A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect
Remote sensing (RS) estimation of chlorophyll density serves as an effective measure to assess crop nitrogen (N) nutrition status and guide precision N fertilizer management. Throμgh multi-angular RS, this study aims to improve the estimation accuracy of chlorophyll density by reducing the disturban...
Gespeichert in:
| Veröffentlicht in: | Precision agriculture 2023-10, Vol.24 (5), p.2098-2125 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2125 |
|---|---|
| container_issue | 5 |
| container_start_page | 2098 |
| container_title | Precision agriculture |
| container_volume | 24 |
| creator | Pan, Yuanyuan Zhou, Ruiheng Zhang, Jiayi Guo, Wanting Yu, Minglei Guo, Caili Yao, Xia Cheng, Tao Zhu, Yan Cao, Weixing Tian, Yongchao |
| description | Remote sensing (RS) estimation of chlorophyll density serves as an effective measure to assess crop nitrogen (N) nutrition status and guide precision N fertilizer management. Throμgh multi-angular RS, this study aims to improve the estimation accuracy of chlorophyll density by reducing the disturbance of mixed background (soil and non-photosynthetic vegetation), and to explore the solutions to minimizing the influence of view zenith angles (VZAs). Wheat canopy multi-angular hyperspectral data (− 60°, − 45°, − 30°, 0°, 30°, 45°, 60°) were systematically collected throμgh three-years of field experiments. A soil non-photosynthetic background and angle insensitive vegetation index
SAIVI
=
(
ρ
750
-
1
-
ρ
860
-
1
)
-
(
ρ
765
-
1
-
ρ
860
-
1
)
(
ρ
750
-
1
-
ρ
860
-
1
)
+
(
ρ
765
-
1
-
ρ
860
-
1
)
was proposed for inversion of chlorophyll density. Furthermore, SAIVI, along with another 11 vegetation indices (VIs), were evaluated for their performance in estimating three chlorophyll parameters, namely chlorophyll concentration (CC), canopy chlorophyll density based on leaf area (CCC
L
) and canopy chlorophyll density based on fresh weight (CCC
W
). The results indicated that SAIVI had strong stability in restraining distractor (mixed background of soil and non-photosynthetic vegetation). For inversion of CC, CCC
L
and CCC
W
, backward VZAs showed higher accuracy than vertical angle. The new proposed SAIVI performed best for estimating CCC
L
and CCC
W
with an optimal VZA of − 30°, and the corresponding R
2
and RRMSE of 0.76 and 0.77, 14.5% and 26.6%, respectively. |
| doi_str_mv | 10.1007/s11119-023-10032-w |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3153150615</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2852192500</sourcerecordid><originalsourceid>FETCH-LOGICAL-c352t-aac4aa4c95aaec0cf9c7558d95b06b1ad55f4dd8d2ef17449e00110aa321bb763</originalsourceid><addsrcrecordid>eNp9UU1P3DAQtSqQoAt_gJMlLlxCbSfOB7fVqtBKSL2UszWxx7uhwQ52ttvtP-BfM3QrVeoBy9LMWO_NeN5j7EKKaylE8ylLOl0hVFlQXapi94GdSt1QWcv2iPKy1YVSuj5hH3N-FIJglTplL0secMfzhHZOMPIhOPzFfUwc8zw8wTzEwKPnuw3CzC2EOO253YwxxWmzH0fuMORh3t9wGylxmIaw5j3YH-sUt8FRwxmTx4TBIgd6-DnQvN8YhnlD9XpEjt7T9DN27GHMeP43LtjD7efvqy_F_be7r6vlfWFLreYCwFYAle00AFphfWcbrVvX6V7UvQSnta-ca51CL5uq6pB2lQKgVLLvm7pcsKtD3ynF5y1taZ6GbHEcIWDcZlNKTVfUFBbs8j_oY9ymQL8zqtVKdkqT2AumDiibYs4JvZkSKZf2Rgrz5o45uGPIHfPHHbMjUnkg5elNMUz_Wr_DegX8nJX1</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2852192500</pqid></control><display><type>article</type><title>A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect</title><source>Springer Nature - Complete Springer Journals</source><creator>Pan, Yuanyuan ; Zhou, Ruiheng ; Zhang, Jiayi ; Guo, Wanting ; Yu, Minglei ; Guo, Caili ; Yao, Xia ; Cheng, Tao ; Zhu, Yan ; Cao, Weixing ; Tian, Yongchao</creator><creatorcontrib>Pan, Yuanyuan ; Zhou, Ruiheng ; Zhang, Jiayi ; Guo, Wanting ; Yu, Minglei ; Guo, Caili ; Yao, Xia ; Cheng, Tao ; Zhu, Yan ; Cao, Weixing ; Tian, Yongchao</creatorcontrib><description>Remote sensing (RS) estimation of chlorophyll density serves as an effective measure to assess crop nitrogen (N) nutrition status and guide precision N fertilizer management. Throμgh multi-angular RS, this study aims to improve the estimation accuracy of chlorophyll density by reducing the disturbance of mixed background (soil and non-photosynthetic vegetation), and to explore the solutions to minimizing the influence of view zenith angles (VZAs). Wheat canopy multi-angular hyperspectral data (− 60°, − 45°, − 30°, 0°, 30°, 45°, 60°) were systematically collected throμgh three-years of field experiments. A soil non-photosynthetic background and angle insensitive vegetation index
