{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T19:42:39Z","timestamp":1774554159538,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2017,10,14]],"date-time":"2017-10-14T00:00:00Z","timestamp":1507939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["1094229-2014"],"award-info":[{"award-number":["1094229-2014"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Earth Observation has become a progressively important source of information for land use and land cover services over the past decades. At the same time, an increasing number of reconnaissance satellites have been set in orbit with ever increasing spatial, temporal, spectral, and radiometric resolutions. The available bulk of data, fostered by open access policies adopted by several agencies, is setting a new landscape in remote sensing in which timeliness and efficiency are important aspects of data processing. This study presents a fully automated workflow able to process a large collection of very high spatial resolution satellite images to produce actionable information in the application framework of smallholder farming. The workflow applies sequential image processing, extracts meaningful statistical information from agricultural parcels, and stores them in a crop spectrotemporal signature library. An important objective is to follow crop development through the season by analyzing multi-temporal and multi-sensor images. The workflow is based on free and open-source software, namely R, Python, Linux shell scripts, the Geospatial Data Abstraction Library, custom FORTRAN, C++, and the GNU Make utilities. We tested and applied this workflow on a multi-sensor image archive of over 270 VHSR WorldView-2, -3, QuickBird, GeoEye, and RapidEye images acquired over five different study areas where smallholder agriculture prevails.<\/jats:p>","DOI":"10.3390\/rs9101048","type":"journal-article","created":{"date-parts":[[2017,10,16]],"date-time":"2017-10-16T11:11:09Z","timestamp":1508152269000},"page":"1048","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Workflow for Automated Satellite Image Processing: from Raw VHSR Data to Object-Based Spectral Information for Smallholder Agriculture"],"prefix":"10.3390","volume":"9","author":[{"given":"Dimitris","family":"Stratoulias","sequence":"first","affiliation":[{"name":"Faculty of Geo-Information and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands"},{"name":"GeoAnalysis, Budapest, 1134 Hungary"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4517-113X","authenticated-orcid":false,"given":"Valentyn","family":"Tolpekin","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands"}]},{"given":"Rolf","family":"De By","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands"}]},{"given":"Raul","family":"Zurita-Milla","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands"}]},{"given":"Vasilios","family":"Retsios","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands"}]},{"given":"Wietske","family":"Bijker","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands"}]},{"given":"Mohammad","family":"Hasan","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Rhode Island , Kingston, RI 02881, USA"}]},{"given":"Eric","family":"Vermote","sequence":"additional","affiliation":[{"name":"NASA Goddard Space Flight Center, Terrestrial Information Systems Laboratory, Greenbelt, MD 20771, USA"}]}],"member":"1968","published-online":{"date-parts":[[2017,10,14]]},"reference":[{"key":"ref_1","unstructured":"United Nations, Department of Economic and Social Affairs, Population Division (2015). World Population Prospects: The 2015 Revision, Key Findings & Advance Tables, United Nations. Working Paper No. ESA\/WP.241."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1126\/science.1257469","article-title":"World population stabilization unlikely this century","volume":"346","author":"Gerland","year":"2014","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"20260","DOI":"10.1073\/pnas.1116437108","article-title":"Global food demand and the sustainable intensification of agriculture","volume":"108","author":"Tilman","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.rse.2003.04.007","article-title":"Remote sensing applications for precision agriculture: A learning community approach","volume":"88","author":"Seelan","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Jackson, R.D. (1984, January 16). Remote sensing of vegetation characteristics for farm management. Proceedings of the 1984 Technical Symposium East, Arlington, VA, USA.","DOI":"10.1117\/12.966243"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sandau, R., Paxton, L., and Esper, J. (2008). Trends and visions for small satellite missions. Small Satellites for Earth Observation, Springer.","DOI":"10.1007\/978-1-4020-6943-7"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1126\/science.196.4285.19","article-title":"Remote sensing of crop yields","volume":"196","author":"Idso","year":"1977","journal-title":"Science"},{"key":"ref_8","first-page":"50","article-title":"On-farm profitability of remote sensing on agriculture","volume":"1","author":"Tenkorang","year":"2008","journal-title":"J. Terr. Obs."