{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T02:01:50Z","timestamp":1779328910395,"version":"3.51.4"},"reference-count":54,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) New Directions Research Program, Canada and Graduate Merit Scholarship, Nature and Technology-FRQNT (B2X), Government of Quebec, Canada","award":["New Directions Research Program: ND2014-2487"],"award-info":[{"award-number":["New Directions Research Program: ND2014-2487"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing (RS) and proximal soil sensing (PSS) technologies offer an advanced array of methods for obtaining soil property information and determining soil variability for precision agriculture. A large amount of data collected by these sensors may provide essential information for precision or site-specific management in a production field. Data clustering techniques are crucial for data mining, and high-density data analysis is important for field management. A new clustering technique was introduced and compared with existing clustering tools to determine the relatively homogeneous parts of agricultural fields. A DUALEM-21S sensor, along with high-accuracy topography data, was used to characterize soil variability in three agricultural fields situated in Ontario, Canada. Sentinel-2 data assisted in quantifying bare soil and vegetation indices (VIs). The custom Neighborhood Search Analyst (NSA) data clustering tool was implemented using Python scripts. In this algorithm, part of the variance of each data layer is accounted for by subdividing the field into smaller, relatively homogeneous, areas. The algorithm\u2019s attributes were illustrated using field elevation, shallow and deep apparent electrical conductivity (ECa), and several VIs. The unique feature of this proposed protocol was the successful development of user-friendly and open source options for defining the spatial continuity of each group and for use in the zone delineation process.<\/jats:p>","DOI":"10.3390\/rs11091036","type":"journal-article","created":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T03:15:22Z","timestamp":1556766922000},"page":"1036","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Clustering Tools for Integration of Satellite Remote Sensing Imagery and Proximal Soil Sensing Data"],"prefix":"10.3390","volume":"11","author":[{"given":"Md","family":"Saifuzzaman","sequence":"first","affiliation":[{"name":"Department of Bioresource Engineering, McGill University, Montreal, QC H9X 3V9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7279-3597","authenticated-orcid":false,"given":"Viacheslav","family":"Adamchuk","sequence":"additional","affiliation":[{"name":"Department of Bioresource Engineering, McGill University, Montreal, QC H9X 3V9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roberto","family":"Buelvas","sequence":"additional","affiliation":[{"name":"Department of Bioresource Engineering, McGill University, Montreal, QC H9X 3V9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0801-3546","authenticated-orcid":false,"given":"Asim","family":"Biswas","sequence":"additional","affiliation":[{"name":"School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiv","family":"Prasher","sequence":"additional","affiliation":[{"name":"Department of Bioresource Engineering, McGill University, Montreal, QC H9X 3V9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicole","family":"Rabe","sequence":"additional","affiliation":[{"name":"Ontario Ministry of Agriculture, Food and Rural Affairs, Guelph, ON N1G 4Y2, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Doug","family":"Aspinall","sequence":"additional","affiliation":[{"name":"Woodrill Farms Ltd., Guelph, ON N1H 6H8, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjun","family":"Ji","sequence":"additional","affiliation":[{"name":"Department of Soil and Environment, Precision Agriculture and Pedometrics, Swedish University of Agricultural Sciences, SE-532 23 Skara, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/S0168-1699(02)00096-0","article-title":"Precision Agriculture\u2014A Worldwide Overview","volume":"36","author":"Zhang","year":"2002","journal-title":"Comput. 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