Spectral aspects for monitoring forest health in extreme season using multispectral imagery

Gupta, Saurabh Kumar; Pandey, Arvind Chandra

doi:10.1016/j.ejrs.2021.07.001

Cited by 12 publications

(8 citation statements)

References 40 publications

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“…Firstly, data acquisition was conducted. After data acquisition, we initially applied the ENVI forest health tool on the Sentinel-2 image to find the hot-score area, which represented the study area with a low level of forest health [21]. Then we computed indices related to leaf pigment and canopy architecture in the study area.…”

Section: Methodsmentioning

confidence: 99%

“…For instance, Jump et al [16] discovered that tree dieback can lead to a decrease in water content and Leaf Area Index (LAI). Dallahi et al [17] assessed forest dieback using the Normalized Difference Vegetation Index (NDVI); Eitel et al [18] found that the Normalized Difference Red-edge Index (NDRE) can be used to monitor early red-edge increase; Gitelson et al [19] found a strong correlation between the Green Normalized Difference Vegetation Index (GNDVI) and chlorophyll a, and Wojtowicz et al [20] used GNDVI to identify the vegetation infected with leaf rust; Gupta and Pandey [21] analyzed and mapped forest health using Anthocyanin Reflectance Index 1 (ARI1). Typically, researchers fit vegetation indices to field data to reflect forest health conditions.…”

Section: Introductionmentioning

confidence: 99%

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Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve

Gao,

Chen,

Wang

et al. 2023

Remote Sensing

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Jiuzhaigou Valley is recognized as both a world natural heritage site and a biosphere reserve. Conducting research on vegetation health within its scope can provide a demonstration role for sustainable development research. In this study, we proposed a technology integration approach that combined remote sensing intelligent identification and quantitative retrieval, and achieved vegetation health monitoring and susceptibility mapping of unhealthy trees. Leveraging WorldView-2 high-resolution satellite images, unhealthy trees were elaborately identified through the object-oriented classification method employing spectral and texture features, with F1 Score exceeding 75%. By applying fuzzy operations on indices related to leaf pigment and canopy architecture, we ultimately generated susceptibility maps of unhealthy trees on Sentinel-2 satellite images, with Area Under the Curve (AUC) exceeding 0.85. Our findings underscore that the vegetation health in Jiuzhaigou Valley is predominantly influenced by human activities and geological hazards. The forests of Jiuzhaigou Valley exhibit a certain degree of resilience to geological disasters, while human activities have been continuously exerting adverse effects on forest health in recent years, necessitating heightened attention. The methodology proposed in this study for mapping unhealthy trees susceptibility presents a cost-effective solution that can be readily applied for vegetation health monitoring and early warning in analogous biosphere reserves.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve

Gao,

Chen,

Wang

et al. 2023

Remote Sensing

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“…Note that precise maps of Hazaribagh Plateau are not publicly available. The outline map of Hazaribagh Wildlife Sanctuary was drawn using the maps already published (Gupta & Pandey, 2021) (fig. 1B).…”

Section: Site Mapping and Geo-taggingmentioning

confidence: 99%

On the behavioural biology of a morpho-variant of Myrmaplata plataleoides (O. Pickard-Cambridge, 1869) (Araneae: Salticidae) with taxonomic notes

2022

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We hereby report an isolated population of a rare morpho-variant of the ant-mimicking jumping spider Myrmaplata plataleoides (O. Pickard-Cambridge, 1869) from Hazaribagh Wildlife Sanctuary, Hazaribagh, Jharkhand, India, which is also the first record of this species from the state of Jharkhand, India. Descriptions of both male and female spiders, the female’s exuviae, its eggs and habitat are presented. We have studied its moulting, feeding and sexual behaviour in detail, and have recorded various behavioural aspects that were never documented before, such as debris-rolling behaviour, photokinetic response, starvation response and oxygen deprivation response. We here report the occurrence of this spider near the colonies of the ground-nesting ant Camponotus compressus (Fabricius, 1787). This spider is known to mimic the Asian weaver ant Oecophylla smaragdina (Fabricius, 1775), which are greenish orange to red in colour. Specimens collected by us are dark brown to black in coloration whereas the commonly reported specimens are often greenish orange to red. We propose that the darker coloration would have been naturally selected in this isolated population of M. plataleoides as an adaptation to coexist with C. compressus, which is also black in coloration and abundant around the spiders. Study of the moulting behaviour of the morpho-variant further reveals the display of a novel mechanism of ant mimicry among these spiders which we have named as temporal myrmecomorphy. Temporal myrmecomorphy has been proposed to be a protective mechanism used by a harmless mimic against the attacks of the aggressive models so that it can co-exist with the models. Present study establishes the usefulness of a morpho-variant as an important model in understanding the evolution and behaviour of a species holistically.

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“…Traditional vegetation indices evaluate vegetation growth and health by using combinations of near-infrared and visible light bands, such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Soil-Adjusted Vegetation Index (SAVI). Gupta et al [7] constructed a forest health index combining NDVI with Anthocyanin Reflectance Index 1 (ARI1) and Structure Insensitive Pigment Index (SIPI), based on Sentinel-2A imagery to assess forest health conditions. Alhammadi and Glenn [8] used the SAVI index to assess the health condition of date palm trees on the eastern coast of the United Arab Emirates.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Effectiveness of the Red-Edge Bands of GF-6 Imagery in Forest Health Discrimination

Chen,

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The red-edge band is closely related to biochemical parameters that characterize the growth condition of green plants and is an important factor in monitoring vegetation health. Therefore, red-edge indices based on the red-edge band have been developed to measure vegetation health. However, due to the limited availability of satellites with a red-edge band, most existing red-edge indices were not developed based on satellite data. Fortunately, the launch of the GaoFen-6 (GF-6) satellite provides favorable conditions for monitoring vegetation health using satellite imagery, as it has two red-edge bands with spatial resolution of 16 m. To investigate the effectiveness of the red-edge bands on the GF-6 satellite in monitoring forest health, this study selected six red-edge indices and conducted tests in Zhangjiajie region in Hunan Province, China, and Hetian Basin in Fujian Province, China. The selected indices are the Normalized Difference Red-Edge Index 1 (NDRE1), the Modified Chlorophyll Absorption Ratio Index 2 (MCARI2), the Red-Edge Chlorophyll (CIred-edge), the Inverted Red-Edge Chlorophyll Index (IRECI), the Red-Edge Position (REP), and the Missouri emergency resource information system Terrestrial Chlorophyll Index (MTCI). The results showed that when applied to NDRE1 and CIred-edge, the red-edge bands of GF-6 can effectively distinguish forest health conditions, with discrimination accuracy of 92.3% and 92.5%, respectively. However, the performance of the GF-6 red-edge bands with the other four indices yielded accuracy generally lower than 70%. Overall, the two red-edge bands added to the GF-6 satellite contribute to discerning forest health conditions, with NDRE1 and CIred-edge being the preferred rededge indices.Index Terms-remote sensing, GF-6, red-edge band, red-edge index, forest health.

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Spectral aspects for monitoring forest health in extreme season using multispectral imagery

Cited by 12 publications

References 40 publications

Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve

Susceptibility Mapping of Unhealthy Trees in Jiuzhaigou Valley Biosphere Reserve

On the behavioural biology of a morpho-variant of Myrmaplata plataleoides (O. Pickard-Cambridge, 1869) (Araneae: Salticidae) with taxonomic notes

Analysis of the Effectiveness of the Red-Edge Bands of GF-6 Imagery in Forest Health Discrimination

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