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.worlddev.2015.10.041","article-title":"The Number, Size and Distribution of Farms, Smallholder Farms, and Family Farms Worldwide","volume":"87","author":"Lowder","year":"2016","journal-title":"World Dev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"9034","DOI":"10.3390\/rs6099034","article-title":"Defining the Spatial Resolution Requirements for Crop Identification Using Optical Remote Sensing","volume":"6","author":"Duveiller","year":"2014","journal-title":"Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1482","DOI":"10.3390\/rs70201482","article-title":"Meeting Earth Observation requirements for global agricultural monitoring: An evaluation of the revisit capabilities of current and planned moderate resolution optical observing missions","volume":"7","author":"Whitcraft","year":"2015","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"669","DOI":"10.5194\/isprsarchives-XL-7-W3-669-2015","article-title":"Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data","volume":"XL-7\/W3","author":"Pehani","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_13","unstructured":"Scheffler, D., Sips, M., Behling, R., Dransch, D., Eggert, D., Fajerski, J., Freytag, J.C., Griffiths, P., Hollstein, A., and Hostert, P. (2016, January 6\u20137). Geomultisens\u2014A common automatic processing and analysis system for multi-sensor satellite data. Proceedings of the Second joint Workshop of the EARSeL Special Interest Group on Land Use & Land Cover and the NASA LCLUC Program: \u201cAdvancing Horizons for Land Cover Services Entering the Big Data Era\u201d, Prague, Czech Republic."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2200","DOI":"10.3390\/rs5052200","article-title":"Exploring the potential for automatic extraction of vegetation phenological metrics from traffic webcams","volume":"5","author":"Morris","year":"2013","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"12356","DOI":"10.3390\/rs70912356","article-title":"Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery","volume":"7","author":"Inglada","year":"2015","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6111","DOI":"10.3390\/rs6076111","article-title":"A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables","volume":"6","author":"Clewley","year":"2014","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Grippa, T., Lennert, M., Beaumont, B., Vanhuysse, S., Stephenne, N., and Wolff, E. (2017). An Open-Source Semi-Automated Processing Chain for Urban Object-Based Classification. Remote Sens., 9.","DOI":"10.3390\/rs9040358"},{"key":"ref_18","unstructured":"(2017, July 14). Google Earth Engine: A Planetary-Scale Platform for Earth Science Data & Analysis\u2014Powered by Google\u2019s Cloud Infrastructure. Available online: https:\/\/earthengine.google.com."},{"key":"ref_19","unstructured":"DigitalGlobe Platform\u2014Actionable Insights (2017, July 14). Global Scale. Available online: https:\/\/platform.digitalglobe.com\/gbdx."},{"key":"ref_20","unstructured":"Tiede, D., Baraldi, A., Sudmanns, M., Belgiu, M., and Lang, S. (2016, January 6\u20137). ImageQuerying\u2014Automatic real-time information extraction and content-based image retrieval in big EO image databases. Proceedings of the Second joint Workshop of the EARSeL Special Interest Group on Land Use & Land Cover and the NASA LCLUC Program: \u201cAdvancing Horizons for Land Cover Services Entering the Big Data Era\u201d, Prague, Czech Republic."},{"key":"ref_21","unstructured":"Amazon EC2\u2014Secure and Resizable Compute Capacity in the Cloud (2017, July 14). Launch Applications When Needed without Upfront Commitments. Available online: https:\/\/aws.amazon.com\/ec2."},{"key":"ref_22","unstructured":"Microsoft Azure\u2014Global (2017, July 14). Trusted. Hybrid. Available online: https:\/\/azure.microsoft.com\/en-us."},{"key":"ref_23","unstructured":"(2017, July 14). STARS. Available online: http:\/\/www.stars-project.org\/en."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2566","DOI":"10.1080\/01431161.2012.747016","article-title":"Crop mapping in countrieswith small-scale farming: A case study for West Shewa, Ethiopia","volume":"34","author":"Delrue","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.worlddev.2013.10.001","article-title":"African agriculture in 50 years: Smallholders in a rapidly changing world?","volume":"63","author":"Collier","year":"2014","journal-title":"World Dev."},{"key":"ref_26","first-page":"5","article-title":"Farm size and productivity: Understanding the strengths of smallholders and improving their livelihoods","volume":"46","author":"Chand","year":"2011","journal-title":"Econ. Political Wkly Suppl. Rev. Agric."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4968","DOI":"10.3390\/rs70404968","article-title":"Innovative technologies for terrestrial remote sensing","volume":"7","author":"Aplin","year":"2015","journal-title":"Remote Sens."},{"key":"ref_28","unstructured":"R Foundation for Statistical Computing (2014). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_29","first-page":"24","article-title":"Data processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment","volume":"54","author":"Warren","year":"2013","journal-title":"Comput. Geosci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Pehani, P., \u010cotar, K., Marseti\u010d, A., Zaletelj, J., and O\u0161tir, K. (2016). Automatic Geometric Processing for Very High Resolution Optical Satellite Data Based on Vector Roads and Orthophotos. Remote Sens., 8.","DOI":"10.3390\/rs8040343"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1080\/01431168708954779","article-title":"Review article radiometric correction of visible and infrared remote sensing data at the Canada Centre for remote sensing","volume":"8","author":"Ahern","year":"1987","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/36.581987","article-title":"Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: An Overview","volume":"35","author":"Vermote","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2016.04.008","article-title":"Preliminary analysis of the performance of the Landsat 8\/OLI land surface reflectance product","volume":"185","author":"Vermote","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_34","first-page":"1249","article-title":"Calibration and validation plan for the L2A processor and products of the Sentinel-2 mission","volume":"W3\/XL.7","author":"Pflug","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1016\/j.rse.2010.03.002","article-title":"multi-temporal method for cloud detection, applied to FORMOSAT-2, VEN\u00b5S, LANDSAT and SENTINEL-2 images","volume":"114","author":"Hagolle","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_36","first-page":"427","article-title":"Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView-2 panchromatic images","volume":"21","author":"Aguilar","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_37","first-page":"1617","article-title":"Comparison of orthorectification methods suitable for rapid mapping using direct georeferencing and RPC for optical satellite data","volume":"XXXVII","author":"Hoja","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_38","unstructured":"Willneff, J., and Poon, J. (2006, January 21\u201324). Georeferencing from orthorectified and non-orthorectified high-resolution satellite imagery. Proceedings of the 13th Australasian Remote Sensing and Photogrammetry Conference: Earth Observation from Science to Solutions, Canberra, Australia."