Forest applications with hyperspectral imaging

Goodenough, D.G.; Chen, Hao; Gordon, Piper; Niemann, K. Olaf; Quinn, Geoffrey S.

doi:10.1109/igarss.2012.6351973

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…Optical remote sensing with high spectral resolution, known as hyperspectral remote sensing or imaging spectroscopy, provides the most spectrally rich data on material properties. Hyperspectral sensors are capable of recording great number (up to hundreds) of narrow bands, enabling the derivation of spectral curves, which in turn, can be explored with numerous techniques and potentially provide forest information products, including maps of forest species, canopy chemistry, biomass, and carbon (Goodenough et al 2012). Expectations from hyperspectral data include improved species identification, a better mapping of biochemical status of trees and the possibility of estimating biomass directly from the data (Ustin and Trabucco 2000;Ustin et al 2004;Koch 2010).…”

Section: Optical Remote Sensingmentioning

confidence: 99%

Vegetation biomass estimation with remote sensing: focus on forest and other wooded land over the Mediterranean ecosystem

Galidaki

Zianis

Gitas

et al. 2016

International Journal of Remote Sensing

102

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Carbon sequestration service of Mediterranean forest and other wooded land is threatened by their fragile, complex, and highly evolving nature, due to both human disturbances and climate change. Remote-sensing methods for forest biomass estimation have gained increased attention, and substantial research has been conducted worldwide over the past four decades. Yet, the literature body focused on Mediterranean forests is rather limited as a result of their small extent compared to other biomes. We discuss the remote-sensing studies over the Mediterranean forest and other wooded land, discriminating research based on the primary data source used, such as optical imagery, datasets from active sensors, and combination of multisource data. The review indicates that there is a significant research gap in terms of the studies, as well as a need for a reduction of the errors and uncertainty of estimates, which are associated with both the sensors' characteristics and the Mediterranean forest and other wooded land structure. Biomass estimates based on optical data were generally less accurate (R 2 close to 0.70, where R 2 is the coefficient of determination), however, when data from active sensors were involved, accuracy of estimations was considerably greater (usually R 2 greater than 0.80). With respect to scale, most of the local scale studies established relationships with R 2 over 0.70 and as high as 0.98, while the few regional scale studies exhibited R 2 close to 0.80. Further, in-depth analysis can provide more efficient data fusion, classification methods, and procedures for operational regional and national assessment of forest biomass over such Mediterranean areas.

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Section: Optical Remote Sensingmentioning

confidence: 99%

Vegetation biomass estimation with remote sensing: focus on forest and other wooded land over the Mediterranean ecosystem

Galidaki

Zianis

Gitas

et al. 2016

International Journal of Remote Sensing

102

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“…With its increasing availability, it is expected to play an increasing role in supporting sustainable agricultural practices and maximizing productivity in the future. Similar is being used in forestry applications (Goodenough et al, 2012, Tusa et al, 2019, Saarinen et al, 2018, Krtalić et al, 2021.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral Imaging in Preservation of Croatia’s Historic Trees: A Case Study of Dedek Oak in Maksimir Park

