{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:49:13Z","timestamp":1760240953206,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2019,10,10]],"date-time":"2019-10-10T00:00:00Z","timestamp":1570665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771542"],"award-info":[{"award-number":["41771542"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Projects in the National Science &amp; Technology Pillar Program during the 12th Five-year Plan Period","award":["2012BAC04B03"],"award-info":[{"award-number":["2012BAC04B03"]}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["[2017]3109"],"award-info":[{"award-number":["[2017]3109"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate mapping of agricultural fields is needed for many purposes, including irrigation decisions and cadastral management. This paper is concerned with the automated mapping of cropland strips that are common in the North China Plain. These strips are commonly 3\u20138 m in width and 50\u2013300 m in length, and are separated by small ridges that assist with irrigation. Conventional surveying methods are labor-intensive and time-consuming for this application, and only limited performance is possible with very high resolution satellite images. Small Unmanned Aircraft System (sUAS) images could provide an alternative approach to ridge detection and strip mapping. This paper presents a novel method for detecting cropland strips, utilizing centimeter spatial resolution imagery captured by sUAS flying at low altitude (60 m). Using digital surface models (DSM) and ortho-rectified imagery from sUAS data, this method extracts candidate ridge locations by surface roughness segmentation in combination with geometric constraints. This method then exploits vegetation removal and morphological operations to refine candidate ridge elements, leading to polyline-based representations of cropland strip boundaries. This procedure has been tested using sUAS data from four typical cropland plots located approximately 60 km west of Jinan, China. The plots contained early winter wheat. The results indicated an ability to detect ridges with comparatively high recall and precision (96.8% and 95.4%, respectively). Cropland strips were extracted with over 98.9% agreement relative to ground truth, with kappa coefficients over 97.4%. To our knowledge, this method is the first to attempt cropland strip mapping using centimeter spatial resolution sUAS images. These results have demonstrated that sUAS mapping is a viable approach for data collection to assist in agricultural land management in the North China Plain.<\/jats:p>","DOI":"10.3390\/rs11202343","type":"journal-article","created":{"date-parts":[[2019,10,11]],"date-time":"2019-10-11T03:07:11Z","timestamp":1570763231000},"page":"2343","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automated Mapping of Typical Cropland Strips in the North China Plain Using Small Unmanned Aircraft Systems (sUAS) Photogrammetry"],"prefix":"10.3390","volume":"11","author":[{"given":"Jianyong","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, Department of Surveying and Land Use, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"given":"Yanling","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, Department of Surveying and Land Use, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"given":"A. Lynn","family":"Abbott","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA 24061, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3649-835X","authenticated-orcid":false,"given":"Randolph H.","family":"Wynne","sequence":"additional","affiliation":[{"name":"Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA 24061, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6225-6787","authenticated-orcid":false,"given":"Zhenqi","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"given":"Yuzhu","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, Department of Surveying and Land Use, China University of Mining and Technology-Beijing, Beijing 100083, China"}]},{"given":"Shuaishuai","family":"Tian","sequence":"additional","affiliation":[{"name":"Institute of Land Reclamation and Ecological Restoration, Department of Surveying and Land Use, China University of Mining and Technology-Beijing, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1038\/nature25785","article-title":"Pursuing sustainable productivity with millions of smallholder farmers","volume":"555","author":"Cui","year":"2018","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1038\/nature19368","article-title":"Closing yield gaps in china by empowering smallholder farmers","volume":"537","author":"Zhang","year":"2016","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Dong, Q.H., Liu, J., Wang, L.M., Chen, Z.X., and Gallego, J. (2017). Estimating crop area at county level on the north china plain with an indirect sampling of segments and an adapted regression estimator. Sensors, 17.","DOI":"10.3390\/s17112638"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agwat.2014.07.010","article-title":"Winter wheat with subsurface drip irrigation (SDI): Crop coefficients, water-use estimates, and effects of SDI on grain yield and water use efficiency","volume":"146","author":"Gao","year":"2014","journal-title":"Agric. Water Manag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1086\/edcc.36.s3.1566543","article-title":"The household responsibility system in China\u2019s agricultural reform: A theoretical and empirical study","volume":"36","author":"Lin","year":"1988","journal-title":"Econ. Dev. Cult. Chang."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1007\/s11119-013-9322-9","article-title":"Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard","volume":"14","author":"Nicols","year":"2013","journal-title":"Precis. Agric."