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Lowe, D.G. (1999, January 20\u201327). Object recognition from local scale-invariant features. Proceedings of the IEEE International Conference on Computer Vision, Corfu, Greece.","DOI":"10.1109\/ICCV.1999.790410"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., and Van Gool, L. (2006, January 7\u201313). SURF: Speeded Up Robust Features. Proceedings of the 9th European Conference on Computer Vision, Graz, Austria.","DOI":"10.1007\/11744023_32"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1023\/A:1008045108935","article-title":"Feature Detection with Automatic Scale Selection","volume":"30","author":"Lindeberg","year":"1998","journal-title":"Int. J. Comput. Vis."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Le Moigne, J., Netanyahu, N.S., and Eastman, R.D. (2011). Image Registration for Remote Sensing, Cambridge University Press.","DOI":"10.1017\/CBO9780511777684"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Zaletelj, J., Burnik, U., and Tasic, J.F. (2013, January 4\u20136). Registration of satellite images based on road network map. Proceedings of the 8th International Symposium on Image and Signal Processing and Analysis, Trieste, Italy.","DOI":"10.1109\/ISPA.2013.6703713"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.isprsjprs.2012.08.007","article-title":"Quantification of crown changes and change uncertainty of trees in an urban environment","volume":"74","author":"Ardila","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_46","unstructured":"Tolpekin, V., Bijker, W., Zurita Milla, R., Stratoulias, D., and de By, R.A. (2017). Automatic co-registration of very high resolution satellite images of smallholder farms using a 3D tree model. Manuscript in preparation."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3855","DOI":"10.1080\/01431160010006926","article-title":"Cloud cover in Landsat observations of the Brazilian Amazon","volume":"22","author":"Asner","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2016.07.033","article-title":"Landsat 8: The plans, the reality, and the legacy","volume":"185","author":"Loveland","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.isprsjprs.2008.12.007","article-title":"Use of Markov random fields for automatic cloud\/shadow detection on high resolution optical images","volume":"64","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.amc.2008.05.050","article-title":"Automatic cloud removal from multi-temporal SPOT images","volume":"205","author":"Tseng","year":"2008","journal-title":"Appl. Math. Comput."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1016\/j.isprsjprs.2011.03.005","article-title":"A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors","volume":"66","author":"Sedano","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a green channel in remote sensing of global vegetation from EOS-MODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices global set of TM images for EOS-MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/S0034-4257(02)00018-4","article-title":"Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture","volume":"81","author":"Haboudane","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"663","DOI":"10.2307\/1936256","article-title":"Derivation of leaf area index from quality of light on the forest floor","volume":"50","author":"Jordan","year":"1969","journal-title":"Ecology"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/36.134076","article-title":"Atmospherically resistant vegetation index (ARVI) for EOS-MODIS","volume":"30","author":"Kaufman","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(88)90106-X","article-title":"A soil-adjusted vegetation index (SAVI)","volume":"25","author":"Huete","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/0034-4257(94)90134-1","article-title":"A modified soil adjusted vegetation index","volume":"48","author":"Qi","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Texture features for image classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"991","DOI":"10.14358\/PERS.69.9.991","article-title":"Spatial metrics and image texture for mapping urban land use","volume":"69","author":"Herold","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/S0034-4257(02)00135-9","article-title":"Monitoring vegetation phenology using MODIS","volume":"84","author":"Zhang","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_63","unstructured":"Stallman, R.M., McGrath, R., and Smith, P. (2016). GNU Make: A Program for Directing Recompilation, GNU make Version 3.80, Free Software Foundation."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/10\/1048\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:47:21Z","timestamp":1760208441000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/10\/1048"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,14]]},"references-count":63,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2017,10]]}},"alternative-id":["rs9101048"],"URL":"https:\/\/doi.org\/10.3390\/rs9101048","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,10,14]]}}}