SAIVI
=
(
ρ
750
-
1
-
ρ
860
-
1
)
-
(
ρ
765
-
1
-
ρ
860
-
1
)
(
ρ
750
-
1
-
ρ
860
-
1
)
+
(
ρ
765
-
1
-
ρ
860
-
1
)
was proposed for inversion of chlorophyll density. Furthermore, SAIVI, along with another 11 vegetation indices (VIs), were evaluated for their performance in estimating three chlorophyll parameters, namely chlorophyll concentration (CC), canopy chlorophyll density based on leaf area (CCC
L
) and canopy chlorophyll density based on fresh weight (CCC
W
). The results indicated that SAIVI had strong stability in restraining distractor (mixed background of soil and non-photosynthetic vegetation). For inversion of CC, CCC
L
and CCC
W
, backward VZAs showed higher accuracy than vertical angle. The new proposed SAIVI performed best for estimating CCC
L
and CCC
W
with an optimal VZA of − 30°, and the corresponding R
2
and RRMSE of 0.76 and 0.77, 14.5% and 26.6%, respectively.</description><identifier>ISSN: 1385-2256</identifier><identifier>EISSN: 1573-1618</identifier><identifier>DOI: 10.1007/s11119-023-10032-w</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Agriculture ; Atmospheric Sciences ; Biomedical and Life Sciences ; Canopies ; canopy ; Chemistry and Earth Sciences ; Chlorophyll ; Computer Science ; Density ; Estimation ; Field tests ; Leaf area ; Life Sciences ; Nitrogen ; nitrogen fertilizers ; nutritional status ; Photosynthesis ; Physics ; precision ; Remote sensing ; Remote Sensing/Photogrammetry ; soil ; Soil Science & Conservation ; Soils ; Statistics for Engineering ; Vegetation ; Vegetation index ; Wheat ; Zenith</subject><ispartof>Precision agriculture, 2023-10, Vol.24 (5), p.2098-2125</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c352t-aac4aa4c95aaec0cf9c7558d95b06b1ad55f4dd8d2ef17449e00110aa321bb763</citedby><cites>FETCH-LOGICAL-c352t-aac4aa4c95aaec0cf9c7558d95b06b1ad55f4dd8d2ef17449e00110aa321bb763</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11119-023-10032-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11119-023-10032-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Pan, Yuanyuan</creatorcontrib><creatorcontrib>Zhou, Ruiheng</creatorcontrib><creatorcontrib>Zhang, Jiayi</creatorcontrib><creatorcontrib>Guo, Wanting</creatorcontrib><creatorcontrib>Yu, Minglei</creatorcontrib><creatorcontrib>Guo, Caili</creatorcontrib><creatorcontrib>Yao, Xia</creatorcontrib><creatorcontrib>Cheng, Tao</creatorcontrib><creatorcontrib>Zhu, Yan</creatorcontrib><creatorcontrib>Cao, Weixing</creatorcontrib><creatorcontrib>Tian, Yongchao</creatorcontrib><title>A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect</title><title>Precision agriculture</title><addtitle>Precision Agric</addtitle><description>Remote sensing (RS) estimation of chlorophyll density serves as an effective measure to assess crop nitrogen (N) nutrition status and guide precision N fertilizer management. Throμgh multi-angular RS, this study aims to improve the estimation accuracy of chlorophyll density by reducing the disturbance of mixed background (soil and non-photosynthetic vegetation), and to explore the solutions to minimizing the influence of view zenith angles (VZAs). Wheat canopy multi-angular hyperspectral data (− 60°, − 45°, − 30°, 0°, 30°, 45°, 60°) were systematically collected throμgh three-years of field experiments. A soil non-photosynthetic background and angle insensitive vegetation index
SAIVI
=
(
ρ
750
-
1
-
ρ
860
-
1
)
-
(
ρ
765
-
1
-
ρ
860
-
1
)
(
ρ
750
-
1
-
ρ
860
-
1
)
+
(
ρ
765
-
1
-
ρ
860
-
1
)
was proposed for inversion of chlorophyll density. Furthermore, SAIVI, along with another 11 vegetation indices (VIs), were evaluated for their performance in estimating three chlorophyll parameters, namely chlorophyll concentration (CC), canopy chlorophyll density based on leaf area (CCC
L
) and canopy chlorophyll density based on fresh weight (CCC
