Effects of spatial aggregation approaches on classified satellite imagery

Spatial aggregations of raster data based on the majority rule have been typically used in landscape ecological studies. It is generally acknowledged that (1) dominant classes increase in abundance while minor classes decrease in abundance or even disappear through aggregation processes; and (2) spatial patterns also change with aggregations. In this paper, we examined an alternative, random rule-based aggregation and its effects on cover type abundance and landscape patterns, in comparison with the majority rule-based aggregation. We aggregated a classified TM imagery (about 1.5 million ha) from 30m (4231 × 3717 pixels) incrementally to 990m resolution (132 pixels × 116 pixels). Cover type proportion, mean patch size ratio, aggregation index (AI), and fractal dimension (FD) were used to assess the effects of aggregation. To compare landscapes under different resolutions, we assumed that the landscapes were least distorted if (1) the cover type proportions and mean patch size ratios among classes were maintained, and (2) all cover types responded in the same way for a given index as aggregation levels increased. For example, distortion is introduced by aggregation if some cover types increase their AI values with increasing aggregation levels while other cover types decrease. Our study indicated that the two spatial aggregation techniques led to different results in cover type proportions and they altered spatial pattern in opposite ways. The majority rule-based aggregations caused distortions of cover type proportions and spatial patterns. Generally, the majority rule-based aggregation filtered out minor classes and produced clumped landscapes. Such landscape representations are relatively easy for interpreting and, therefore, are suitable for land managers to conceptualize spatial patterns of a study region. By contrast, the random rule-based aggregations maintained cover type proportions accurately, but tended to make spatial patterns change toward disaggregation. Overall, the measurements of landscape indices used in this study indicated that

[1]  Kurt H. Riitters,et al.  Assessing habitat suitability at multiple scales: A landscape-level approach , 1997 .

[2]  Nathan H. Schumaker,et al.  Using Landscape Indices to Predict Habitat Connectivity , 1996 .

[3]  Hong S. He,et al.  INTEGRATION OF GIS DATA AND CLASSIFIED SATELLITE IMAGERY FOR REGIONAL FOREST ASSESSMENT , 1998 .

[4]  Robert V. O'Neill,et al.  Pattern, process, and predictability: the use of neutral models for landscape analysis , 1991 .

[5]  Eric J. Gustafson,et al.  Quantifying Landscape Spatial Pattern: What Is the State of the Art? , 1998, Ecosystems.

[6]  N. Lam,et al.  Multi-Scale Fractal Analysis of Image Texture and Pattern , 1999 .

[7]  Christopher O. Justice,et al.  The spatial variation of vegetation changes at very coarse scales , 1990 .

[8]  J. Wiens.  Spatial Scaling in Ecology , 1989 .

[9]  Philip J. Howarth,et al.  The Effects of Spatial Resolution on Land Cover/Land Use Theme Extraction from Airborne Digital Data , 1987 .

[10]  M. MacKenzie,et al.  Effects of sensor spatial resolution on landscape structure parameters , 1995, Landscape Ecology.

[11]  C. Woodcock,et al.  The factor of scale in remote sensing , 1987 .

[12]  Bruce T. Milne,et al.  Effects of changing spatial scale on the analysis of landscape pattern , 1989, Landscape Ecology.

[13]  Kurt H. Riitters,et al.  Sensitivity of landscape metrics to pixel size , 1995 .

[14]  Scott G. Leibowitz,et al.  Use of Scale Invariance in Evaluating Judgement Indicators , 1999 .

[15]  Valerie I. Cullinan,et al.  A comparison of quantitative methods for examining landscape pattern and scale , 1992, Landscape Ecology.

[16]  Ling Bian,et al.  Comparing Effects of Aggregation Methods on Statistical and Spatial Properties of Simulated Spatial Data , 1999 .

[17]  G. Hess,et al.  Pattern and error in landscape ecology: A commentary , 1994, Landscape Ecology.

[18]  Jianguo Wu,et al.  The modifiable areal unit problem and implications for landscape ecology , 1996, Landscape Ecology.

[19]  Aaron Moody,et al.  The influence of scale and the spatial characteristics of landscapes on land-cover mapping using remote sensing , 1995, Landscape Ecology.

[20]  Anthony W King,et al.  Aggregating Fine-Scale Ecological Knowledge to Model Coarser-Scale Attributes of Ecosystems. , 1992, Ecological applications : a publication of the Ecological Society of America.

[21]  David J. Mladenoff,et al.  A Systems Analysis of the Global Boreal Forest: The southern boreal–northern hardwood forest border , 1992 .

[22]  J. T. Curtis,et al.  The Vegetation of Wisconsin: An Ordination of Plant Communities. , 1960 .

[23]  R. Brooks,et al.  Effects of landscape patterns on biotic communities , 1997, Landscape Ecology.

[24]  C. E. Woodcock,et al.  Geostatistical Estimation of Resolution- Dependent Variance in Remotely Sensed Images , 1999 .

[25]  P. Burrough.  Fractal dimensions of landscapes and other environmental data , 1981, Nature.

[26]  J. M. Thomas,et al.  Multiple landscape scales: An intersite comparison , 1991, Landscape Ecology.

[27]  Bruce T. Milne,et al.  Indices of landscape pattern , 1988, Landscape Ecology.

[28]  Hong S. He,et al.  An aggregation index (AI) to quantify spatial patterns of landscapes , 2000, Landscape Ecology.

[29]  W. Baker.  Spatially heterogeneous multi-scale response of landscapes to fire suppression , 1993 .

[30]  Peter T. Wolter,et al.  Improved forest classification in the northern Lake States using multi-temporal Landsat imagery , 1995 .

[31]  R. O'Neill,et al.  Landscape patterns in a disturbed environment , 1987 .

[32]  Bruce T. Milne,et al.  Scaling of ‘landscapes’ in landscape ecology, or, landscape ecology from a beetle's perspective , 1989, Landscape Ecology.

[33]  Vincent V. Salomnson.  The NASA Earth Observing System (EOS) Terra and Aqua Mission Moderate Resolution Imaging Spectroradiometer (MODIS: Science and Applications , 2003 .

[34]  Forrest G. Hall,et al.  Linking knowledge among spatial and temporal scales: Vegetation, atmosphere, climate and remote sensing , 1988, Landscape Ecology.

[35]  Robert V. O'Neill,et al.  Robust Analysis of Aggregation Error , 1982 .

[36]  Monica G. Turner,et al.  Predicting across scales: Theory development and testing , 1989, Landscape Ecology.

[37]  A S Fotheringham,et al.  The Modifiable Areal Unit Problem in Multivariate Statistical Analysis , 1991 .

[38]  Aaron Moody,et al.  Scale-dependent errors in the estimation of land-cover proportions. Implications for global land-cover datasets , 1994 .