Thematic land-cover map assimilation and synthesis: the case of locating potential bioenergy feedstock in eastern Ontario, Canada

Calvert, Kirby; Luciani, Peter; Mabee, Warren

doi:10.1080/13658816.2013.833619

Cited by 3 publications

(11 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Diagram of the 16 domain tiles used in Equation (13), , whose centroids, , are the Because the region of interest has been spatially discretized into domain tiles with different ranges and parameters, the LC prediction in ℛ would produce unrealistic spatial LC transitions at the edges of the domain tiles without employing some spatial smoothing. Consequently, we use Equation (13) to calculate the value of the parameters in the matrices used in Equations (5) and (6), , and , , for the prediction at location as a weighted average of the elements corresponding to the 16 domain tiles closest to and shown in Figure 10, computed as follows:…”

Section: Resultsmentioning

confidence: 99%

“…Consequently, we use uation (13) to calculate the value of the parameters in the matrices used in Equations (5) and (6), , and , , for the prediction at location as a weighted average of the elements rresponding to the 16 domain tiles closest to and shown in Figure 10, computed as follows:…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, not all of them are detailed enough spatially (i.e., their spatial resolution is coarse-~1 km or coarser) to be applied in environmental studies at a regional scale [13,18]. Therefore, we use six LC products that include the region of interest and have a fine/moderate spatial resolution (i.e., 500 m or finer): National Land Cover Dataset 1992, hereafter referred to as NLCD92 [18,54]; National Land Cover Dataset, hereafter referred to as NLCD [7,14,55]; Collection 5 Moderate Resolution Imaging Spectroradiometer Global Land Cover Type, hereafter referred to as MODIS [6,56]; Enhanced Historical Land-Use and Land-Cover Data Sets of the USGS, hereafter referred to as Historical-USGS [57,58]; USGS Conterminous United States Projected Land-Use/Land-Cover Mosaics, referred to as BC-USGS (BC from BackCasting) [59][60][61][62][63]; and LANDFIRE Existing Vegetation Cover, hereafter referred to as LF [64].…”

Section: Land Cover Datasetsmentioning

confidence: 99%

“…The development of remote sensing technologies, extraction and processing methodologies, and steadily improving computational capacity have resulted in increased availability of LC products [1,2,[13][14][15]. LC products are thematic maps depicting different LC classes, developed from an algorithmic classification of satellite imagery, which is often supported by the inclusion of ancillary a flexible LC classification and to address large scale nonstationarities.…”

Section: Introductionmentioning

confidence: 99%

“…The weights in Equation (13), exp − Figure 9. Comparison of the optimal prediction of LC in domain tile 3 from Rodríguez-Jeangros et al [36] at a spatial resolution of 50 m in the year 2001 (see Figure 1) with two methodology cases: (a) LC prediction based on Equations (1) and (2), but ignoring the proposed modifications of including in Equations (1) and (2); using in Equation (5); setting , and , as inversely proportional to the temporal ranges in Equation (8); and using as a proxy in the estimation of ( , ) for the cases when ( , ) = | ( , ) = = 0 for all ∈ (black cells); and (b) LC prediction based on the modified version of SCaMF, described in Section 2.3.…”

mentioning

confidence: 99%

See 4 more Smart Citations

SCaMF–RM: A Fused High-Resolution Land Cover Product of the Rocky Mountains

et al. 2017

View full text Add to dashboard Cite

Land cover (LC) products, derived primarily from satellite spectral imagery, are essential inputs for environmental studies because LC is a critical driver of processes involved in hydrology, ecology, and climatology, among others. However, existing LC products each have different temporal and spatial resolutions and different LC classes that rarely provide the detail required by these studies. Using multiple existing LC products, we implement our Spatiotemporal Categorical Map Fusion (SCaMF) methodology over a large region of the Rocky Mountains (RM), encompassing sections of six states, to create a new LC product, SCaMF-RM. To do this, we must adapt SCaMF to address the prediction of LC in large space-time regions that present nonstationarities, and we add more flexibility in the LC classifications of the predicted product. SCaMF-RM is produced at two high spatial resolutions, 30 and 50 m, and a yearly frequency for the 30-year period 1983-2012. When multiple products are available in time, we illustrate how SCaMF-RM captures relevant information from the different LC products and improves upon flaws observed in other products. Future work needed includes an exhaustive validation not only of SCaMF-RM but also of all input LC products.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Land Cover Datasetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