W
). The results indicated that SAIVI had strong stability in restraining distractor (mixed background of soil and non-photosynthetic vegetation). For inversion of CC, CCC
L
and CCC
W
, backward VZAs showed higher accuracy than vertical angle. The new proposed SAIVI performed best for estimating CCC
L
and CCC
W
with an optimal VZA of − 30°, and the corresponding R
2
and RRMSE of 0.76 and 0.77, 14.5% and 26.6%, respectively.</description><subject>Agriculture</subject><subject>Atmospheric Sciences</subject><subject>Biomedical and Life Sciences</subject><subject>Canopies</subject><subject>canopy</subject><subject>Chemistry and Earth Sciences</subject><subject>Chlorophyll</subject><subject>Computer Science</subject><subject>Density</subject><subject>Estimation</subject><subject>Field tests</subject><subject>Leaf area</subject><subject>Life Sciences</subject><subject>Nitrogen</subject><subject>nitrogen fertilizers</subject><subject>nutritional status</subject><subject>Photosynthesis</subject><subject>Physics</subject><subject>precision</subject><subject>Remote sensing</subject><subject>Remote Sensing/Photogrammetry</subject><subject>soil</subject><subject>Soil Science & Conservation</subject><subject>Soils</subject><subject>Statistics for Engineering</subject><subject>Vegetation</subject><subject>Vegetation index</subject><subject>Wheat</subject><subject>Zenith</subject><issn>1385-2256</issn><issn>1573-1618</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9UU1P3DAQtSqQoAt_gJMlLlxCbSfOB7fVqtBKSL2UszWxx7uhwQ52ttvtP-BfM3QrVeoBy9LMWO_NeN5j7EKKaylE8ylLOl0hVFlQXapi94GdSt1QWcv2iPKy1YVSuj5hH3N-FIJglTplL0secMfzhHZOMPIhOPzFfUwc8zw8wTzEwKPnuw3CzC2EOO253YwxxWmzH0fuMORh3t9wGylxmIaw5j3YH-sUt8FRwxmTx4TBIgd6-DnQvN8YhnlD9XpEjt7T9DN27GHMeP43LtjD7efvqy_F_be7r6vlfWFLreYCwFYAle00AFphfWcbrVvX6V7UvQSnta-ca51CL5uq6pB2lQKgVLLvm7pcsKtD3ynF5y1taZ6GbHEcIWDcZlNKTVfUFBbs8j_oY9ymQL8zqtVKdkqT2AumDiibYs4JvZkSKZf2Rgrz5o45uGPIHfPHHbMjUnkg5elNMUz_Wr_DegX8nJX1</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Pan, Yuanyuan</creator><creator>Zhou, Ruiheng</creator><creator>Zhang, Jiayi</creator><creator>Guo, Wanting</creator><creator>Yu, Minglei</creator><creator>Guo, Caili</creator><creator>Yao, Xia</creator><creator>Cheng, Tao</creator><creator>Zhu, Yan</creator><creator>Cao, Weixing</creator><creator>Tian, Yongchao</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X2</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>M0C</scope><scope>M0K</scope><scope>M2P</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20231001</creationdate><title>A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect</title><author>Pan, Yuanyuan ; Zhou, Ruiheng ; Zhang, Jiayi ; Guo, Wanting ; Yu, Minglei ; Guo, Caili ; Yao, Xia ; Cheng, Tao ; Zhu, Yan ; Cao, Weixing ; Tian, Yongchao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c352t-aac4aa4c95aaec0cf9c7558d95b06b1ad55f4dd8d2ef17449e00110aa321bb763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Agriculture</topic><topic>Atmospheric Sciences</topic><topic>Biomedical and Life Sciences</topic><topic>Canopies</topic><topic>canopy</topic><topic>Chemistry and Earth Sciences</topic><topic>Chlorophyll</topic><topic>Computer Science</topic><topic>Density</topic><topic>Estimation</topic><topic>Field tests</topic><topic>Leaf area</topic><topic>Life Sciences</topic><topic>Nitrogen</topic><topic>nitrogen fertilizers</topic><topic>nutritional status</topic><topic>Photosynthesis</topic><topic>Physics</topic><topic>precision</topic><topic>Remote sensing</topic><topic>Remote Sensing/Photogrammetry</topic><topic>soil</topic><topic>Soil Science & Conservation</topic><topic>Soils</topic><topic>Statistics for Engineering</topic><topic>Vegetation</topic><topic>Vegetation index</topic><topic>Wheat</topic><topic>Zenith</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pan, Yuanyuan</creatorcontrib><creatorcontrib>Zhou, Ruiheng</creatorcontrib><creatorcontrib>Zhang, Jiayi</creatorcontrib><creatorcontrib>Guo, Wanting</creatorcontrib><creatorcontrib>Yu, Minglei</creatorcontrib><creatorcontrib>Guo, Caili</creatorcontrib><creatorcontrib>Yao, Xia</creatorcontrib><creatorcontrib>Cheng, Tao</creatorcontrib><creatorcontrib>Zhu, Yan</creatorcontrib><creatorcontrib>Cao, Weixing</creatorcontrib><creatorcontrib>Tian, Yongchao</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Agricultural