Oil palm pest infestation monitoring and evaluation by helicopter-mounted, low altitude remote sensing platform

Grianggai Samseemoung, Hemantha P W Jayasuriya, Peeyush Soni

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Timely detection of pest or disease infections is extremely important for controlling the spread of disease and preventing crop productivity losses. A specifically designed radio-controlled helicopter mounted low altitude remote sensing (LARS) platform can offer near-real-time results upon user demand. The acquired LARS images were processed to estimate vegetative-indices and thereby detecting upper stem rot (Phellinus Noxius) disease in both young and mature oil palm plants. The indices helped discriminate healthy and infested plants by visualization, analysis and presentation of digital imagery software, which were validated with ground truth data. Good correlations and clear data clusters were obtained in characteristic plots of normalized difference vegetation index (NDVI)LARS and green normalized difference vegetation index LARS against NDVISpectro and chlorophyll content, by which infested plants were discriminated from healthy plants in both young and mature crops. The chlorophyll content values (μmol m-2) showed notable differences among clusters for healthy young (972 to 1100), for infested young (253 to 400), for healthy mature (1210 to 1500), and for infested mature (440 to 550) oil palm. The correlation coefficients (R2) were in a reasonably acceptable range (0.62 to 0.88). The vegetation indices based on LARS images, provided satisfactory results when compared to other approaches. The developed technology showed promising scope for medium and large plantations.

Original languageEnglish
Article number053540
JournalJournal of Applied Remote Sensing
Volume5
Issue number1
DOIs
Publication statusPublished - 2011

Fingerprint

remote sensing
oil
monitoring
NDVI
chlorophyll
crop
vegetation index
visualization
plantation
imagery
evaluation
pest infestation
stem
radio
software
productivity
young
index

Keywords

  • chlorophyll content
  • image processing
  • LARS
  • oil palm infestation
  • Phellinus noxius
  • vegetation indices

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Cite this

Oil palm pest infestation monitoring and evaluation by helicopter-mounted, low altitude remote sensing platform. / Samseemoung, Grianggai; Jayasuriya, Hemantha P W; Soni, Peeyush.

In: Journal of Applied Remote Sensing, Vol. 5, No. 1, 053540, 2011.

Research output: Contribution to journalArticle

@article{7ab84b0bf2b3472f92f102be851cb162,
title = "Oil palm pest infestation monitoring and evaluation by helicopter-mounted, low altitude remote sensing platform",
abstract = "Timely detection of pest or disease infections is extremely important for controlling the spread of disease and preventing crop productivity losses. A specifically designed radio-controlled helicopter mounted low altitude remote sensing (LARS) platform can offer near-real-time results upon user demand. The acquired LARS images were processed to estimate vegetative-indices and thereby detecting upper stem rot (Phellinus Noxius) disease in both young and mature oil palm plants. The indices helped discriminate healthy and infested plants by visualization, analysis and presentation of digital imagery software, which were validated with ground truth data. Good correlations and clear data clusters were obtained in characteristic plots of normalized difference vegetation index (NDVI)LARS and green normalized difference vegetation index LARS against NDVISpectro and chlorophyll content, by which infested plants were discriminated from healthy plants in both young and mature crops. The chlorophyll content values (μmol m-2) showed notable differences among clusters for healthy young (972 to 1100), for infested young (253 to 400), for healthy mature (1210 to 1500), and for infested mature (440 to 550) oil palm. The correlation coefficients (R2) were in a reasonably acceptable range (0.62 to 0.88). The vegetation indices based on LARS images, provided satisfactory results when compared to other approaches. The developed technology showed promising scope for medium and large plantations.",
keywords = "chlorophyll content, image processing, LARS, oil palm infestation, Phellinus noxius, vegetation indices",
author = "Grianggai Samseemoung and Jayasuriya, {Hemantha P W} and Peeyush Soni",
year = "2011",
doi = "10.1117/1.3609843",
language = "English",
volume = "5",
journal = "Journal of Applied Remote Sensing",
issn = "1931-3195",
publisher = "SPIE",
number = "1",

}

TY - JOUR

T1 - Oil palm pest infestation monitoring and evaluation by helicopter-mounted, low altitude remote sensing platform

AU - Samseemoung, Grianggai

AU - Jayasuriya, Hemantha P W

AU - Soni, Peeyush

PY - 2011

Y1 - 2011

N2 - Timely detection of pest or disease infections is extremely important for controlling the spread of disease and preventing crop productivity losses. A specifically designed radio-controlled helicopter mounted low altitude remote sensing (LARS) platform can offer near-real-time results upon user demand. The acquired LARS images were processed to estimate vegetative-indices and thereby detecting upper stem rot (Phellinus Noxius) disease in both young and mature oil palm plants. The indices helped discriminate healthy and infested plants by visualization, analysis and presentation of digital imagery software, which were validated with ground truth data. Good correlations and clear data clusters were obtained in characteristic plots of normalized difference vegetation index (NDVI)LARS and green normalized difference vegetation index LARS against NDVISpectro and chlorophyll content, by which infested plants were discriminated from healthy plants in both young and mature crops. The chlorophyll content values (μmol m-2) showed notable differences among clusters for healthy young (972 to 1100), for infested young (253 to 400), for healthy mature (1210 to 1500), and for infested mature (440 to 550) oil palm. The correlation coefficients (R2) were in a reasonably acceptable range (0.62 to 0.88). The vegetation indices based on LARS images, provided satisfactory results when compared to other approaches. The developed technology showed promising scope for medium and large plantations.

AB - Timely detection of pest or disease infections is extremely important for controlling the spread of disease and preventing crop productivity losses. A specifically designed radio-controlled helicopter mounted low altitude remote sensing (LARS) platform can offer near-real-time results upon user demand. The acquired LARS images were processed to estimate vegetative-indices and thereby detecting upper stem rot (Phellinus Noxius) disease in both young and mature oil palm plants. The indices helped discriminate healthy and infested plants by visualization, analysis and presentation of digital imagery software, which were validated with ground truth data. Good correlations and clear data clusters were obtained in characteristic plots of normalized difference vegetation index (NDVI)LARS and green normalized difference vegetation index LARS against NDVISpectro and chlorophyll content, by which infested plants were discriminated from healthy plants in both young and mature crops. The chlorophyll content values (μmol m-2) showed notable differences among clusters for healthy young (972 to 1100), for infested young (253 to 400), for healthy mature (1210 to 1500), and for infested mature (440 to 550) oil palm. The correlation coefficients (R2) were in a reasonably acceptable range (0.62 to 0.88). The vegetation indices based on LARS images, provided satisfactory results when compared to other approaches. The developed technology showed promising scope for medium and large plantations.

KW - chlorophyll content

KW - image processing

KW - LARS

KW - oil palm infestation

KW - Phellinus noxius

KW - vegetation indices

UR - http://www.scopus.com/inward/record.url?scp=80054070328&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80054070328&partnerID=8YFLogxK

U2 - 10.1117/1.3609843

DO - 10.1117/1.3609843

M3 - Article

AN - SCOPUS:80054070328

VL - 5

JO - Journal of Applied Remote Sensing

JF - Journal of Applied Remote Sensing

SN - 1931-3195

IS - 1

M1 - 053540

ER -