North American forest disturbance mapped from a decadal Landsat record

Masek, Jeffrey G.; Huang, Chengquan; Wolfe, Robert E.; Cohen, Warren B.; Hall, Forrest G.; Kutler, J.; Nelson, Peter O.

doi:10.1016/j.rse.2008.02.010

Cited by 398 publications

(307 citation statements)

References 35 publications

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“…Remote sensing approaches offer a feasible and effective tool for the detection of forest disturbances in regional and even global scales (Healey et al 2005;Masek et al 2008;Rykhus & Lu 2011;Stroppiana et al 2012). In previous studies, a variety of spectral indices (such as DI by Healey et al 2005, NDVI and EVI by Stroppiana et al 2012 and NDVI, DVI, RVI, SAVI, etc.…”

Section: Discussionmentioning

confidence: 99%

“…Forest disturbance and recovery has been proposed as a primary mechanism for transferring carbon between the land surface and atmosphere, and thus plays an important role in both regional and global carbon budgets, as well as in long-term forest monitoring processes (Healey et al 2005;Masek et al 2008;S€ onmez et al 2011). Forest fire is one of the dominant disturbances, especially in boreal forests.…”

Section: Introductionmentioning

confidence: 99%

“…The application of optical remote sensing technology is the most common and traditional approach to extracting forest characteristics and monitoring forest change. Optical imageries, particularly the extensive Landsat records, are well suited to the detection of forest disturbances (Masek et al 2008;Kennedy et al 2012;Townshend et al 2012).…”

Section: Introductionmentioning

confidence: 99%

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Mapping a burned forest area from Landsat TM data by multiple methods

Chen

Moriya

Sakai

et al. 2014

Geomatics, Natural Hazards and Risk

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Forest fire is one of the dominant disturbances in boreal forests. It is the primary process responsible for organizing the physical and biological attributes of the boreal biome, shaping landscape diversity and influencing biogeochemical cycles. The Greater Hinggan Mountain of China is rich in forest resources while suffers from a high incidence of forest fires simultaneously. In this study, focusing on the most serious forest fire in the history of P. R. China which occurred in this region, we made use of two Landsat-5 TM (Thematic Mapper) images, and proposed to map the overall burned area and burned forest area by multiple methods. During the mapping, the fire perimeter, as well as rivers, roads and urban areas were first extracted and masked visually, and then four indices of Normalized Difference Vegetation Index, Enhanced Vegetation Index, Vegetation Fractional Cover and Disturbance Index were calculated. For each index, the optimal threshold for separating burned from unburned forest area was determined using their histograms. For comparison, threshold segmentation using single-band reflectance was performed, in addition to a Maximum Likelihood Classifier (MLC) based supervised classification of all features and forest area alone; their accuracies were also evaluated and analysed. Among all the methods compared here, mapping by EVI threshold segmentation proved to be optimal by the comparisons of overall accuracy (99.78%) and the kappa coefficient (0.9946). Finally, the calculated burned area and burned forest area were compared with the values from official statistics. Compared with the classical methods used to report official statistics on burned areas, the remote sensing-based mapping is more objective and efficient, less labour-and time-consuming, and more repeatable.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping a burned forest area from Landsat TM data by multiple methods

Chen

Moriya

Sakai

et al. 2014

Geomatics, Natural Hazards and Risk

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“…One of the best sources for land use studies is the Landsat series of satellites. Landsat data are useful for land surface mapping, change detection and monitoring (Cohen and Goward 2004;Alesheikh et al 2007;Hansen et al 2008;Masek et al 2008;Cetin 2009). Landsat data are particularly applicable for land use classification on a regional scale because of their lower cost, longer history and higher frequency of archives than other remote sensing data sources (Rozenstein and Karnieli 2010).…”

Section: Introductionmentioning

confidence: 99%

A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran

Mohammady

Moradi

Zeinivand

et al. 2014

Int. J. Environ. Sci. Technol.

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Land use classification is often the first step in land use studies and thus forms the basis for many earth science studies. In this paper, we focus on low-cost techniques for combining Landsat images with geographic information system approaches to create a land use map. In the Golestan region of Iran, we show that traditional supervised and unsupervised methods do not result in sufficiently accurate land use maps. Therefore, we evaluated a synthetic approach combining supervised and unsupervised methods with decision rules based on easily accessible ancillary data. For accuracy assessment, confusion matrices and kappa coefficients were calculated for the maps created with the supervised, unsupervised and synthetic approaches. Overall accuracy of the synthetic approach was 98.2 %, which is over the 85 % level that is considered satisfactory for planning and management purposes. This shows that integration of remote sensing data, ancillary data and decision rules provides better classification accuracy than traditional methods, without significant additional use of resources.

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“…In contrast, a more traditional scene-based sampling approach (e.g. Masek et al 2008) would only use about 60 observations over 27 years, limiting the ability to detect change.…”

Section: Discussionmentioning

confidence: 99%

Rapid, high-resolution detection of environmental change over continental scales from satellite data – the Earth Observation Data Cube

Lewis

Lymburner

Purss

et al. 2015

International Journal of Digital Earth

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The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations -the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.ARTICLE HISTORY

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North American forest disturbance mapped from a decadal Landsat record

Cited by 398 publications

References 35 publications

Mapping a burned forest area from Landsat TM data by multiple methods

Mapping a burned forest area from Landsat TM data by multiple methods

A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran

Rapid, high-resolution detection of environmental change over continental scales from satellite data – the Earth Observation Data Cube

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