NISFARIZA MOHD NOOR - University of Malaya, Malaysia (original) (raw)

Papers by NISFARIZA MOHD NOOR

ción aérea para una imple mentación más rápida del control de la enfermedad de PBE por Ganoderma.... more ción aérea para una imple mentación más rápida del control de la enfermedad de PBE por Ganoderma. El estudio inicial se realizó para investigar la posibilidad de utilizar la telede tección hiperespectral como herramienta para la detección temprana de esta enfermedad; se llevó a cabo en tres niveles experi-

Ethnics in coalition: An analysis of stronghold state level party’s performance and trend

Geografia, Feb 29, 2024

Advances in Agricultural and Food Research Journal, Sep 24, 2022

Rice (Oryza sativa L.) is an essential staple food not only for Asians but also for people worldw... more Rice (Oryza sativa L.) is an essential staple food not only for Asians but also for people worldwide. However, weeds in rice fields can cause yield reduction due to their tendency to compete for resources. These significant biological obstacles can potentially cause complete yield loss if inappropriately managed. In addition, future climate change can cause rice weeds to become more competitive against cultivated rice plants by providing new favourable conditions for the unwanted species to expand aggressively. As the effect of climate change on rice weeds has been studied, the abiotic parameters, including carbon dioxide concentration, atmospheric temperature, drought, and soil salinity, can be used to construct predictive modelling to forecast rice weed infestation. Suppose the weed invasion in rice fields can be predicted accurately based on the weather information. In that case, the farmers can prepare the countermeasure early to avoid high yield loss. However, some challenges must be faced by the researchers as the weed invasion depends not only on the climate alone. This review summarises the effect of climatic variation on weed infestation in rice fields. It also discusses how predictive modelling had been developed based on the information on the environmental conditions.

Weed Management Using UAV and Remote Sensing in Malaysia Paddy Field: A Review

Pertanika journal of science & technology, Apr 4, 2024

Detection of Sedge Weeds Infestation in Wetland Rice Cultivation Using Hyperspectral Images and Artificial Intelligence: A Review

Pertanika journal of science & technology, Apr 4, 2024

International Journal of Remote Sensing, Aug 2, 2011

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as ... more Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries-Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.

Applied Ecology and Environmental Research, 2019

Rapid urbanization that caused urban sprawl is a major worldwide concern. In this study an assess... more Rapid urbanization that caused urban sprawl is a major worldwide concern. In this study an assessment of urban sprawl was carried out based on Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) variation in Sepang, Malaysia. The land cover classification consisted of Built-up Area (BUA), Vegetation Area (VA), Open Space Area (OSA), and Water Bodies (WB) from 1990 to 2018. Supervised classification based on maximum likelihood techniques were used to identify the land use classes. Based on the analysis of LULC, the majority of VA (i.e. forest field) was transformed into OSA and gradually the land was converted into BUA. Observation within 25 years, supported by NDVI and NDBI has discovered a consistent increase of BUA while contrastingly a decline of VA, while WB and OSA are suspected to have inconsistently varying highs and lows. This study has demonstrated that urban sprawl caused by rapid urbanization has not favour the population. Without proper planning and growth control, urban sprawl in Sepang would have undesirable consequences to the quality of life and the environment. Therefore, comprehensive land use and progressive environmental change can serve as prognostic measures to mitigate urban sprawl, and to achieve sustainable urbanization and to carry out effective planning and decision making.

Concepts and Applications of Remote Sensing in Forestry, 2022

The ecosystems of rainforests in Peninsular Malaysia are complex. The assessment and monitoring u... more The ecosystems of rainforests in Peninsular Malaysia are complex. The assessment and monitoring using the traditional land-based survey methods for these ecosystems are costly and time-consuming. It is an advantage for remote surveillance, especially when dealing with inaccessible areas. Remote sensing for forests mapping, species distribution, aboveground biomass, and carbon stocks allocation is emerging at this very moment. The technology enables regular monitoring of difficult forest areas and data captured from remote sensors analysed for the deduction and information gathering of the local and world forest cover. Each object reflects unique electromagnetic radiation, which is the foundation behind spectral identification. Vegetation covers such as agricultural plots, urban forestry, or urban landscape are simple due to the accessibility of the and limited numbers of species. However, remote sensing of tropical forests is a big challenge due to the hilly surface and the abundant species. Remote sensors are developed using different utility types of sensing approaches for observing the earth surfaces, namely, the optical sensors (multispectral and hyperspectral), RADAR, and LiDAR. Hyperspectral can harvest the minute disparity or changes of the reflectance of a vegetation cover. The use of hyperspectral for vegetation spans from vegetation species identification, pest and disease detection, and many more. This chapter presents the use of spectroscopy sensors and analytics to discriminate the several species of dipterocarp in forest areas of Semangkok, Selangor, and their spectral library and general distribution of the forest species with their biophysical properties in the montane strata.

