Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soybean plantation

Grianggai Samseemoung, Peeyush Soni, Hemantha P W Jayasuriya, Vilas M. Salokhe

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

Crop growth and weed infestation in a soybean field were monitored by processing low altitude remote sensing (LARS) images taken from crane-mounted and unmanned radio controlled helicopter-mounted platforms. Images were taken for comparison between true color (R-G-B) and color-infrared (NIR) digital cameras acquired at different heights above ground. All LARS images were processed to estimate vegetation-indices for distinguishing stages of crop growth and estimating weed density. LARS images from the two platforms (low-dynamic and high-dynamic) were evaluated. It was found that crane-mounted RGBC and NIRC platforms resulted in better quality images at lower altitudes (10 m. Comparison of NDVIC and NDVIH images showed that NDVI values at 28 DAG (days after germination) exhibited a strong relationship with altitudes used to capture images (R 2 of 0.75 for NDVIC and 0.79 for NDVIH). However, high altitudes (>10 m) decreased NDVI values for both systems. Higher R 2 values (≥0.7) were also obtained between indices estimated from crane-and helicopter-mounted images with those obtained using an on-ground spectrometer, which showed an adequate suitability of the proposed LARS platform systems for crop growth and weed infestation detection. Further, chlorophyll content was well correlated with the indices from these images with high R 2 values (>0.75) for 7, 14, 21 and 28 DAG.

Original languageEnglish
Pages (from-to)611-627
Number of pages17
JournalPrecision Agriculture
Volume13
Issue number6
DOIs
Publication statusPublished - Dec 2012

Fingerprint

Soybeans
remote sensing
plantations
weeds
soybeans
monitoring
crops
Growth
helicopters
Aircraft
Germination
Color
germination
color
Chlorophyll
spectrometers
Radio
cameras
radio
chlorophyll

Keywords

  • Crane-mounted image acquisition
  • Crop growth monitoring
  • Helicopter-mounted image acquisition
  • NDVI
  • Weed detection

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)

Cite this

Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soybean plantation. / Samseemoung, Grianggai; Soni, Peeyush; Jayasuriya, Hemantha P W; Salokhe, Vilas M.

In: Precision Agriculture, Vol. 13, No. 6, 12.2012, p. 611-627.

Research output: Contribution to journalArticle

@article{3e68046a05de44d4aa45c2f8bad5d32f,
title = "Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soybean plantation",
abstract = "Crop growth and weed infestation in a soybean field were monitored by processing low altitude remote sensing (LARS) images taken from crane-mounted and unmanned radio controlled helicopter-mounted platforms. Images were taken for comparison between true color (R-G-B) and color-infrared (NIR) digital cameras acquired at different heights above ground. All LARS images were processed to estimate vegetation-indices for distinguishing stages of crop growth and estimating weed density. LARS images from the two platforms (low-dynamic and high-dynamic) were evaluated. It was found that crane-mounted RGBC and NIRC platforms resulted in better quality images at lower altitudes (10 m. Comparison of NDVIC and NDVIH images showed that NDVI values at 28 DAG (days after germination) exhibited a strong relationship with altitudes used to capture images (R 2 of 0.75 for NDVIC and 0.79 for NDVIH). However, high altitudes (>10 m) decreased NDVI values for both systems. Higher R 2 values (≥0.7) were also obtained between indices estimated from crane-and helicopter-mounted images with those obtained using an on-ground spectrometer, which showed an adequate suitability of the proposed LARS platform systems for crop growth and weed infestation detection. Further, chlorophyll content was well correlated with the indices from these images with high R 2 values (>0.75) for 7, 14, 21 and 28 DAG.",
keywords = "Crane-mounted image acquisition, Crop growth monitoring, Helicopter-mounted image acquisition, NDVI, Weed detection",
author = "Grianggai Samseemoung and Peeyush Soni and Jayasuriya, {Hemantha P W} and Salokhe, {Vilas M.}",
year = "2012",
month = "12",
doi = "10.1007/s11119-012-9271-8",
language = "English",
volume = "13",
pages = "611--627",
journal = "Precision Agriculture",
issn = "1385-2256",
publisher = "Springer Netherlands",
number = "6",

}

TY - JOUR

T1 - Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soybean plantation

AU - Samseemoung, Grianggai

AU - Soni, Peeyush

AU - Jayasuriya, Hemantha P W

AU - Salokhe, Vilas M.

PY - 2012/12

Y1 - 2012/12

N2 - Crop growth and weed infestation in a soybean field were monitored by processing low altitude remote sensing (LARS) images taken from crane-mounted and unmanned radio controlled helicopter-mounted platforms. Images were taken for comparison between true color (R-G-B) and color-infrared (NIR) digital cameras acquired at different heights above ground. All LARS images were processed to estimate vegetation-indices for distinguishing stages of crop growth and estimating weed density. LARS images from the two platforms (low-dynamic and high-dynamic) were evaluated. It was found that crane-mounted RGBC and NIRC platforms resulted in better quality images at lower altitudes (10 m. Comparison of NDVIC and NDVIH images showed that NDVI values at 28 DAG (days after germination) exhibited a strong relationship with altitudes used to capture images (R 2 of 0.75 for NDVIC and 0.79 for NDVIH). However, high altitudes (>10 m) decreased NDVI values for both systems. Higher R 2 values (≥0.7) were also obtained between indices estimated from crane-and helicopter-mounted images with those obtained using an on-ground spectrometer, which showed an adequate suitability of the proposed LARS platform systems for crop growth and weed infestation detection. Further, chlorophyll content was well correlated with the indices from these images with high R 2 values (>0.75) for 7, 14, 21 and 28 DAG.

AB - Crop growth and weed infestation in a soybean field were monitored by processing low altitude remote sensing (LARS) images taken from crane-mounted and unmanned radio controlled helicopter-mounted platforms. Images were taken for comparison between true color (R-G-B) and color-infrared (NIR) digital cameras acquired at different heights above ground. All LARS images were processed to estimate vegetation-indices for distinguishing stages of crop growth and estimating weed density. LARS images from the two platforms (low-dynamic and high-dynamic) were evaluated. It was found that crane-mounted RGBC and NIRC platforms resulted in better quality images at lower altitudes (10 m. Comparison of NDVIC and NDVIH images showed that NDVI values at 28 DAG (days after germination) exhibited a strong relationship with altitudes used to capture images (R 2 of 0.75 for NDVIC and 0.79 for NDVIH). However, high altitudes (>10 m) decreased NDVI values for both systems. Higher R 2 values (≥0.7) were also obtained between indices estimated from crane-and helicopter-mounted images with those obtained using an on-ground spectrometer, which showed an adequate suitability of the proposed LARS platform systems for crop growth and weed infestation detection. Further, chlorophyll content was well correlated with the indices from these images with high R 2 values (>0.75) for 7, 14, 21 and 28 DAG.

KW - Crane-mounted image acquisition

KW - Crop growth monitoring

KW - Helicopter-mounted image acquisition

KW - NDVI

KW - Weed detection

UR - http://www.scopus.com/inward/record.url?scp=84868629417&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84868629417&partnerID=8YFLogxK

U2 - 10.1007/s11119-012-9271-8

DO - 10.1007/s11119-012-9271-8

M3 - Article

VL - 13

SP - 611

EP - 627

JO - Precision Agriculture

JF - Precision Agriculture

SN - 1385-2256

IS - 6

ER -