{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T21:28:13Z","timestamp":1778966893186,"version":"3.51.4"},"reference-count":43,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T00:00:00Z","timestamp":1590364800000},"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":["41901062"],"award-info":[{"award-number":["41901062"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The soil spectral dynamic feedback captured from high temporal resolution remote sensing data, such as MODIS, during the soil drying process after a rainfall could assist with digital soil mapping. However, this method is ineffective in utilizing the images with a relatively high spatial resolution. There are an insufficient number of images in the soil drying process since those high spatial resolution images tend to have a low temporal resolution. This study is aimed at generating soil spectral dynamic feedback by integrating the feedback captured from the images with a high spatial resolution during the process of multiple drying after different rainfall events. The Landsat 8 data with a temporal resolution of 16 day was exemplified. Each single spectral feedback obtained from Landsat 8 was first adjusted to eliminate the impact of different rainfall magnitudes. Then, the soil spectral dynamic feedback was reorganized and generated based on the adjusted feedback. Finally, the soil spectral dynamic feedback generated based on Landsat 8 was used for mapping topsoil texture and compared with the mapping results based on the MODIS data and the fusion data of MODIS and Landsat 8. As revealed by the results, not only could the generated soil spectral dynamic feedback based on Landsat 8 data improve the details of the spatial distribution of soil texture, but it also enhances the accuracy of mapping. The mapping accuracy based on Landsat 8 data is higher than that based on the MODIS data and fusion data. The improvements of accuracy are more obvious in the areas with more complex surface conditions. This study widens the scope of application for soil spectral dynamic feedback and provides support for large-scale and high-precision digital soil mapping.<\/jats:p>","DOI":"10.3390\/rs12101691","type":"journal-article","created":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T11:42:02Z","timestamp":1590406922000},"page":"1691","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["The Generation of Soil Spectral Dynamic Feedback Using Landsat 8 Data for Digital Soil Mapping"],"prefix":"10.3390","volume":"12","author":[{"given":"Canying","family":"Zeng","sequence":"first","affiliation":[{"name":"Institute of Land and Urban-rural Development, Zhejiang University of Finance &amp; Economics, Hangzhou 310018, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China"},{"name":"State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5725-0460","authenticated-orcid":false,"given":"A-Xing","family":"Zhu","sequence":"additional","affiliation":[{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing 210023, China"},{"name":"State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, 1 Wenyuan Road, Nanjing 210023, China"},{"name":"Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,25]]},"reference":[{"key":"ref_1","first-page":"3","article-title":"Chapter 1. spatial soil information systems and spatial soil inference systems: Perspectives for digital soil mapping","volume":"31","author":"Lagacherie","year":"2006","journal-title":"Dev. Soil Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.geoderma.2015.07.017","article-title":"Digital soil mapping: A brief history and some lessons","volume":"264","author":"Minasny","year":"2016","journal-title":"Geoderma"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.geoderma.2009.06.003","article-title":"Multi-criteria characterization of recent digital soil mapping and modeling approaches","volume":"152","author":"Grunwald","year":"2009","journal-title":"Geoderma"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0016-7061(03)00223-4","article-title":"On digital soil mapping","volume":"117","author":"McBratney","year":"2003","journal-title":"Geoderma"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e00255","DOI":"10.1016\/j.geodrs.2020.e00255","article-title":"Impressions of digital soil maps: The good, the not so good, and making them ever better","volume":"20","author":"Arrouays","year":"2020","journal-title":"Geoderma Reg."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1338","DOI":"10.2136\/sssaj2004.0154","article-title":"Spatial variability analysis of soil physical properties of alluvial soils","volume":"69","author":"Iqbal","year":"2005","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1016\/j.cageo.2007.05.001","article-title":"About regression-kriging: From equations to case studies","volume":"33","author":"Hengl","year":"2007","journal-title":"Comput. Geosci.-UK"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.ecolind.2013.12.015","article-title":"Mapping soil organic matter in low-relief areas based on land surface diurnal temperature difference and a vegetation index","volume":"39","author":"Zhao","year":"2014","journal-title":"Ecol. Indic."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.apgeog.2009.10.006","article-title":"Human activity impact on the heterogeneity of a Mediterranean landscape","volume":"30","author":"Geri","year":"2010","journal-title":"Appl. Geogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.rse.2007.02.007","article-title":"Using remotely-sensed estimates of soil moisture to infer soil texture and hydraulic properties across a semi-arid watershed","volume":"110","author":"Santanello","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"557","DOI":"10.5721\/EuJRS20144731","article-title":"Evaluation of Landsat TM5 multispectral data for automated mapping of surface soil texture and organic matter in GIS","volume":"47","author":"Ahmed","year":"2014","journal-title":"Eur. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1177\/0309133309346644","article-title":"Remote sensing of soil surface properties","volume":"33","author":"Anderson","year":"2009","journal-title":"Prog. Phys. Geog."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.catena.2016.05.023","article-title":"Spatial variability of soil organic matter using remote sensing data","volume":"145","author":"Mirzaee","year":"2016","journal-title":"Catena"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2013.02.027","article-title":"Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation","volume":"134","author":"Paloscia","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_15","first-page":"S171","article-title":"Mapping soil organic matter based on land degradation spectral response units using Hyperion images","volume":"12","author":"Wang","year":"2010","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bousbih, S., Zribi, M., Pelletier, C., Gorrab, A., Lilichabaane, Z., Baghdadi, N., Aissa, N.B., and Mougenot, B. (2019). Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2. Remote Sens., 11.","DOI":"10.3390\/rs11131520"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"102645","DOI":"10.1016\/j.jvcir.2019.102645","article-title":"Inversion of organic matter content in wetland soil based on Landsat 8 remote sensing image","volume":"64","author":"Zhai","year":"2019","journal-title":"J. Vis. Commun. Image R."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"722","DOI":"10.2136\/sssaj2002.7220","article-title":"Moisture effects on soil reflectance","volume":"66","author":"Lobell","year":"2002","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, D.C., Zhang, G.N., Rossiter, D.G., and Zhang, J.H. (2015). The prediction of soil texture from Vis-NIR spectra under varying moisture conditions. Soil Sci. Soc. Am. J.","DOI":"10.2136\/sssaj2015.10.0379"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.geoderma.2011.05.007","article-title":"Soil texture mapping over low relief areas using land surface feedback dynamic patterns extracted from MODIS","volume":"171\u2013172","author":"Liu","year":"2012","journal-title":"Geoderma"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/S1002-0160(12)60025-3","article-title":"Mapping soil texture of a plain area using fuzzy-c-means clustering method based on land surface diurnal temperature difference","volume":"22","author":"Wang","year":"2012","journal-title":"Pedosphere"},{"key":"ref_22","first-page":"126","article-title":"Unification of soil feedback patterns under different evaporation conditions to improve soil differentiation over flat area","volume":"49","author":"Guo","year":"2016","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"11801","DOI":"10.3390\/rs70911801","article-title":"Data-Gap Filling to Understand the Dynamic Feedback Pattern of Soil","volume":"7","author":"Guo","year":"2015","journal-title":"Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.ecolind.2016.08.023","article-title":"The impact of rainfall magnitude on the performance of digital soil mapping over low-relief areas using a land surface dynamic feedbackmethod","volume":"72","author":"Zeng","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1111\/ejss.12566","article-title":"Construction of land surface dynamic feedbacks for digital soil mapping with fusion of multisource remote sensing data","volume":"70","author":"Zeng","year":"2019","journal-title":"Eur. J. Soil Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s10333-012-0319-1","article-title":"Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan","volume":"10","author":"Chen","year":"2012","journal-title":"Paddy Water Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1061\/(ASCE)IR.1943-4774.0000175","article-title":"Distribution and trends in reference evapotranspiration in the North China Plain","volume":"136","author":"Song","year":"2009","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"861","DOI":"10.2136\/sssaj2008.0411","article-title":"Differentiation of soil conditions over flat areas using land surface feedback dynamic patterns extracted from MODIS","volume":"74","author":"Zhu","year":"2010","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1029\/WR008i005p01204","article-title":"Model for predicting evaporation from a row crop with incomplete cover","volume":"8","author":"Ritchie","year":"1972","journal-title":"Water Resour. Res."},{"key":"ref_30","first-page":"417","article-title":"Soil evaporation: Test of a practical approach under semi-arid conditions","volume":"35","author":"Stroosnijder","year":"1987","journal-title":"Neth. J. Agr. Sci."},{"key":"ref_31","unstructured":"Allen, R.G. (1998). FAO Irrigation and Drainage Paper No. 56, Food and Agriculture Organization of the United Nations."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0034-4257(00)00198-X","article-title":"Modeling soil moisture reflectance","volume":"76","author":"Muller","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1111\/j.1365-2389.2010.01305.x","article-title":"Modelling moisture-induced soil reflectance changes in cultivated sandy soils: A case study in citrus orchards","volume":"61","author":"Somers","year":"2010","journal-title":"Eur. J. Soil Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1061\/(ASCE)0733-9437(2006)132:2(153)","article-title":"Estimating evaporation from bare soilusing soil moisture data","volume":"132","author":"Ventura","year":"2006","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1097\/00010694-196508000-00009","article-title":"Reflection of radiant energy from soils","volume":"100","author":"Bowers","year":"1965","journal-title":"Soil Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1097\/00010694-199202000-00007","article-title":"Moisture effects on visible spectral characteristics of lateritic soils","volume":"153","author":"Bedidi","year":"1992","journal-title":"Soil Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"104576","DOI":"10.1016\/j.catena.2020.104576","article-title":"Construction of land surface dynamic feedback for digital soil mapping considering the spatial heterogeneity of rainfall magnitude","volume":"191","author":"Zeng","year":"2020","journal-title":"Catena"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2610","DOI":"10.1016\/j.rse.2010.05.032","article-title":"An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions","volume":"114","author":"Zhu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1109\/TGRS.2006.872081","article-title":"On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance","volume":"44","author":"Gao","year":"2006","journal-title":"IEEE T. Geosci. Remote"},{"key":"ref_40","unstructured":"Misiti, M., Misiti, Y., Oppenheim, G., and Poggi, J. (2020, April 17). User\u2019s Guide of Wavelet Toolbox\u21224. Available online: http:\/\/www.mathworks.com\/access\/helpdesk\/help\/2009."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Nason, G.P. (2008). Wavelet Methods in Statistics with R, Springer.","DOI":"10.1007\/978-0-387-75961-6"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1080\/19475683.2018.1534890","article-title":"Spatial prediction based on Third Law of Geography","volume":"24","author":"Zhu","year":"2018","journal-title":"Ann. GIS"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"857","DOI":"10.2307\/2528823","article-title":"A general coefficient of similarity and some of its properties","volume":"27","author":"Gower","year":"1971","journal-title":"Biometrics"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/10\/1691\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:32:20Z","timestamp":1760175140000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/10\/1691"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,25]]},"references-count":43,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["rs12101691"],"URL":"https:\/\/doi.org\/10.3390\/rs12101691","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,25]]}}}