{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T17:45:59Z","timestamp":1730310359648,"version":"3.28.0"},"reference-count":26,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10,3]]},"DOI":"10.1117\/12.2532935","type":"proceedings-article","created":{"date-parts":[[2019,10,3]],"date-time":"2019-10-03T17:02:24Z","timestamp":1570122144000},"page":"10","source":"Crossref","is-referenced-by-count":1,"title":["A semi-automatic approach to derive land cover classification in soil loss models"],"prefix":"10.1117","author":[{"given":"Lia","family":"Duarte","sequence":"first","affiliation":[]},{"given":"Ana Claudia M.","family":"Teodoro","sequence":"additional","affiliation":[]},{"given":"Mario","family":"Cunha","sequence":"additional","affiliation":[]}],"member":"189","reference":[{"doi-asserted-by":"publisher","key":"c1","DOI":"10.1080\/02723646.2018.1541706"},{"year":"1978","author":"Wischmeier","article-title":"Predicting rainfall erosion losses: a guide to conservation planning with Universal Soil Loss Equation (USLE)","key":"c2"},{"key":"c3","first-page":"1","article-title":"Predicting Soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE)","volume":"703","author":"Renard","year":"1997","journal-title":"Washington: Agriculture Handbook, US Department of Agriculture. Papers"},{"key":"c4","first-page":"629","article-title":"Modelling topographic potential for erosion and dep ositionusing GIS","volume":"10","author":"Mitasova","year":"1996","journal-title":"International Journal of Information Systems. Papers"},{"doi-asserted-by":"publisher","key":"c5","DOI":"10.1080\/17445647.2019.1599452"},{"doi-asserted-by":"publisher","key":"c6","DOI":"10.1007\/s10113-012-0278-5"},{"doi-asserted-by":"publisher","key":"c7","DOI":"10.1590\/S1413-70542014000300006"},{"doi-asserted-by":"publisher","key":"c8","DOI":"10.1007\/s11269-014-0680-5"},{"doi-asserted-by":"publisher","key":"c9","DOI":"10.1007\/s10661-016-5349-5"},{"doi-asserted-by":"publisher","key":"c10","DOI":"10.1007\/s11600-019-00288-0"},{"doi-asserted-by":"publisher","key":"c11","DOI":"10.1016\/j.apgeog.2018.10.004"},{"doi-asserted-by":"publisher","key":"c12","DOI":"10.1016\/j.rse.2018.12.026"},{"doi-asserted-by":"publisher","key":"c13","DOI":"10.1080\/01431161.2018.1528400"},{"doi-asserted-by":"publisher","key":"c14","DOI":"10.1016\/j.jag.2018.06.011"},{"unstructured":"ICNF, \u201cInstituto da Conserva\u00e7\u00e3o da Natureza e das Florestas.\u201d 20 january 2019, https:\/\/www.icnf.pt\/ (20 january 2019).","key":"c15"},{"unstructured":"QGIS, \u201cQGIS Project.\u201d 17 january 2019, http:\/\/www.qgis.org\/ (17 january 2019).","key":"c16"},{"unstructured":"GRASS GIS, \u201cThe world\u2019s leading free GIS software.\u201d 22 january 2019, http:\/\/grass.osgeo.org\/ (22 january 2019).","key":"c17"},{"unstructured":"SAGA, \u201cSystem for automated geoscientific analyses.\u201d 22 january 2019. http:\/\/www.saga-gis.org\/ (22 january 2019).","key":"c18"},{"unstructured":"R software, \u201cThe R Project for Statistical Computing.\u201d 20 february 2019. https:\/\/www.r-project.org\/ (20 february 2019).","key":"c19"},{"doi-asserted-by":"publisher","key":"c20","DOI":"10.3390\/environments6030036"},{"doi-asserted-by":"publisher","key":"c21","DOI":"10.1016\/j.jag.2018.12.003"},{"doi-asserted-by":"publisher","key":"c22","DOI":"10.1016\/0034-4257(91)90048-B"},{"doi-asserted-by":"publisher","key":"c23","DOI":"10.1080\/01431160701281072"},{"doi-asserted-by":"publisher","key":"c24","DOI":"10.1117\/1.JRS.13.024519"},{"unstructured":"amsantac.co, \u201cImage Classification with RandomForests in R (and QGIS).\u201d 20 february 2019, http:\/\/amsantac.co\/blog\/en\/2015\/11\/28\/classification-r.html (20 february 2019).","key":"c25"},{"doi-asserted-by":"publisher","key":"c26","DOI":"10.1007\/s10661-016-5712-6"}],"event":{"name":"Earth Resources and Environmental Remote Sensing\/GIS Applications X","start":{"date-parts":[[2019,9,9]]},"location":"Strasbourg, France","end":{"date-parts":[[2019,9,12]]}},"container-title":["Earth Resources and Environmental Remote Sensing\/GIS Applications X"],"original-title":[],"deposited":{"date-parts":[[2019,10,18]],"date-time":"2019-10-18T21:36:45Z","timestamp":1571434605000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/11156\/2532935\/A-semi-automatic-approach-to-derive-land-cover-classification-in\/10.1117\/12.2532935.full"}},"subtitle":[],"editor":[{"given":"Karsten","family":"Schulz","sequence":"additional","affiliation":[]},{"given":"Konstantinos G.","family":"Nikolakopoulos","sequence":"additional","affiliation":[]},{"given":"Ulrich","family":"Michel","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2019,10,3]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1117\/12.2532935","relation":{},"subject":[],"published":{"date-parts":[[2019,10,3]]}}}