Babić,

Miljković,

Odak

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This study focuses on the application of hyperspectral imaging techniques for the genetic preservation of historic trees, specifically investigating the 600-year-old "Dedek" Oak in Maksimir Park, Croatia. The research aims to contribute to the conservation of Croatia's natural heritage and underscore the potential of hyperspectral imaging in tree preservation. The Croatian Forest Research Institute has been actively involved in preserving the pedunculate oak trees, recognizing their cultural and ecological significance. Efforts have been made to cultivate seedlings from the original genetic material, thereby preventing the loss of valuable genes and ensuring their long-term preservation. Spectral signatures of "Dedek" Oak and its clones were captured using high-performance hyperspectral push broom cameras, including the HySpex VNIR-1800 and SWIR-384. Spectral camera scanning was conducted in the field and laboratory. The comparative analysis of the spectral samples revealed unique characteristics and demonstrated the effectiveness of hyperspectral imaging in studying historic trees for preservation purposes. The spectral signatures of vegetation display dynamic characteristics in terms of spectral resolution. Collecting and documenting these signatures is considerably more challenging, and their integration into spectral libraries should be approached with careful consideration. There are several spectral libraries that are organized by chapters and consist of samples that have a sufficient number of analysis and documentation to determine the quality of the spectrum. In this study, spectral signatures of pedunculate oak (Quercus robur L.) called Dedek and its clones were singled out. The objective of this research was to establish a foundation for a spectral library that would facilitate future research on the application of hyperspectral scanners for detecting protected tree species and their clones, all for the purpose of preservation of the genetic diversity of protected trees in Croatia. The findings of this research contribute to the conservation of Croatia's natural heritage by providing valuable insights into the genetic preservation of the 600-year-old "Dedek" Oak. Also, determining the spectral signatures of clones can help us with the identification of specific tree species (especially during aerial imaging, which is planned to be conducted in the future). In conclusion, this research showcases the importance of preserving historic trees and the potential of hyperspectral imaging as a valuable tool for genetic preservation efforts. The study's outcomes contribute to the long-term conservation of Croatia's natural heritage and provide a foundation for future research in the field of tree preservation and spectral library inception.

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“…Hyperspectral sensors that are able to differentiate forest species and foliar chemistry may be used to generate a wide variety of forest information products, including maps of forest species, canopy chemistry, biomass, and carbon. Methods and concerns related to forest monitoring and mapping are examined, with particular focus on biomass and carbon mapping, in light of past and contemporary work in the area of hyperspectral imaging 24 . Using Hyperion data, a research was carried out at the Bhitarkanika Forest Reserve in Odisha, India.…”

Section: Introductionmentioning

confidence: 99%

“…Methods and concerns related to forest monitoring and mapping are examined, with particular focus on biomass and carbon mapping, in light of past and contemporary work in the area of hyperspectral imaging. 24 Using Hyperion data, a research was carried out at the Bhitarkanika Forest Reserve in Odisha, India. At a significance threshold of p0.05, it displayed an excellent R 2 of 0.84 with enhanced vegetation index (EVI) and 0.81 with normalized difference vegetation index (NDVI)-derived biomass.…”

Section: Introductionmentioning

confidence: 99%

AVIRIS-NG hyperspectral data for biomass modeling: from ground plot selection to forest species recognition

Verma

Sharma

Lele

2023

J. Appl. Rem. Sens.

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Forest biomass is an important biophysical parameter, which delivers vital and valuable information about forest health, growth, productivity, carbon cycle monitoring, forest degradation, and its ecosystem. It is an important inconstant for ecological modeling, carbon stock assessment, and climate change. Forest biomass estimation has been progressively investigated, in which the accuracy of results is good enough to estimate accuracy of biomass; therefore, more accurate estimation of biomass is important for refining the precision and its applicability of these techniques. Hyperspectral remote sensing provides more accurate information about vegetation, so with the combination of advanced hyperspectral datasets it may be a better technique to enhance the results and accuracy of spatial biomass. Airborne hyperspectral data of airborne visible infrared imaging spectrometer-next generation data were demonstrated to estimate above ground biomass (AGB) of a tropical dry deciduous forest. Atmospherically resistant vegetation index, simple ratio index (SRI), normalized difference vegetation index, and enhanced vegetation index (EVI) were used to estimate AGB, in which EVI performs better than other vegetation indices with 0.55 R square value. Plant senescence reflectance index was used to estimate the dry and senescence condition of the forest and its correlations were performed with ground biomass and other vegetation indices.

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Forest applications with hyperspectral imaging

Cited by 7 publications

References 22 publications

Vegetation biomass estimation with remote sensing: focus on forest and other wooded land over the Mediterranean ecosystem

Vegetation biomass estimation with remote sensing: focus on forest and other wooded land over the Mediterranean ecosystem

Hyperspectral Imaging in Preservation of Croatia’s Historic Trees: A Case Study of Dedek Oak in Maksimir Park

AVIRIS-NG hyperspectral data for biomass modeling: from ground plot selection to forest species recognition

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