Keywords
Dipterocarp
Hyperspectral
Species identification
Spectral reflectance

Landsat observation of urban growth and land use change using NDVI and NDBI analysis

IOP Conference Series: Earth and Environmental Science

Landsat observation has numerous potentials as a quantitative approach in regional scale monitori... more Landsat observation has numerous potentials as a quantitative approach in regional scale monitoring of urban growth and environmental change. To achieve this approach, three Landsat data of year 1991 (TM), 2005 (ETM+) and 2019 (OLI-TIRS) has been acquired, classified, and accurately assessed. The research assesses spatio-temporal urban growth, its pattern and land use land cover (LULC) changes of using Normalized Difference Vegetation Index (NDVI) and Normalized Difference Building Index (NDBI) analysis. NDVI were performed for vegetation monitoring especially on loss of vegetation land while NDBI were performed for identification of dense urban and built-up areas. The NDVI and NDBI density results show a significant decreased of vegetation land and a leap up increased of urban and built-up land use. This indicates a significant rapid growth development and a vast transformation of agricultural and forest land into low density development. A rapid urban growth of regional developmen...

International Journal of Remote Sensing, 2017

Field spectroscopy is a rapid and non-destructive analytical technique that may be used for asses... more Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from three levels of Ganoderma disease severity were acquired using a spectroradiometer. Denoizing and data transformation using first derivative analysis was conducted on the original reflectance spectra. Then, comparative statistical analysis was used to select significant wavelength from transformed data. Wavelength pairs of spectral indices were selected using optimum index factor. The spectral indices were produced using the wavelength ratios and a modified simple ratio method. The relationship analysis between spectral indices and total leaf chlorophyll (TLC) was conducted using regression technique. The results suggested that six spectral indices are suitable for the early detection of Ganoderma disease in oil palm seedlings. Final results after regression with TLC showed that Ratio 3 is the best spectral index for the early detection of Ganoderma infection in oil palm seedlings. For future works, this can be used for the development of robust spectral indices for Ganoderma disease detection in young and mature oil palm using airborne hyperspectral imaging.

Field Spectroscopy for Detection of Ganoderma Disease in Oil Palm

ABSTRACT he Basal Stem Rot (BSR) disease caused by Ganoderma boninense has caused huge economic l... more ABSTRACT he Basal Stem Rot (BSR) disease caused by Ganoderma boninense has caused huge economic losses to oil palm plantations (Roslan and Idris, 2012). The disease can be diagnosed based on the presence of basidiomata of the pathogen on the stem base or frond bases or roots (Idris and Ariffin, 2004). Several technologies have been developed for the detection of the Ganoderma disease in oil palm, namely Ganoderma Selective Medium (GSM) (Ariffin et al., 1993); Polyclonal Antibodies Enzyme-Linked Immunosorbent Assay (PAbs-ELISA) (Idris and Rafidah, 2008); Multiplex PCR-DNA Kit (Idris et al., 2010); and GanoSken Tomography (Idris et al., 2010). Another technology known as field spectroscopy can also be used for the detection of Ganoderma disease in oil palm. Field spectroscopy is a hyperspectral remote sensing (HRS) technique that provides non-destructive measurement to differentiate healthy and infected oil palm (Izzuddin, 2010; Shafri et al., 2011; Nishfasriza, 2012). The field spectroscopy technique refers to the application of a hand-held spectroradiometer to retrieve spectral reflectances from oil palm canopy and leaves. Spectral reflectances are measured as percentages of reflectances from the oil palm canopy and leaves after the illumination of sunlight within a certain spectrum range. OBJECTIVES 1. To identify significant wavelengths suitable for the detection of Ganoderma disease in oil palm. 2. To develop a field spectroscopy system for the detection of Ganoderma disease in oil palm. 3. To assess the accuracy of the field spectros-copy system for the detection of the Ganoder-ma disease in oil palm. T METHODOLOGY The field spectroscopy system (Figure 1) used consisted of a spectroradiometer sensor, white reflectance calibration, fibre optic cable and data processing software called Oil Palm Spectral Analyser System (OPSAS). Figure 1. Field spectroscopy system. The samplings were conducted at the canopy-level of immature oil palm and at leaves-level of young and mature oil palm (Figure 2). The palms were initially confirmed to be infected by the Ganoder-ma disease using GSM. Spectral reflectances were acquired from over 512 wavelengths from 273.13 nanometer (nm) to 1099.57 nm with an average spectral resolution of 1.6 nm. The spectral reflectances measured from oil palm were calculated using the following equation: Reflectance σ,θ =