},{"key":"ref_7","first-page":"666","article-title":"A novel remote sensing approach for prediction of maize yield under different conditions of nitrogen fertilization","volume":"7","author":"Masuka","year":"2016","journal-title":"Front. Plant Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.rse.2017.06.033","article-title":"MODIS phenology-derived, multi-year distribution of conterminous U.S. crop types","volume":"198","author":"Massey","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2014.01.006","article-title":"Automated crop field extraction from multi-temporal Web Enabled Landsat Data","volume":"144","author":"Yan","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.rse.2017.08.027","article-title":"Detection of cropland field parcels from Landsat imagery","volume":"201","author":"Graesser","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1016\/j.rse.2017.10.005","article-title":"Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis","volume":"204","author":"Belgiu","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.rse.2019.01.007","article-title":"Gradients in urban material composition: A new concept to map cities with spaceborne imaging spectroscopy data","volume":"223","author":"Jilge","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_13","first-page":"130","article-title":"Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms","volume":"75","author":"Planas","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.isprsjprs.2019.04.003","article-title":"A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data","volume":"152","author":"Ashapure","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"Structure-from-Motion photogrammetry: A low-cost, effective tool for geoscience applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.geomorph.2016.11.009","article-title":"An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection","volume":"278","author":"Cook","year":"2017","journal-title":"Geomorphology"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Crommelinck, S., Bennett, R., Gerke, M., Nex, F., Yang, M., and Vosselman, G. (2016). Review of automatic feature extraction from high-resolution optical sensor data for UAV-based cadastral mapping. Remote Sens., 8.","DOI":"10.3390\/rs8080689"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.rse.2017.06.007","article-title":"Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery","volume":"198","author":"Jin","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1109\/JSTARS.2018.2793849","article-title":"Automatic tobacco plant detection in UAV images via deep neural networks","volume":"11","author":"Fan","year":"2018","journal-title":"IEEE J. Select. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Poblete-Echeverra, C., Olmedo, G.F., Ingram, B., and Bardeen, M. (2017). Detection and segmentation of vine canopy in ultra-high spatial resolution RGB imagery obtained from unmanned aerial vehicle (UAV): A case study in a commercial vineyard. Remote Sens., 9.","DOI":"10.3390\/rs9030268"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Al-Rawabdeh, A., He, F.N., Moussa, A., El-Sheimy, N., and Habib, A. (2016). Using an unmanned aerial vehicle-based digital imaging system to derive a 3D point cloud for landslide scarp recognition. Remote Sens., 8.","DOI":"10.3390\/rs8020095"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.rse.2011.10.007","article-title":"Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera","volume":"117","author":"Berni","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.geomorph.2016.12.003","article-title":"Can DEM time series produced by UAV be used to quantify diffuse erosion in an agricultural watershed?","volume":"280","author":"Pineux","year":"2017","journal-title":"Geomorphology"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.geomorph.2017.12.027","article-title":"McGET: A rapid image-based method to determine the morphological characteristics of gravels on the Gobi desert surface","volume":"304","author":"Mu","year":"2018","journal-title":"Geomorphology"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhang, S., Lippitt, C., Bogus, S., and Neville, P. (2016). Characterizing pavement surface distress conditions with hyper-spatial resolution natural color aerial photography. Remote Sens., 8.","DOI":"10.3390\/rs8050392"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"4852","DOI":"10.1080\/01431161.2018.1490504","article-title":"The impact of small unmanned airborne platforms on passive optical remote sensing: A conceptual perspective","volume":"39","author":"Lippitt","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"295","DOI":"10.5194\/hess-21-295-2017","article-title":"Attributing regional trends of evapotranspiration and gross primary productivity with remote sensing: A case study in the North China Plain","volume":"21","author":"Mo","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.still.2017.03.013","article-title":"Effects of deep vertical rotary tillage on dry matter accumulation and grain yield of summer maize in the Huang-Huai-Hai Plain of China","volume":"170","author":"Zhai","year":"2017","journal-title":"Soil Tillage Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.agee.2015.03.016","article-title":"Carbon budget of a winter-wheat and summer-maize rotation cropland in the north china plain","volume":"206","author":"Wang","year":"2015","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1007\/s00254-003-0838-6","article-title":"GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey)","volume":"44","author":"Cevik","year":"2003","journal-title":"Environ. Geol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2950","DOI":"10.1109\/TGRS.2006.876704","article-title":"A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery","volume":"44","author":"Zhang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2111\/07-011.1","article-title":"Classification of digital photography for measuring productive ground cover","volume":"61","author":"Rotz","year":"2008","journal-title":"Rangeland Ecol. Manag."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hassanein, M., Lari, Z., and El-Sheimy, N. (2018). A new vegetation segmentation approach for cropped fields based on threshold detection from Hue histograms. Sensors, 18.","DOI":"10.3390\/s18041253"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/34.368156","article-title":"Decomposition of arbitrarily shaped morphological structuring elements","volume":"17","author":"Park","year":"1995","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1538","DOI":"10.1109\/JSTARS.2012.2199085","article-title":"Semi-automated road detection from high resolution satellite images by directional morphological enhancement and segmentation techniques","volume":"5","author":"Chaudhuri","year":"2012","journal-title":"IEEE J. Select. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1109\/34.161346","article-title":"Thinning methodologies: A comprehensive survey","volume":"14","author":"Lam","year":"1992","journal-title":"IEEE Trans. Pattern Anal."},{"key":"ref_38","unstructured":"Hough, P.V.C. (1962). Method and Means for Recognizing Complex Patterns. (No. 3069654), U.S. Patent."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/361237.361242","article-title":"Use of the Hough transformation to detect lines and curves in pictures","volume":"15","author":"Duda","year":"1972","journal-title":"Commun. ACM"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1109\/TSMC.1978.4309944","article-title":"Image segmentation and feature extraction","volume":"8","author":"Sklansky","year":"1978","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1016\/j.patcog.2014.08.027","article-title":"A survey of Hough Transform","volume":"48","author":"Mukhopadhyay","year":"2015","journal-title":"Pattern Recogn."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1016\/j.cad.2011.03.006","article-title":"Shape preserving data reduction for 3D surface points","volume":"43","author":"Ma","year":"2011","journal-title":"Comput. Aided Des."},{"key":"ref_43","first-page":"151","article-title":"Evaluation of automatic road extraction","volume":"32","author":"Heipke","year":"1997","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_44","first-page":"1","article-title":"A systematic extraction approach for mapping glacial lakes in high mountain regions of Asia","volume":"12","author":"Zhao","year":"2018","journal-title":"IEEE J. Select. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_45","first-page":"708","article-title":"Fully automatic road network extraction from satellite images","volume":"3","author":"Tuncer","year":"2007","journal-title":"IEEE Int. Conf. Recent Adv. Space Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3906","DOI":"10.1109\/TGRS.2011.2136381","article-title":"Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images","volume":"49","author":"Das","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2993","DOI":"10.1109\/TITS.2017.2665658","article-title":"Road recognition from remote sensing imagery using incremental learning","volume":"18","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Intell. Transp."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"19307","DOI":"10.3390\/s141019307","article-title":"Automatic crack detection and classification method for subway tunnel safety monitoring","volume":"14","author":"Zhang","year":"2014","journal-title":"Sensors"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"17654","DOI":"10.1007\/s11356-018-1961-y","article-title":"Energy and environmental impact analysis of rice cultivation and straw management in northern Thailand","volume":"25","author":"Yodkhum","year":"2018","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1080\/09669582.2016.1224890","article-title":"Cognition of disaster risk in a tourism community: An agricultural heritage system perspective","volume":"25","author":"Sun","year":"2017","journal-title":"J. Sustain. Tour."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/j.isprsjprs.2014.06.018","article-title":"A new landscape metric for the identification of terraced sites: The Slope Local Length of Auto-Correlation (SLLAC)","volume":"96","author":"Sofia","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1111\/phor.12229","article-title":"True orthophoto generation using line segment matches","volume":"33","author":"Wang","year":"2018","journal-title":"Photogramm. Rec."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Duan, F.Z., Wan, Y.C., and Deng, L. (2017). A novel approach for coarse-to-fine windthrown tree extraction based on unmanned aerial vehicle images. Remote Sens., 9.","DOI":"10.3390\/rs9040306"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.autcon.2017.06.024","article-title":"Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography","volume":"83","author":"Omar","year":"2017","journal-title":"Autom. Constr."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1365","DOI":"10.14358\/PERS.70.12.1365","article-title":"Road extraction using SVM and image segmentation","volume":"70","author":"Song","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/0924-2716(95)98233-P","article-title":"Road extraction from aerial and satellite images by dynamic programming","volume":"50","author":"Gruen","year":"1995","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Xu, Y.Y., Xie, Z., Feng, Y.X., and Chen, Z.L. (2018). Road extraction from high-resolution remote sensing imagery using deep learning. Remote Sens., 10.","DOI":"10.3390\/rs10091461"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"4653","DOI":"10.1080\/01431160701250382","article-title":"Classified road detection from satellite images based on perceptual organization","volume":"28","author":"Yang","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1016\/j.patrec.2009.12.018","article-title":"Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images","volume":"31","author":"Valero","year":"2010","journal-title":"Pattern Recogn. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"4548","DOI":"10.1109\/JSTARS.2014.2327226","article-title":"A decision-tree classifier for extracting transparent plastic-mulched landcover from Landsat-5 TM images","volume":"7","author":"Lu","year":"2014","journal-title":"IEEE J. Select. Top. Appl. Earth Obs. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/20\/2343\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:28:58Z","timestamp":1760189338000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/20\/2343"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,10]]},"references-count":60,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["rs11202343"],"URL":"https:\/\/doi.org\/10.3390\/rs11202343","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,10,10]]}}}