SCaMF–RM: A Fused High-Resolution Land Cover Product of the Rocky Mountains

et al. 2017

View full text Add to dashboard Cite

show abstract

Fusing multiple existing space‐time land cover products

et al. 2016

View full text Add to dashboard Cite

Land cover (LC) is a critical variable driving many environmental processes, so its assessment, monitoring, and characterization are essential. However, existing LC products, derived primarily from satellite spectral imagery, each have different temporal and spatial resolutions and different LC classes. Most effort is focused on either fusing a pair of LC products over a small space‐time region or on interpolating missing values in an individual LC product. Here, we review the complexities of LC identification and propose a method for fusing multiple existing LC products to produce a single LC record for a large spatial‐temporal grid, referred to as spatiotemporal categorical map fusion. We first reconcile the LC classes of different LC products and then present a probabilistic weighted nearest neighbor estimator of LC class. This estimator depends on three unknown parameters that are estimated using numerical optimization to maximize an agreement criterion that we define. We illustrate the method using six LC products over the Rocky Mountains and show the improvement gained by supplying the optimization with data‐driven information describing the spatial‐temporal behavior of each LC class. Given the massive size of the LC products, we show how the optimal parameters for a given year are often optimal for other years, leading to shorter computing times.

show abstract

Spatial Analysis of Biomass Resources within a Socio-Ecologically Heterogeneous Region: Identifying Opportunities for a Mixed Feedstock Stream

Calvert

Mabee

2014

IJGI

Self Cite

View full text Add to dashboard Cite

Local bioenergy will play a crucial role in national and regional sustainable energy strategies. Effective siting and feedstock procurement strategies are critical to the development and implementation of bioenergy systems. This paper aims to improve spatial decision-support in this domain by shifting focus from homogenous (forestry or agricultural) regions toward heterogeneous regions-i.e., areas with a presence of both forestry and agricultural activities; in this case, eastern Ontario, Canada. Multiple land-cover and resource map series are integrated in order to produce a spatially distributed GIS-based model of resource availability. These data are soft-linked with spreadsheet-based linear models in order to estimate and compare the quantity and supply-cost of the full range of non-food bioenergy feedstock available to a prospective developer, and to assess the merits of a mixed feedstock stream relative to a homogenous feedstock stream. The method is applied to estimate bioenergy production potentials and biomass supply-cost curves for a number of cities in the study region. Comparisons of biomass catchment areas; supply-cost curves; resource density maps; and resource flow charts demonstrate considerable strategic and operational advantages to locating a facility within the region's -transition zone‖ between forestry and agricultural activities. Existing and emerging bioenergy technologies that are feedstock agnostic and therefore capable of accepting a mixed-feedstock stream are OPEN ACCESS ISPRS Int. J. Geo-Inf. 2014, 3 210 reviewed with emphasis on -intermediates‖ such as wood pellets; biogas; and bio-oils, as well as bio-industrial clusters.

show abstract

Thematic land-cover map assimilation and synthesis: the case of locating potential bioenergy feedstock in eastern Ontario, Canada

Cited by 3 publications

References 35 publications

SCaMF–RM: A Fused High-Resolution Land Cover Product of the Rocky Mountains

SCaMF–RM: A Fused High-Resolution Land Cover Product of the Rocky Mountains

Fusing multiple existing space‐time land cover products

Spatial Analysis of Biomass Resources within a Socio-Ecologically Heterogeneous Region: Identifying Opportunities for a Mixed Feedstock Stream

Contact Info

Product

Resources

About