International Journal of Remote Sensing, 2011

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as ... more Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries-Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.

Applied Sciences, 2022

Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients... more Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have been developed in recent years to increase weed detection speed and accuracy, resolving the contradiction between the goals of enhancing soil health and achieving sufficient weed control for profitable farming. In recent years, a variety of platforms, such as satellites, airplanes, unmanned aerial vehicles (UAVs), and close-range platforms, have become more commonly available for gathering hyperspectral images with varying spatial, temporal, and spectral resolutions. Plants must be divided into crops and weeds based on their species for successful weed detection. Therefore, hyperspectral image categorization also has become popular since the development of hyperspectral image technology. Unmanned aerial vehicle (UAV) hyperspectral i...

Applied Sciences, 2022

Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients... more Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have been developed in recent years to increase weed detection speed and accuracy, resolving the contradiction between the goals of enhancing soil health and achieving sufficient weed control for profitable farming. In recent years, a variety of platforms, such as satellites, airplanes, unmanned aerial vehicles (UAVs), and close-range platforms, have become more commonly available for gathering hyperspectral images with varying spatial, temporal, and spectral resolutions. Plants must be divided into crops and weeds based on their species for successful weed detection. Therefore, hyperspectral image categorization also has become popular since the development of hyperspectral image technology. Unmanned aerial vehicle (UAV) hyperspectral i...

Land Use Dynamics and Governance in the Sungai Selangor Watershed

Spatial Patterns of Ganoderma Basal Stem Rot Disease in Oil Palm Plantations in Sarawak, Malaysia

ABSTRACT The Geographical Information System (GIS) and Geostatistics were used to examine the spa... more ABSTRACT The Geographical Information System (GIS) and Geostatistics were used to examine the spatial variation of Basal Stem Rot (BSR) disease in oil palm planted in Miri (Plantations A and B) and in Kuching (Plantation C) in Sarawak, Malaysia. The disease caused by three species of Ganoderma, a basidiomycete fungus, they are G. boninense, G. zonatum and G. miniatocinctum. The BSR disease development in oil palm planted in three plantations A, B and C, was assessed from 12 until 24 years after planting to generate information about temporal, spatial spread and hotspots of the disease. Semivariogram analysis was performed on the data to show the spatio-temporal structure of BSR disease at 12, 18 and 24 years after planting. The disease was observed in all three plantations with 0.12% to 0.27% at 12 years after planting and increased to 9.74% to 18.63% at 24 years after planting. Effects of nugget to sill were found relatively moderate to weak of spatial pattern distribution. The observed disease patterns suggest that the progress of BSR disease incidence is firstly randomly scattered (12 to 18 years after planting) and secondly by root-to-root contact of the disease spreading to neighbouring palms may be occurred. Further study is needed to investigate factors associated with the outbreak of BSR disease in these plantations.

