Forest Fragmentation of the Conterminous United States: Assessing Forest Intactness through Road Density and Spatial Characteristics

Heilman, Gerald E.; Strittholt, James R.; Slosser, Nicholas C; DellaSala, Dominick A.

doi:10.1641/0006-3568(2002)052[0411:ffotcu]2.0.co;2

Cited by 168 publications

(90 citation statements)

References 32 publications

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“…Especially in Greece, roads mostly follow the tracks of ancient pathways, and several roads are known to have been in operation since ancient times (Faloso 2003). The range of road density values observed in protected areas in Greece is comparable to that of the northern Great Lakes Region in North America (Saunders et al 2002) and the native forest ecosystems of the US, which also include protected areas (Heilman et al 2002). On the other hand, the high road density values (>1.5 km/km 2 ) found in certain Greek Natura 2000 sites are comparable to those of densely populated countries such as the US (Forman and Alexander 1998), which is surprising considering their high conservation value.…”

Section: Discussionmentioning

confidence: 68%

Road effects on habitat richness of the Greek Natura 2000 network

Votsi¹,

Mazaris²,

Kallimanis³

et al. 2012

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The road network has both positive and negative ecological effects, and understanding these helps identify environmentally preferable solutions for transportation policy and planning. We investigated the relationship between road density and habitat type richness of Greek protected areas. We used digital vector maps of 214 sites included in the Greek Natura 2000 network. We calculated road density for the terrestrial part of each site and correlated it with habitat type richness. Average road density of protected areas (0.377 km/ km 2 ) was significantly lower than the national road density of Greece (0.446 km/km 2 ). We identified 32 sites that were not intersected by roads. These roadless sites were located at mountain tops, at islets, or in remote coastal zones. Overall we found no significant correlation between road density and habitat type richness. We suggest that the effect of road networks on habitat type richness is less apparent at landscapes with long history of human presence, because the landscape (and its habitat diversity) has coevolved with human activities over the past millennia. Our analysis provides a step towards quantifying the effect of road density on the diversity of habitats and consequently on species of conservation interest in international networks of protected areas such as the European Natura 2000 network.

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Section: Discussionmentioning

confidence: 68%

Road effects on habitat richness of the Greek Natura 2000 network

Votsi¹,

Mazaris²,

Kallimanis³

et al. 2012

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“…Net change is another potential objective of interest (Stehman & Wickham, 2006). Landscape pattern metrics that quantify forest fragmentation, patch size and shape metrics, and the adjacency of different land-cover classes are increasingly used (Heilman et al, 2002) and represent another potential objective to be addressed by accuracy assessment. Assessing the accuracies of proportion of area, net change and landscape pattern may be better addressed by spatially contiguous sample data, thus motivating the use of one-stage cluster sampling for which a cluster of contiguous pixels is the sampling unit (Stehman, 2009b).…”

Section: Sampling Designmentioning

confidence: 99%

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

McRoberts

Cohen

Næsset

et al. 2010

Scandinavian Journal of Forest Research

112

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Tremendous advances in the construction and assessment of forest attribute maps and related spatial products have been realized in recent years, partly as a result of the use of remotely sensed data as an information source. This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses five topic areas: statistical classification and prediction techniques used to construct maps and related spatial products, accuracy assessment methods, map-based statistical inference, and two emerging topics, change detection and use of lidar data. Multiple general conclusions were drawn from the review: (1) remotely sensed data greatly contribute to the construction of forest attribute maps and related spatial products and to the reduction of inventory costs; (2) parametric prediction techniques, accuracy assessment methods and probability-based (design-based) inferential methods are generally familiar and mature, although inference is surprisingly seldom addressed; (3) non-parametric prediction techniques and modelbased inferential methods lack maturity and merit additional research; (4) change detection methods, with their great potential for adding a spatial component to change estimates, will mature rapidly; and (5) lidar applications, although currently immature, add an entirely new dimension to remote sensing research and will also mature rapidly. Crucial forest sustainability and climate change applications will continue to push all aspects of remote sensing to the forefront of forest research and operations.

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“…VeRDET will often begin a disturbance segment a year earlier or end it a year later than the human interpreter, most likely due to noise in the time series, missing dates, or from discretization inherent in creating yearly composites. Additionally, pixels on the edges of patches, of which there are very many in fragmented eastern forests [51] are often included into a patch with different dynamics than what was interpreted for the pixel. In extreme cases an edge pixel is alternatingly included in neighboring patches, making its time series unrepresentative of the actual dynamics for the location.…”

Section: Discussionmentioning

confidence: 99%

Patch-Based Forest Change Detection from Landsat Time Series

Hughes

Kaylor

Hayes

2017

Forests

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Abstract:In the species-rich and structurally complex forests of the Eastern United States, disturbance events are often partial and therefore difficult to detect using remote sensing methods. Here we present a set of new algorithms, collectively called Vegetation Regeneration and Disturbance Estimates through Time (VeRDET), which employ a novel patch-based approach to detect periods of vegetation disturbance, stability, and growth from the historical Landsat image records. VeRDET generates a yearly clear-sky composite from satellite imagery, calculates a spectral vegetation index for each pixel in that composite, spatially segments the vegetation index image into patches, temporally divides the time series into differently sloped segments, and then labels those segments as disturbed, stable, or regenerating. Segmentation at both the spatial and temporal steps are performed using total variation regularization, an algorithm originally designed for signal denoising. This study explores VeRDET's effectiveness in detecting forest change using four vegetation indices and two parameters controlling the spatial and temporal scales of segmentation within a calibration region. We then evaluate algorithm effectiveness within a 386,000 km 2 area in the Eastern United States where VeRDET has overall error of 23% and omission error across disturbances ranging from 22% to 78% depending on agent.

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Forest Fragmentation of the Conterminous United States: Assessing Forest Intactness through Road Density and Spatial Characteristics

Cited by 168 publications

References 32 publications

Road effects on habitat richness of the Greek Natura 2000 network

Road effects on habitat richness of the Greek Natura 2000 network

Using remotely sensed data to construct and assess forest attribute maps and related spatial products

Patch-Based Forest Change Detection from Landsat Time Series

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