Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves

Datt, B.

doi:10.1080/014311699211778

Cited by 303 publications

(108 citation statements)

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“…The possibility of routine assessments of forest canopy health utilizing remote sensing technologies has increased in recent years through advances in our understanding of the spectral reflectance properties of vegetation, including eucalyptus-dominated forests (Coops et al 1997, 2003b, Datt 1998, 1999b, Stone et al 2001, Pietrzykowski et al 2006. During the growth of forest trees, a multitude of stressors (biotic or abiotic) can result in the development of stress symptoms (or strains) (Lichtenthaler 1996).…”

Section: Detection Of Stress In Eucalyptsmentioning

confidence: 99%

Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts

Barry

Stone²,

Mohammed

2008

International Journal of Remote Sensing

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Remote sensing for evaluation of canopy health in plantation eucalypts is a realistic option for forest managers in the near future if reliable and robust methods of spectral analysis can be developed. Pot-grown eucalypts of three species important to the Australian plantation industry were used for crown-scale spectral (400-1000 nm) evaluations of vegetation indices as indicators of common symptoms of stress. When defoliation treatments (in E. globulus) or exposure to cold and nutrient deprivation (in E. pilularis) resulted in large differences in leaf cover, the red edge position and slope indices, two normalized difference vegetation indices (NDVIs), modified chlorophyll absorption ratio index 2 (MCARI2) or modified triangular vegetation index 2 (MTVI2) were most strongly correlated to leaf cover. However the NDVIs were significantly affected by soil background in a study with E. globulus. The percentage of red leaves resulting from stress treatment was most strongly correlated with the anthocyanin reflectance index (ARI) and red-green index (RGI) in both E. grandis and E. pilularis, however the RGI was affected by background type in the E. globulus study while the ARI was not. Exposure to cold and nutrient deprivation led to marked changes in leaf cover for E. pilularis but not in E. grandis and a much more reduced level of chlorophyll in E. pilularis than is suspected in E. grandis. In E. globulus, defoliation from the upper crown was easier to detect with spectral data than from the lower crown. Results were generally comparable to studies of eucalypt crown condition from native forests.

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Section: Detection Of Stress In Eucalyptsmentioning

confidence: 99%

Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts

Barry

Stone²,

Mohammed

2008

International Journal of Remote Sensing

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“…RededgePeakArea Red-edge peak area derived from [41,57] SR N IRnarrowRededge1 Simple NIR and Red-edge 1 Ratio [39] SR N IRnarrowRededge2 Simple NIR and Red-edge 2 Ratio…”

Section: Spectral Resolution For Spatial Object Detectionmentioning

confidence: 99%

“…The foreground classes have been chosen within a set of key structuring landscape objects described in Section 2.1.1. The separability analysis, described in Section 2.1.2, has been performed for the spectral bands, for common spectral indices used to enhance the discrimination as well as for new indices based on the less common spectral bands available from Sentinel-2 (Table 2 [ [39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58]). For this purpose, pure spectral signatures of objects have been extracted from the images at well known locations (see Section 3).…”

Section: Spectral Resolution For Spatial Object Detectionmentioning

confidence: 99%

Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

et al. 2016

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Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas. With its 10 m to 20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However, many components of the ecological network are still smaller than the 10 m pixel, i.e., they are sub-pixel targets that stretch the sensor’s resolution to its limit. This paper proposes a framework to empirically estimate the minimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2. The same approach was also applied to Landsat-8 and SPOT-5 (Take 5), which can be considered as similar in terms of spectral definition and spatial resolution, respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case. Overall, results for Sentinel-2 highlight the critical importance of a good compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of 3 m and small water bodies are separable with a diameter larger than 11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications.

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“…Enhanced vegetation index (EVI) [77] Modified red edge Simple Ratio Index (mSR 705 ) [78] Canopy Single Ratio (SR canopy ) [79] Single Ratio (SR 705 ) [79] Simple Ratio Vogelmann index (SR v ) [80] Modified Normalized Difference Vegetation Index (mND 705 ) [79] Canopy Normalized Difference Vegetation Index (ND canopy ) [79] Normalized Difference Vegetation Index (ND 705 ) [79] Modified Single Ratio (MSR) [81] Ratio TCARI/OSAVI [82] Vegetation Index (canopy structural water)…”

Section: Vigor Greenness)mentioning

confidence: 99%

Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile

et al. 2015

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Abstract:The Andes foothills of central Chile are characterized by high levels of floristic diversity in a scenario, which offers little protection by public protected areas. Knowledge of the spatial distribution of this diversity must be gained in order to aid in conservation management. Heterogeneous environmental conditions involve an important number of niches closely related to species richness. Remote sensing information derived from satellite hyperspectral and airborne Light Detection and Ranging (LiDAR) data can be used as proxies to generate a spatial prediction of vascular plant richness. This study aimed to estimate the spatial distribution of plant species richness using remote sensing in the Andes foothills of the Maule Region, Chile. This region has a secondary deciduous forest dominated by Nothofagus obliqua mixed with sclerophyll species. Floristic measurements were performed using a nested plot design with 60 plots of 225 m 2 each. Multiple predictors were evaluated: 30 topographical and vegetation structure indexes from LiDAR data, and 32 spectral indexes and band transformations from the EO1-Hyperion sensor. A random forest algorithm was used to identify relevant variables in richness prediction, and these variables were used in turn to obtain a final multiple linear regression predictive model (Adjusted R 2 = 0.651; RSE = 3.69). An independent validation survey was performed with significant results (Adjusted R 2 = 0.571, RMSE = 5.05). Selected variables were statistically significant: OPEN ACCESSRemote Sens. 2015, 7 2693 catchment slope, altitude, standard deviation of slope, average slope, Multiresolution Ridge Top Flatness index (MrRTF) and Digital Crown Height Model (DCM). The information provided by LiDAR delivered the best predictors, whereas hyperspectral data were discarded due to their low predictive power.

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Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves

Cited by 303 publications

References 0 publications

Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts

Crown‐scale evaluation of spectral indices for defoliated and discoloured eucalypts

Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile

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