlation (SLLAC). ISPRS J Photogramm Remote Sens 96:123–133

    Article  Google Scholar 

  • Sofia G, Marinello F, Tarolli P (2016) Metrics for quantifying anthropogenic impacts on geomorphology: road networks. Earth Surf Process Landf 41(2):240–255

    Article  Google Scholar 

  • Tarolli P, Preti F, Romano N (2014) Terraced landscapes: from an old best practice to a potential hazard for soil degradation due to land abandonment. Anthropocene 6:10–25

    Article  Google Scholar 

  • Xue MD, Zhang HM, Yang JT, Li XS (2019). Extraction of terrace information based on UAV image and topographic index. Application Research of Computers 36(9)

  • Yang L (2006) A research on extraction soil and water conversation information based on spots images. Dissertation, Northwest University

  • Yu H, Liu ZH, Zhang XP, Li R (2008) Extraction of terraced field texture features based on Fourier transformation. Remote Sensing for Land & Resources 2:39–42

    Google Scholar 

  • Zhang Y, Shi M, Zhao X, Wang XJ, Luo ZD, Zhao Y (2017) Methods for automatic identification and extraction of terraces from high spatial resolution satellite data (China-GF-1). Int Soil and Water Conserv Res 5(1):17–25

    Article  Google Scholar 

  • Zhang YG (2016) Terrace information extraction form remote sensing image based on object-oriented classification method. Dissertation, Northwest A&F University

  • Zhao BY, Ma N, Yang J, Li ZH, Wang QX (2012). Extracting features of soil and water conservation measures from remote sensing image of different resolution levels: accuracy analysis. Bull Soil Water Conserv 32(4) (164-157)

  • Zhao DB (2007). The analysis and extraction of soil conservation practices information based on hi-resolution remote sensing images. Dissertation, Northwest A&F University

  • Zhao HQ, Fang X, Ding H, Strobl J, Xiong LY, Na JM, Tang GA (2017) Extraction of terraces on the loess plateau from high-resolution DEMs and imagery utilizing object-based image analysis. ISPRS Int J Geo Inf 6(6):157

    Article  Google Scholar 

  • Zhao X, Wang XJ, Zhao Y, Luo ZD, Xu YL, Guo H, Zhang Y (2016) A feasibility analysis on methodology of terraced extraction using Fourier transformation based on domestic hi-resolution remote sensing image of GF-1 satellite. SWCC 1:63–65

    Google Scholar 

  • Zhou Y, Tang GA, Wang C, Xiao CC, Dong YF, Sun JL (2010) Automatic segmentation of loess positive and negative terrains based on high resolution grid DEMs. Sci Geogr Sin 30(2):261–266

    Google Scholar 

  • Zhu SJ, Tang GA, Zhang W, Zhao WD (2011) Rapid modeling method for terrace digital elevation model. Bulletin of Surveying and Mapping 4(68–70):82

    Google Scholar 

Download references

Acknowledgements

We are grateful for the financial support from the National Natural Science Foundation of China (Grant Nos. 41571383, 41801321, 41871313, 41930102), the Priority Academic Program Development of Jiangsu Higher Education Institutions (164320H116). The constructive criticisms and suggestions from anonymous reviewers are also gratefully acknowledged.

Author information

Authors and Affiliations

  1. School of Geography, Nanjing Normal University, Nanjing, 210023, China

    Lanhua Luo, Fayuan Li, Ziyang Dai, Xue Yang & Wei Liu

  2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China

    Lanhua Luo, Fayuan Li, Ziyang Dai, Xue Yang & Wei Liu

  3. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, 210023, China

    Lanhua Luo, Fayuan Li, Ziyang Dai, Xue Yang & Wei Liu

  4. School of Environment Science, Nanjing Xiaozhuang University, Nanjing, 211171, China

    Xuan Fang

Authors
  1. Lanhua Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fayuan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ziyang Dai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xue Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xuan Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fayuan Li.

Additional information

Communicated by: H. Babaie

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, L., Li, F., Dai, Z. et al. Terrace extraction based on remote sensing images and digital elevation model in the loess plateau, China. Earth Sci Inform 13, 433–446 (2020). https://doi.org/10.1007/s12145-020-00444-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12145-020-00444-x

Keywords

Search

Navigation