Non-Invasive Determination of Chlorophyll Content in Oil Palm Seedlings using Field Spectroscopy

Chlorophyll content and greenness index are frequently used as a basis in determining the vigor a... more Chlorophyll content and greenness index are frequently used as a basis in determining the vigor and health of vegetation and explaining the physiological and pathological properties of plants. This paper evaluates the estimation of chlorophyll content in oil palm seedlings in nursery using destructive and non-destructive sampling and their relationships with the foliar hyperspectral indices. Foliar reflectance was measured using GER1500 spectroradiometer concurrent with in situ measurement of foliar chlorophyll and sampling. Foliar chlorophyll was acquired using Minolta Chlorophyll Meter SPAD-502 and Total Leaf Chlorophyll (TLC) of foliar was determined using the spectrophotometry method. The spectra of oil palm were transformed using published indices which have been ascertained as an excellent indicator to indicate foliar chlorophyll and plant vigorousness. The SPAD readings were correlated with oil palm leaf chlorophyll contents extracted in the laboratory to establish the calibr...

El uso de sensores remotos para detectar la infección por Ganoderma

El estudio del uso de la teledeteccion para la enfermedad de la Pudricion basal del estipite (PBE... more El estudio del uso de la teledeteccion para la enfermedad de la Pudricion basal del estipite (PBE) de la palma de aceite por parte de la Mesa de Aceite de Palma de Malasia (Malaysian Palm Oil Board) inicio en 2008. Se efectuaron diversos estudios para analizar las propiedades fisiologicas y fenologicas de la palma de aceite y la interaccion entre las radiaciones electromagneticas y la enfermedad de la PBE por Ganoderma. Existe la necesidad de desarrollar tecnologias de deteccion de la PBE basada en teledeteccion aerea para una implementacion mas rapida del control de la enfermedad de PBE por Ganoderma. El estudio inicial se realizo para investigar la posibilidad de utilizar la teledeteccion hiperespectral como herramienta para la deteccion temprana de esta enfermedad; se llevo a cabo en tres niveles experimentales: en el vivero, en el campo y en el aire, utilizando dos sensores hiperespectrales: el espectrorradiometro manual (GER 1500) y el sistema de imagenes hiperespectrales (AISA...

SPOT Imagery Observation on Mangrove Changes Using NDVI Density Analysis: The Case of Sepang Besar River, Malaysia

the arab world geographer, 2020

ción aérea para una imple mentación más rápida del control de la enfermedad de PBE por Ganoderma.... more ción aérea para una imple mentación más rápida del control de la enfermedad de PBE por Ganoderma. El estudio inicial se realizó para investigar la posibilidad de utilizar la telede tección hiperespectral como herramienta para la detección temprana de esta enfermedad; se llevó a cabo en tres niveles experi-

Ethnics in coalition: An analysis of stronghold state level party’s performance and trend

Geografia, Feb 29, 2024

Advances in Agricultural and Food Research Journal, Sep 24, 2022

Rice (Oryza sativa L.) is an essential staple food not only for Asians but also for people worldw... more Rice (Oryza sativa L.) is an essential staple food not only for Asians but also for people worldwide. However, weeds in rice fields can cause yield reduction due to their tendency to compete for resources. These significant biological obstacles can potentially cause complete yield loss if inappropriately managed. In addition, future climate change can cause rice weeds to become more competitive against cultivated rice plants by providing new favourable conditions for the unwanted species to expand aggressively. As the effect of climate change on rice weeds has been studied, the abiotic parameters, including carbon dioxide concentration, atmospheric temperature, drought, and soil salinity, can be used to construct predictive modelling to forecast rice weed infestation. Suppose the weed invasion in rice fields can be predicted accurately based on the weather information. In that case, the farmers can prepare the countermeasure early to avoid high yield loss. However, some challenges must be faced by the researchers as the weed invasion depends not only on the climate alone. This review summarises the effect of climatic variation on weed infestation in rice fields. It also discusses how predictive modelling had been developed based on the information on the environmental conditions.

Weed Management Using UAV and Remote Sensing in Malaysia Paddy Field: A Review

Pertanika journal of science & technology, Apr 4, 2024

Detection of Sedge Weeds Infestation in Wetland Rice Cultivation Using Hyperspectral Images and Artificial Intelligence: A Review

Pertanika journal of science & technology, Apr 4, 2024

International Journal of Remote Sensing, Aug 2, 2011

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as ... more Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries-Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.

