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<mods ID="pps-202501-0003">
	<titleInfo><title>Mapping and monitoring of weeds using unmanned aircraft systems and remote sensing</title></titleInfo>
	<name type="personal">
		<namePart type="family">Pon Arasan</namePart>
		<namePart type="given">A.</namePart>
		<role><roleTerm type="text">author</roleTerm></role>
	</name>
	<name type="personal">
		<namePart type="family">Radhamani</namePart>
		<namePart type="given">S.</namePart>
		<role><roleTerm type="text">author</roleTerm></role>
	</name>
	<name type="personal">
		<namePart type="family">Pazhanivelan</namePart>
		<namePart type="given">S.</namePart>
		<role><roleTerm type="text">author</roleTerm></role>
	</name>
	<name type="personal">
		<namePart type="family">Kavitha</namePart>
		<namePart type="given">R.</namePart>
		<role><roleTerm type="text">author</roleTerm></role>
	</name>
	<name type="personal">
		<namePart type="family">Raja</namePart>
		<namePart type="given">R.</namePart>
		<role><roleTerm type="text">author</roleTerm></role>
	</name>
	<name type="personal">
		<namePart type="family">Kumaraperumal</namePart>
		<namePart type="given">R.</namePart>
		<role><roleTerm type="text">author</roleTerm></role>
	</name>
	<typeOfResource>text</typeOfResource>
	<genre>journal article</genre>
	<originInfo><dateIssued>2025</dateIssued></originInfo>
	<language></language>
	<abstract lang="English">Effective weed management relies on frequent field monitoring, which is difficult to perform in vast areas. Integrating red-green-blue, thermal, hyperspectral, and multispectral sensors with unmanned aircraft systems and artificial intelligence ensures better results in managing the weed menace. Since India depends largely on agriculture, it is still a long way from implementing more advanced weed management methods. Mapping and surveillance of weeds in croplands by employing remote sensing will lead to varied herbicide application rates, thus reducing its overuse. This study reviews the practical application of remote sensing methods and unmanned aircraft systems in weed mapping</abstract>
	<subject><topic>UAS; weed mapping; artificial intelligence; remote sensing; sensors</topic></subject>
	<identifier type="doi">10.17221/74/2024-PPS</identifier>
	<identifier type="uri">https://pps.agriculturejournals.cz/artkey/pps-202501-0003.php</identifier>
	<location><url>https://pps.agriculturejournals.cz/artkey/pps-202501-0003.php</url></location>
	<relatedItem type="host">
		<titleInfo><title>Plant Protection Science</title></titleInfo>
		<originInfo><issuance>continuing</issuance></originInfo>
		<part>
			<detail type="volume"><number>61</number></detail>
			<detail type="issue"><number>1</number></detail>
			<extent unit="pages">
				<start>44</start>
				<end>55</end>
			</extent>
			<date>2025</date>
		</part>
		<identifier type="issn">12122580</identifier>
		<genre authority="marc">periodical</genre>
		<genre>academic journal</genre>
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