CHARACTERIZING LANDSCAPE SPATIAL HETEROGENEITY USING SEMIVARIOGRAM PARAMETERS DERIVED FROM NDVI IMAGES

Multiscale Landscape Representation Derived from Remote Sensing Images Using Spatial Subpixel Models and Combinatorial Maps

Landscapes can be modelled as sets of homogeneous objects (landscape elements) forming areas of characteristic patterns (landscape units). The common way to represent landscapes is by vector GIS data structures which do not provide a mechanism for storing the spatial relationships between the objects in explicit form. Also, they do not account for a multi-scale representation. Graphs can be use...

Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity

Traffic conditions are usually characterized from the perspective of travel time or the average vehicle speed in the field of transportation, reflecting the congestion degree of a road network. This article provides a method from a new perspective to characterize traffic conditions; the perspective is based on the heterogeneity of vehicle speeds. A novel measurement, the ratio of areas (RA) in ...

Quantifying spatial heterogeneity at the landscape scale using variogram models

The monitoring of earth surface dynamic processes at a global scale requires high temporal frequency remote sensing observations which are provided up to now by moderate spatial resolution sensors. However, the spatial heterogeneity within the moderate spatial resolution pixel biases non-linear estimation processes of land surface variables from remote sensing data. To limit its influence on th...

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale (∼ 50 m resolution) a...

Model Averaging for Semivariogram Model Parameters