Science Database</collection><collection>Science Database</collection><collection>Environmental Science Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Precision agriculture</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pan, Yuanyuan</au><au>Zhou, Ruiheng</au><au>Zhang, Jiayi</au><au>Guo, Wanting</au><au>Yu, Minglei</au><au>Guo, Caili</au><au>Yao, Xia</au><au>Cheng, Tao</au><au>Zhu, Yan</au><au>Cao, Weixing</au><au>Tian, Yongchao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect</atitle><jtitle>Precision agriculture</jtitle><stitle>Precision Agric</stitle><date>2023-10-01</date><risdate>2023</risdate><volume>24</volume><issue>5</issue><spage>2098</spage><epage>2125</epage><pages>2098-2125</pages><issn>1385-2256</issn><eissn>1573-1618</eissn><abstract>Remote sensing (RS) estimation of chlorophyll density serves as an effective measure to assess crop nitrogen (N) nutrition status and guide precision N fertilizer management. Throμgh multi-angular RS, this study aims to improve the estimation accuracy of chlorophyll density by reducing the disturbance of mixed background (soil and non-photosynthetic vegetation), and to explore the solutions to minimizing the influence of view zenith angles (VZAs). Wheat canopy multi-angular hyperspectral data (− 60°, − 45°, − 30°, 0°, 30°, 45°, 60°) were systematically collected throμgh three-years of field experiments. A soil non-photosynthetic background and angle insensitive vegetation index
SAIVI
=
(
ρ
750
-
1
-
ρ
860
-
1
)
-
(
ρ
765
-
1
-
ρ
860
-
1
)
(
ρ
750
-
1
-
ρ
860
-
1
)
+
(
ρ
765
-
1
-
ρ
860
-
1
)
was proposed for inversion of chlorophyll density. Furthermore, SAIVI, along with another 11 vegetation indices (VIs), were evaluated for their performance in estimating three chlorophyll parameters, namely chlorophyll concentration (CC), canopy chlorophyll density based on leaf area (CCC
L
) and canopy chlorophyll density based on fresh weight (CCC
W
). The results indicated that SAIVI had strong stability in restraining distractor (mixed background of soil and non-photosynthetic vegetation). For inversion of CC, CCC
L
and CCC
W
, backward VZAs showed higher accuracy than vertical angle. The new proposed SAIVI performed best for estimating CCC
L
and CCC
W
with an optimal VZA of − 30°, and the corresponding R
2
and RRMSE of 0.76 and 0.77, 14.5% and 26.6%, respectively.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11119-023-10032-w</doi><tpages>28</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1385-2256 |
| ispartof | Precision agriculture, 2023-10, Vol.24 (5), p.2098-2125 |
| issn | 1385-2256 1573-1618 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_3153150615 |
| source | Springer Nature - Complete Springer Journals |
| subjects | Agriculture Atmospheric Sciences Biomedical and Life Sciences Canopies canopy Chemistry and Earth Sciences Chlorophyll Computer Science Density Estimation Field tests Leaf area Life Sciences Nitrogen nitrogen fertilizers nutritional status Photosynthesis Physics precision Remote sensing Remote Sensing/Photogrammetry soil Soil Science & Conservation Soils Statistics for Engineering Vegetation Vegetation index Wheat Zenith |
| title | A new spectral index for estimation of wheat canopy chlorophyll density: considering background interference and view zenith angle effect |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T23%3A41%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20new%20spectral%20index%20for%20estimation%20of%20wheat%20canopy%20chlorophyll%20density:%20considering%20background%20interference%20and%20view%20zenith%20angle%20effect&rft.jtitle=Precision%20agriculture&rft.au=Pan,%20Yuanyuan&rft.date=2023-10-01&rft.volume=24&rft.issue=5&rft.spage=2098&rft.epage=2125&rft.pages=2098-2125&rft.issn=1385-2256&rft.eissn=1573-1618&rft_id=info:doi/10.1007/s11119-023-10032-w&rft_dat=%3Cproquest_cross%3E2852192500%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2852192500&rft_id=info:pmid/&rfr_iscdi=true |