Application of Clustering to Landsat MSS Digital Data for Peatland Inventory

Palylyk, Claudia L.; Crown, P.H.

doi:10.1080/07038992.1984.10855070

Cited by 8 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unsupervised classifications are ideal for making inferences where little or no validation data are available. A number of studies have utilised unsupervised classifiers for wetland applications [253][254][255][256][257]. Gluck et al [258] is an example of a complementary principle component analysis (PCA), which reduces the number of image bands utilised in an ISODATA classifier, where the first principle component (PC1) highlights vegetation, PC2 indicates wetness differences, and PC3 distinguishes wetlands from uplands.…”

Section: Unsupervised Classificationmentioning

confidence: 99%

Remote Sensing of Wetlands in the Prairie Pothole Region of North America

Montgomery

Mahoney

Brisco³

et al. 2021

Remote Sensing

View full text Add to dashboard Cite

The Prairie Pothole Region (PPR) of North America is an extremely important habitat for a diverse range of wetland ecosystems that provide a wealth of socio-economic value. This paper describes the ecological characteristics and importance of PPR wetlands and the use of remote sensing for mapping and monitoring applications. While there are comprehensive reviews for wetland remote sensing in recent publications, there is no comprehensive review about the use of remote sensing in the PPR. First, the PPR is described, including the wetland classification systems that have been used, the water regimes that control the surface water and water levels, and the soil and vegetation characteristics of the region. The tools and techniques that have been used in the PPR for analyses of geospatial data for wetland applications are described. Field observations for ground truth data are critical for good validation and accuracy assessment of the many products that are produced. Wetland classification approaches are reviewed, including Decision Trees, Machine Learning, and object versus pixel-based approaches. A comprehensive description of the remote sensing systems and data that have been employed by various studies in the PPR is provided. A wide range of data can be used for various applications, including passive optical data like aerial photographs or satellite-based, Earth-observation data. Both airborne and spaceborne lidar studies are described. A detailed description of Synthetic Aperture RADAR (SAR) data and research are provided. The state of the art is the use of multi-source data to achieve higher accuracies and hybrid approaches. Digital Surface Models are also being incorporated in geospatial analyses to separate forest and shrub and emergent systems based on vegetation height. Remote sensing provides a cost-effective mechanism for mapping and monitoring PPR wetlands, especially with the logistical difficulties and cost of field-based methods. The wetland characteristics of the PPR dictate the need for high resolution in both time and space, which is increasingly possible with the numerous and increasing remote sensing systems available and the trend to open-source data and tools. The fusion of multi-source remote sensing data via state-of-the-art machine learning is recommended for wetland applications in the PPR. The use of such data promotes flexibility for sensor addition, subtraction, or substitution as a function of application needs and potential cost restrictions. This is important in the PPR because of the challenges related to the highly dynamic nature of this unique region.

show abstract

Section: Unsupervised Classificationmentioning

confidence: 99%

Remote Sensing of Wetlands in the Prairie Pothole Region of North America

Montgomery

Mahoney

Brisco³

et al. 2021

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Remote sensing has been used to monitor changes in a variety of landscapes, including peatlands [17][18][19][20]. Remote sensing is often used because it offers a consistent, large-scale, affordable approach to measuring landscape change.…”

Section: Remote Sensingmentioning

confidence: 99%

Investigating the Potential Use of RADARSAT-2 and UAS imagery for Monitoring the Restoration of Peatlands

et al. 2020

View full text Add to dashboard Cite

The restoration of peatlands is critical to help reduce the effects of climate change and further prevent the loss of habitat for many species of flora and fauna. The objective of this research was to evaluate RADARSAT-2 satellite imagery and high-resolution Unmanned Aerial Systems (UASs) to determine if they could be used as surrogates for monitoring the success of peatland restoration. Areas of peatland that were being actively harvested, had been restored from past years (1994–2003), and natural shrub bog in Lac St. Jean, Quebec were used as a test case. We compared the Freeman–Durden and Touzi decompositions by applying the Bhattacharyya Distance (BD) statistic to see if the spectral signatures of restored peatland could be separated from harvested peat and natural shrub bog. We flew Unmanned Aerial Surveys (UASs) over the study site to identify Sphagnum and Polytrichum strictum, two indicator species of early peatland restoration success. Results showed that the Touzi decomposition was better able to separate the spectral signatures of harvested, restored, and natural shrub bog (BD values closer to 9). Symmetric scattering type αs1, Helicity |τ1,2,3|, a steep incidence angle, and peak growing season appear to be important for separating the spectral signatures. We had moderate success in detecting Sphagnum and Polytrichum strictum visually by using texture and pattern but were unable to use colour due to differences in sun angle and clouds during the UAS flights. Results suggest that RADARSAT-2 data using the Touzi decomposition and UAS imagery show potential for monitoring peatland restoration success over time.

show abstract

“…In 1977, the DSS began offering a course in remote sensing and land classification. Over the next decade research included application of digital satellite and airborne data to soil and crop inventory (Reichert and Crown 1984;Izzaurralde 1989) and monitoring forest land resources (Hall et al 1984;Palylyk and Crown 1984). Later work continued on the monitoring of vegetation health (Hall et al 1995;Wowk 2000) and the effect of human activities on the landscape (El-Sawaf 1997).…”

Section: Remote Sensingmentioning

confidence: 99%

Soil science at the University of Alberta: a century of service to science and society

et al. 2020

View full text Add to dashboard Cite

This paper highlights major activities and achievements in soil science by professors at the University of Alberta (U of A), which provide incredible benefits to society, provincially, nationally, and globally. Evolution of the soils profession in Alberta commenced in 1919 with the hiring of FA Wyatt who developed the Department of Soil Science (DSS) and initiated a soil survey program in Alberta. JD Newton joined the department in 1922, teaching and supporting soil surveys that led to a fertilizer program greatly benefitting agriculture. With time, opportunities and problems were encountered with utilization of soils. U of A soil scientists conducted inventories, conducted innovative research, developed superior management techniques, and through evolving education and extension, continuously helped bring improvements to how we utilized and managed soil resources. The DSS 100 year evolution is chronicled under the themes of pedology (including soil survey), soil fertility, soil sustainability (conservation, land reclamation, contaminant remediation) with embedded specialized studies within these themes.

show abstract

Application of Clustering to Landsat MSS Digital Data for Peatland Inventory

Cited by 8 publications

References 4 publications

Remote Sensing of Wetlands in the Prairie Pothole Region of North America

Remote Sensing of Wetlands in the Prairie Pothole Region of North America

Investigating the Potential Use of RADARSAT-2 and UAS imagery for Monitoring the Restoration of Peatlands

Soil science at the University of Alberta: a century of service to science and society

Contact Info

Product

Resources

About