Applied Ecology and Environmental Research, 2019

Rapid urbanization that caused urban sprawl is a major worldwide concern. In this study an assess... more Rapid urbanization that caused urban sprawl is a major worldwide concern. In this study an assessment of urban sprawl was carried out based on Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) variation in Sepang, Malaysia. The land cover classification consisted of Built-up Area (BUA), Vegetation Area (VA), Open Space Area (OSA), and Water Bodies (WB) from 1990 to 2018. Supervised classification based on maximum likelihood techniques were used to identify the land use classes. Based on the analysis of LULC, the majority of VA (i.e. forest field) was transformed into OSA and gradually the land was converted into BUA. Observation within 25 years, supported by NDVI and NDBI has discovered a consistent increase of BUA while contrastingly a decline of VA, while WB and OSA are suspected to have inconsistently varying highs and lows. This study has demonstrated that urban sprawl caused by rapid urbanization has not favour the population. Without proper planning and growth control, urban sprawl in Sepang would have undesirable consequences to the quality of life and the environment. Therefore, comprehensive land use and progressive environmental change can serve as prognostic measures to mitigate urban sprawl, and to achieve sustainable urbanization and to carry out effective planning and decision making.

Concepts and Applications of Remote Sensing in Forestry, 2022

The ecosystems of rainforests in Peninsular Malaysia are complex. The assessment and monitoring u... more The ecosystems of rainforests in Peninsular Malaysia are complex. The assessment and monitoring using the traditional land-based survey methods for these ecosystems are costly and time-consuming. It is an advantage for remote surveillance, especially when dealing with inaccessible areas. Remote sensing for forests mapping, species distribution, aboveground biomass, and carbon stocks allocation is emerging at this very moment. The technology enables regular monitoring of difficult forest areas and data captured from remote sensors analysed for the deduction and information gathering of the local and world forest cover. Each object reflects unique electromagnetic radiation, which is the foundation behind spectral identification. Vegetation covers such as agricultural plots, urban forestry, or urban landscape are simple due to the accessibility of the and limited numbers of species. However, remote sensing of tropical forests is a big challenge due to the hilly surface and the abundant species. Remote sensors are developed using different utility types of sensing approaches for observing the earth surfaces, namely, the optical sensors (multispectral and hyperspectral), RADAR, and LiDAR. Hyperspectral can harvest the minute disparity or changes of the reflectance of a vegetation cover. The use of hyperspectral for vegetation spans from vegetation species identification, pest and disease detection, and many more. This chapter presents the use of spectroscopy sensors and analytics to discriminate the several species of dipterocarp in forest areas of Semangkok, Selangor, and their spectral library and general distribution of the forest species with their biophysical properties in the montane strata.

Keywords
Dipterocarp
Hyperspectral
Species identification
Spectral reflectance

Landsat observation of urban growth and land use change using NDVI and NDBI analysis

IOP Conference Series: Earth and Environmental Science

Landsat observation has numerous potentials as a quantitative approach in regional scale monitori... more Landsat observation has numerous potentials as a quantitative approach in regional scale monitoring of urban growth and environmental change. To achieve this approach, three Landsat data of year 1991 (TM), 2005 (ETM+) and 2019 (OLI-TIRS) has been acquired, classified, and accurately assessed. The research assesses spatio-temporal urban growth, its pattern and land use land cover (LULC) changes of using Normalized Difference Vegetation Index (NDVI) and Normalized Difference Building Index (NDBI) analysis. NDVI were performed for vegetation monitoring especially on loss of vegetation land while NDBI were performed for identification of dense urban and built-up areas. The NDVI and NDBI density results show a significant decreased of vegetation land and a leap up increased of urban and built-up land use. This indicates a significant rapid growth development and a vast transformation of agricultural and forest land into low density development. A rapid urban growth of regional developmen...

International Journal of Remote Sensing, 2017

Field spectroscopy is a rapid and non-destructive analytical technique that may be used for asses... more Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from three levels of Ganoderma disease severity were acquired using a spectroradiometer. Denoizing and data transformation using first derivative analysis was conducted on the original reflectance spectra. Then, comparative statistical analysis was used to select significant wavelength from transformed data. Wavelength pairs of spectral indices were selected using optimum index factor. The spectral indices were produced using the wavelength ratios and a modified simple ratio method. The relationship analysis between spectral indices and total leaf chlorophyll (TLC) was conducted using regression technique. The results suggested that six spectral indices are suitable for the early detection of Ganoderma disease in oil palm seedlings. Final results after regression with TLC showed that Ratio 3 is the best spectral index for the early detection of Ganoderma infection in oil palm seedlings. For future works, this can be used for the development of robust spectral indices for Ganoderma disease detection in young and mature oil palm using airborne hyperspectral imaging.

