Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis
▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issu...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Meiling [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011transfer abstract |
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10 |
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Enthalten in: No title available - s.l. |
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volume:13 ; year:2011 ; number:2 ; pages:246-255 ; extent:10 |
| Links: |
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| DOI / URN: |
10.1016/j.jag.2010.12.006 |
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| 520 | |a ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. | ||
| 520 | |a ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. | ||
| 650 | 7 | |a Hyperspectral reflectance |2 Elsevier | |
| 650 | 7 | |a Stress information |2 Elsevier | |
| 650 | 7 | |a Wavelet transform |2 Elsevier | |
| 650 | 7 | |a Heavy metal pollution |2 Elsevier | |
| 650 | 7 | |a Fractal analysis |2 Elsevier | |
| 700 | 1 | |a Liu, Xiangnan |4 oth | |
| 700 | 1 | |a Ding, Weicui |4 oth | |
| 700 | 1 | |a Wu, Ling |4 oth | |
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10.1016/j.jag.2010.12.006 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001777.pica (DE-627)ELV015781240 (ELSEVIER)S0303-2434(10)00143-1 DE-627 ger DE-627 rakwb eng Liu, Meiling verfasserin aut Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis 2011transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. Hyperspectral reflectance Elsevier Stress information Elsevier Wavelet transform Elsevier Heavy metal pollution Elsevier Fractal analysis Elsevier Liu, Xiangnan oth Ding, Weicui oth Wu, Ling oth Enthalten in Elsevier No title available s.l. (DE-627)ELV015781232 nnns volume:13 year:2011 number:2 pages:246-255 extent:10 https://doi.org/10.1016/j.jag.2010.12.006 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 13 2011 2 246-255 10 |
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10.1016/j.jag.2010.12.006 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001777.pica (DE-627)ELV015781240 (ELSEVIER)S0303-2434(10)00143-1 DE-627 ger DE-627 rakwb eng Liu, Meiling verfasserin aut Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis 2011transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. Hyperspectral reflectance Elsevier Stress information Elsevier Wavelet transform Elsevier Heavy metal pollution Elsevier Fractal analysis Elsevier Liu, Xiangnan oth Ding, Weicui oth Wu, Ling oth Enthalten in Elsevier No title available s.l. (DE-627)ELV015781232 nnns volume:13 year:2011 number:2 pages:246-255 extent:10 https://doi.org/10.1016/j.jag.2010.12.006 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 13 2011 2 246-255 10 |
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10.1016/j.jag.2010.12.006 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001777.pica (DE-627)ELV015781240 (ELSEVIER)S0303-2434(10)00143-1 DE-627 ger DE-627 rakwb eng Liu, Meiling verfasserin aut Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis 2011transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. Hyperspectral reflectance Elsevier Stress information Elsevier Wavelet transform Elsevier Heavy metal pollution Elsevier Fractal analysis Elsevier Liu, Xiangnan oth Ding, Weicui oth Wu, Ling oth Enthalten in Elsevier No title available s.l. (DE-627)ELV015781232 nnns volume:13 year:2011 number:2 pages:246-255 extent:10 https://doi.org/10.1016/j.jag.2010.12.006 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 13 2011 2 246-255 10 |
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10.1016/j.jag.2010.12.006 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001777.pica (DE-627)ELV015781240 (ELSEVIER)S0303-2434(10)00143-1 DE-627 ger DE-627 rakwb eng Liu, Meiling verfasserin aut Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis 2011transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. ▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. Hyperspectral reflectance Elsevier Stress information Elsevier Wavelet transform Elsevier Heavy metal pollution Elsevier Fractal analysis Elsevier Liu, Xiangnan oth Ding, Weicui oth Wu, Ling oth Enthalten in Elsevier No title available s.l. (DE-627)ELV015781232 nnns volume:13 year:2011 number:2 pages:246-255 extent:10 https://doi.org/10.1016/j.jag.2010.12.006 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 13 2011 2 246-255 10 |
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Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis |
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▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. |
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▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. |
| abstract_unstemmed |
▸ Accurate detection of heavy metal-induced stress on the growth of crops is essential for agricultural ecological environment and food security. How to explore sensitive spectral parameter for monitoring stress levels of crop under heavy metal from hyperspectral remote sensing is a challenging issue. ▸ In our manuscript, wavelet transform in conjunction with fractal analysis were adopted to extract and quantify subtle stress information of rice under heavy metal. The method of detecting stress levels of rice under heavy metal contamination may be a significance contributing to precision agriculture. ▸ Compared with REP in identifying the stress levels of crop under heavy metal, FDWT (fractal dimension of reflectance with wavelet transform) spectral parameter that explored in our manuscript was more sensitive to stress levels of rice under heavy metal with higher R 2 against biochemical composition. |
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Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis |
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https://doi.org/10.1016/j.jag.2010.12.006 |
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| author2 |
Liu, Xiangnan Ding, Weicui Wu, Ling |
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| doi_str |
10.1016/j.jag.2010.12.006 |
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2024-07-06T18:27:58.854Z |
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