Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies

Zarco‐Tejada, Pablo J.; Miller, John R.; Harron, J.; Hu, Baoxin; Noland, Thomas L.; Goel, Narendra S.; Mohammed, Gina H.; Sampson, P. H.

doi:10.1016/j.rse.2002.06.002

Cited by 182 publications

(86 citation statements)

References 37 publications

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“…While foliar chlorophyll (as well as carotenoids) concentrations typically decrease when plant stress level increases, additional constituents accumulate within the leaves. Such changes affect leaf spectral properties and provide the possibility of remotely diagnosing a plant's stress level (Rock et al 1986, Martin & Aber 1997, Datt 1998, Zarco-Tejada et al 2004, Malenovský et al 2006). The reflected radiation of the visible and near infrared portions of the electromagnetic spectrum has proven to be the most important in detecting plant stress (Gitelson et al 2003).…”

Section: Introductionmentioning

confidence: 99%

Spectral reflectance properties of healthy and stressed coniferous trees

Masaitis¹,

Mozgeris²,

Augustaitis³

2013

iForest

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This study investigates the properties of hyperspectral reflectance of healthy and stressed coniferous trees. Two coniferous tree species which naturally grow in Lithuania, Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.), as well as an introduced species, Siberian pine (Pinus sibirica Du Tour), were selected for the study. Hyperspectral reflectance data were collected under laboratory conditions by scanning the needles of healthy (no foliar loss) and stressed Norway spruce (foliar loss 66-70%), Scots pine (foliar loss 71-75%) and Siberian pine (foliar loss 86-90%) trees using a Themis Vision Systems VNIR 400H hyperspectral imaging camera. The spectrometer of the camera covers the spectral range of 400-1000 nm with the sampling interval of 0.6 nm. Simultaneously, the chlorophyll a and b content in the needles was determined by spectrophotometrically measuring the needles’ absorbance of ethanol extracts. The statistical analyses included principal component analysis, analysis of variance and partial least squares regression techniques. Relatively large spectral differences between healthy and stressed trees were detected for Norway spruce needles: 884 out of 955 wavebands indicated a statistically different reflectance (p<0.05). The reflectance associated with the stress level was statistically different (p<0.05) in 767 and 698 out of 955 wavebands for Scots pine and Siberian pine, respectively. The most informative wavelengths for spectral separation between the needles taken from healthy and stressed trees were found in the following spectral ranges: 701.0-715.7 nm for Norway spruce, 706.1-718.2 nm for Scots pine, and 862.3-893.1 nm for Siberian pine. The relationship between the spectral reflectance properties of the needles and their chlorophyll content was also determined for each species. Waveband ranges (as well as single bands) most sensitive to changes in chlorophyll content were: 709.9-722.1 nm (715.6 nm) for Norway spruce; 709.3-721.4 nm (715.0 nm) for Scots pine; 710.6-722.7 nm (720.1 nm) for Siberian pine. In general, the study revealed that narrow-band based hyperspectral imaging has the potential for accurately detecting stress in coniferous trees

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Section: Introductionmentioning

confidence: 99%

Spectral reflectance properties of healthy and stressed coniferous trees

Masaitis¹,

Mozgeris²,

Augustaitis³

2013

iForest

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“…[16,[49][50][51][52][53]. The indices VOG1, ZM and GM1 have also been proven to correlate with chlorophyll content [16,54,55]. Taking into account that VOG and ZM are simple ratios centered around 730 nm (red), both can be considered as gross estimators of the REIP.…”

Section: Could Nitrogen Deficiency Stress Be Detected By the Sensors?mentioning

confidence: 99%

Using Optical Sensors to Identify Water Deprivation, Nitrogen Shortage, Weed Presence and Fungal Infection in Wheat

et al. 2016

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Abstract:The success of precision agriculture relies largely on our ability to identify how the plants' growth limiting factors vary in time and space. In the field, several stress factors may occur simultaneously, and it is thus crucial to be able to identify the key limitation, in order to decide upon the correct contra-action, e.g., herbicide application. We performed a pot experiment, in which spring wheat was exposed to water shortage, nitrogen deficiency, weed competition (Sinapis alba L.) and fungal infection (Blumeria graminis f. sp. tritici) in a complete, factorial design. A range of sensor measurements were taken every third day from the two-leaf stage until booting of the wheat (BBCH 12 to 40). Already during the first 10 days after stress induction (DAS), both fluorescence measurements and spectral vegetation indices were able to differentiate between non-stressed and stressed wheat plants exposed to water shortage, weed competition or fungal infection. This meant that water shortage and fungal infection could be detected prior to visible symptoms. Nitrogen shortage was detected on the 11-20 DAS. Differentiation of more than one stress factors with the same index was difficult.

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“…Because stress symptoms in the early phase of a drought period might be expected to produce only subtle spectral variations at the canopy level, it was considered useful to focus the analysis on exclusively illuminated deciduous tree crowns (see also [48]). For eliminating the potentially disturbing influence of shaded crowns and canopy openings with different background materials (e.g., access roads, dry grass, bare soil, exposed rock) from the "HySpex2.5" data set, an approach termed iterative spectral mixture analysis (ISMA) was used.…”

Section: Tree Crown Identificationmentioning

confidence: 99%

The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities

et al. 2015

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Given the importance of forest ecosystems, the availability of reliable, spatially explicit information about the site-specific climate sensitivity of tree species is essential for implementing suitable adaptation strategies. In this study, airborne hyperspectral data were used to assess the response of deciduous species (dominated by European beech and Sessile and Pedunculate oak) to water stress during a summery dry spell. After masking canopy gaps, shaded crown areas and non-deciduous species, potentially indicative spectral indices, the Photochemical Reflectance Index (PRI), Moisture Stress Index (MSI), Normalized Difference Water Index (NDWI), and Chlorophyll Index (CI), were analyzed with respect to available maps of site-specific soil moisture regimes. PRI provided an important indication of site-specific photosynthetic stress on leaf level in relation to limitations in soil water availability. The CI, MSI and NDWI revealed statistically significant differences in total chlorophyll and water concentration at the canopy level. However, after reducing the canopy effects by normalizing these indices with respect to the structure-sensitive simple ratio (SR) vegetation index, it was not yet possible to identify site-specific concentration differences in leaf level at this early stage of the drought. The selected indicators were also tested with simulated EnMAP and Sentinel-2 data (derived from the original airborne data set). While PRI proved to be useful also in the spatial resolution of EnMAP (GSD = 30 m), this was not the case with Sentinel-2, owing to the lack of adequate spectral bands; the remaining indicators (MSI, CI, SR) were also OPEN ACCESS Remote Sens. 2015, 7 14228 successfully produced with Sentinel-2 data at superior spatial resolution (GSD = 10 m). The study confirms the importance of using earth observation systems for supplementing traditional ecological site classification maps, particularly during dry spells and heat waves when ecological gradients are increasingly reflected in the spectral response at the tree crown level. It also underlined the importance of using Sentinel-2 and EnMAP in synergy, as soon as both systems become available.

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Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies

Cited by 182 publications

References 37 publications

Spectral reflectance properties of healthy and stressed coniferous trees

Spectral reflectance properties of healthy and stressed coniferous trees

Using Optical Sensors to Identify Water Deprivation, Nitrogen Shortage, Weed Presence and Fungal Infection in Wheat

The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities

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