Field Spectroscopy for Detection of Ganoderma Disease in Oil Palm

ABSTRACT he Basal Stem Rot (BSR) disease caused by Ganoderma boninense has caused huge economic l... more ABSTRACT he Basal Stem Rot (BSR) disease caused by Ganoderma boninense has caused huge economic losses to oil palm plantations (Roslan and Idris, 2012). The disease can be diagnosed based on the presence of basidiomata of the pathogen on the stem base or frond bases or roots (Idris and Ariffin, 2004). Several technologies have been developed for the detection of the Ganoderma disease in oil palm, namely Ganoderma Selective Medium (GSM) (Ariffin et al., 1993); Polyclonal Antibodies Enzyme-Linked Immunosorbent Assay (PAbs-ELISA) (Idris and Rafidah, 2008); Multiplex PCR-DNA Kit (Idris et al., 2010); and GanoSken Tomography (Idris et al., 2010). Another technology known as field spectroscopy can also be used for the detection of Ganoderma disease in oil palm. Field spectroscopy is a hyperspectral remote sensing (HRS) technique that provides non-destructive measurement to differentiate healthy and infected oil palm (Izzuddin, 2010; Shafri et al., 2011; Nishfasriza, 2012). The field spectroscopy technique refers to the application of a hand-held spectroradiometer to retrieve spectral reflectances from oil palm canopy and leaves. Spectral reflectances are measured as percentages of reflectances from the oil palm canopy and leaves after the illumination of sunlight within a certain spectrum range. OBJECTIVES 1. To identify significant wavelengths suitable for the detection of Ganoderma disease in oil palm. 2. To develop a field spectroscopy system for the detection of Ganoderma disease in oil palm. 3. To assess the accuracy of the field spectros-copy system for the detection of the Ganoder-ma disease in oil palm. T METHODOLOGY The field spectroscopy system (Figure 1) used consisted of a spectroradiometer sensor, white reflectance calibration, fibre optic cable and data processing software called Oil Palm Spectral Analyser System (OPSAS). Figure 1. Field spectroscopy system. The samplings were conducted at the canopy-level of immature oil palm and at leaves-level of young and mature oil palm (Figure 2). The palms were initially confirmed to be infected by the Ganoder-ma disease using GSM. Spectral reflectances were acquired from over 512 wavelengths from 273.13 nanometer (nm) to 1099.57 nm with an average spectral resolution of 1.6 nm. The spectral reflectances measured from oil palm were calculated using the following equation: Reflectance σ,θ =

International Journal of Remote Sensing, 2011

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as ... more Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries-Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.

Applied Sciences, 2022

Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients... more Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have been developed in recent years to increase weed detection speed and accuracy, resolving the contradiction between the goals of enhancing soil health and achieving sufficient weed control for profitable farming. In recent years, a variety of platforms, such as satellites, airplanes, unmanned aerial vehicles (UAVs), and close-range platforms, have become more commonly available for gathering hyperspectral images with varying spatial, temporal, and spectral resolutions. Plants must be divided into crops and weeds based on their species for successful weed detection. Therefore, hyperspectral image categorization also has become popular since the development of hyperspectral image technology. Unmanned aerial vehicle (UAV) hyperspectral i...

Applied Sciences, 2022

Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients... more Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have been developed in recent years to increase weed detection speed and accuracy, resolving the contradiction between the goals of enhancing soil health and achieving sufficient weed control for profitable farming. In recent years, a variety of platforms, such as satellites, airplanes, unmanned aerial vehicles (UAVs), and close-range platforms, have become more commonly available for gathering hyperspectral images with varying spatial, temporal, and spectral resolutions. Plants must be divided into crops and weeds based on their species for successful weed detection. Therefore, hyperspectral image categorization also has become popular since the development of hyperspectral image technology. Unmanned aerial vehicle (UAV) hyperspectral i...

Land Use Dynamics and Governance in the Sungai Selangor Watershed

Spatial Patterns of Ganoderma Basal Stem Rot Disease in Oil Palm Plantations in Sarawak, Malaysia

ABSTRACT The Geographical Information System (GIS) and Geostatistics were used to examine the spa... more ABSTRACT The Geographical Information System (GIS) and Geostatistics were used to examine the spatial variation of Basal Stem Rot (BSR) disease in oil palm planted in Miri (Plantations A and B) and in Kuching (Plantation C) in Sarawak, Malaysia. The disease caused by three species of Ganoderma, a basidiomycete fungus, they are G. boninense, G. zonatum and G. miniatocinctum. The BSR disease development in oil palm planted in three plantations A, B and C, was assessed from 12 until 24 years after planting to generate information about temporal, spatial spread and hotspots of the disease. Semivariogram analysis was performed on the data to show the spatio-temporal structure of BSR disease at 12, 18 and 24 years after planting. The disease was observed in all three plantations with 0.12% to 0.27% at 12 years after planting and increased to 9.74% to 18.63% at 24 years after planting. Effects of nugget to sill were found relatively moderate to weak of spatial pattern distribution. The observed disease patterns suggest that the progress of BSR disease incidence is firstly randomly scattered (12 to 18 years after planting) and secondly by root-to-root contact of the disease spreading to neighbouring palms may be occurred. Further study is needed to investigate factors associated with the outbreak of BSR disease in these plantations.

Non-Invasive Determination of Chlorophyll Content in Oil Palm Seedlings using Field Spectroscopy

Chlorophyll content and greenness index are frequently used as a basis in determining the vigor a... more Chlorophyll content and greenness index are frequently used as a basis in determining the vigor and health of vegetation and explaining the physiological and pathological properties of plants. This paper evaluates the estimation of chlorophyll content in oil palm seedlings in nursery using destructive and non-destructive sampling and their relationships with the foliar hyperspectral indices. Foliar reflectance was measured using GER1500 spectroradiometer concurrent with in situ measurement of foliar chlorophyll and sampling. Foliar chlorophyll was acquired using Minolta Chlorophyll Meter SPAD-502 and Total Leaf Chlorophyll (TLC) of foliar was determined using the spectrophotometry method. The spectra of oil palm were transformed using published indices which have been ascertained as an excellent indicator to indicate foliar chlorophyll and plant vigorousness. The SPAD readings were correlated with oil palm leaf chlorophyll contents extracted in the laboratory to establish the calibr...

El uso de sensores remotos para detectar la infección por Ganoderma

El estudio del uso de la teledeteccion para la enfermedad de la Pudricion basal del estipite (PBE... more El estudio del uso de la teledeteccion para la enfermedad de la Pudricion basal del estipite (PBE) de la palma de aceite por parte de la Mesa de Aceite de Palma de Malasia (Malaysian Palm Oil Board) inicio en 2008. Se efectuaron diversos estudios para analizar las propiedades fisiologicas y fenologicas de la palma de aceite y la interaccion entre las radiaciones electromagneticas y la enfermedad de la PBE por Ganoderma. Existe la necesidad de desarrollar tecnologias de deteccion de la PBE basada en teledeteccion aerea para una implementacion mas rapida del control de la enfermedad de PBE por Ganoderma. El estudio inicial se realizo para investigar la posibilidad de utilizar la teledeteccion hiperespectral como herramienta para la deteccion temprana de esta enfermedad; se llevo a cabo en tres niveles experimentales: en el vivero, en el campo y en el aire, utilizando dos sensores hiperespectrales: el espectrorradiometro manual (GER 1500) y el sistema de imagenes hiperespectrales (AISA...

SPOT Imagery Observation on Mangrove Changes Using NDVI Density Analysis: The Case of Sepang Besar River, Malaysia

the arab world geographer, 2020

MDPI, 2022

This Special Issue on “Sustainable Agriculture and Advances of Remote Sensing” falls within the s... more This Special Issue on “Sustainable Agriculture and Advances of Remote Sensing” falls within the scope of current efforts to mitigate and adapt to the changing climate. It has been launched with the
aim of collecting and promoting recent scientific studies proposing and evaluating advances in remote sensing technology and agricultural engineering leading to sustainable agriculture. It is mainly
addressed to the policy makers, entrepreneurs and academicians engaged in the fight against climate change, in zero hunger initiatives, in natural resource management and in environment protection research. A special thanks is addressed to the authors who submitted their manuscripts to contribute to these initiatives