Interrogating Land Cover Categories: Metaphor and Method in Remote Sensing

The increasing sophistication of classification techniques used in land use and land cover analysis has not been matched by attention to the origin and effects of land cover categories. While classifications appear unproblematic and self-evident, they carry with them their own histories, meanings and effects, which remain largely unexamined. In an effort at such scrutiny, we examine the origins of land cover categories deployed in remote sensing and conclude that categories are theory-laden metaphors and occur epistemologically prior to any clustering algorithm, no matter how sophisticated. We describe the problematic effects that the imposition of classification systems in place of in situ knowledge of the landscape can have, especially in a colonial or post-colonial context. As an alternative to imposed classification, we propose and demonstrate an empirical technique based upon a growing body of work in participatory GIS. The method compares image classifications based on local and expert knowledge, using a case study from Rajasthan, India, concluding that differing metaphors of landscape lead to divergent measures of land cover.     

The Impact on Topographic Mapping of Developments in Land and Air Survey: 1900-1939

At the beginning of the twentieth century, little of the world outside of Europe, India, and parts of North America had been covered by topographic mapping. By the end of the century there were few areas that were not covered by topographic mapping, if only at small scales. Most of the technological changes that made this extension of map coverage possible were pioneered dunng the period 1900-1939. This paper reviews the technological deveiopments in land and air survey that took place during that period and relates them to the drive to produce cost-effective mapping for civil and military purposes.     

A History and Analysis of Mapping Urban Expansion in the Kathmandu Valley,Nepal

Abstract

There have been numerous efforts over many years to map or delineate urban locations and features in the Kathmandu Valley of Nepal. This study acquired 27 land useland cover maps for the Valley or the urban portions of the Valley. Those maps vary greatly in their mapping parameters. The objectives of this study were to first conduct a cartographic comparison of the differences in the creation and content of the maps and then do an analysis of the urban changes in the Valley based upon the maps. The maps for the Valley have differed in their source materials, the amount of field work involved, scale and minimum mapping units, classifications used, definitions of classes and coordinate systems. Source materials have included various scales and formats of aerial photography and different satellite systems. The most difficult issue in comparing the maps is the varied classification systems and definitions. The same feature will be classified differently from map to map. This is particularly an issue for institutional features such as temples, palaces, educational facilities, open public space and governmental sites. Definitions of residential areas are also not consistent. Even with the differences in mapping parameters, considerable useful information can be obtained by comparing these maps. These include a simply documentation of the urban extent and the generally resulting loss in agricultural lands. There was an increase in urban extent from 22 to 83km² between 1955 and 2000. Urban expansion has also changed from occurring on the upland river terraces or tars to the floodplains. Finally, while not directly documented in these maps, the tremendous pace of urban growth has resulted in multiple infrastructure and environmental challenges.     

Testing the Effects of Thematic Uncertainty on Spatial Decision-making

Dasymetric mapping techniques can be employed to estimate population characteristics of small areas that do not correspond to census enumeration areas. Land cover has been the most widely used source of ancillary data in dasymetric mapping. The current research examines the performance of alternative sources of ancillary data, including imperviousness, road networks, and nighttime lights. Nationally available datasets were used in the analysis to allow for replicability. The performance of the techniques used to examine these sources was compared to areal weighting and traditional land cover techniques. Four states were used in the analysis, representing a range of different geographic regions: Connecticut, New Mexico, Oregon, and South Carolina. Ancillary data sources were used to estimate census block group population counts using census tracts as source zones, and the results were compared to the known block group population counts. Results indicate that the performance of dasymetric methods varies substantially among study areas, and no single technique consistently outperforms all others. The three best techniques are imperviousness with values greater than 75 percent removed, imperviousness with values greater than 60 percent removed, and land cover. Total imperviousness and roads perform slightly worse, with nighttime lights performing the worst compared to all other ancillary data types. All techniques performed better than areal weighting.     

A Transition in Improving Maps: The ColorBrewer Example

Many map makers seek to share their map design efforts by distributing styles, fonts, templates, software, tips, and other sorts of instructions. For example, <www.mapsymbols.com> offers links to a variety of symbol and font design efforts by mapmakers who use ESRI's GIS products. In this article, I will reflect on the format for offering map design assistance that I have used in ColorBrewer (Figure 1). ColorBrewer <www.ColorBrewer.org> is a web tool for selecting color schemes for thematic maps. It has elicited a trickle of enthusiastic e-mail from pleased users who tell me that their maps are improved, and they are relieved to save time on a design challenge for which they are not confident of their skills. ColorBrewer is described in detail in two papers (Harrower and Brewer, in press; Brewer et al. 2003). It is described briefly here to provide context for my reflections on a transition in cartography toward assisting people who want to represent their information spatially but who have little or no training in the conventions and principles of map design and data representation.     

Landscape Controls over Major Nutrients and Primary Productivity of Arctic Lakes

Increasing surface temperatures in the Arctic are affecting the dynamics between lakes and their landscapes. In this paper, we use landscape metrics for land cover and statistical analysis to explore the interactions between such measures as shape and patch density indices for land cover and lake primary productivity. The objective was to identify metrics that could be used to predict lake primary productivity, as measured by chlorophyll a, total nitrogen and total phosphorus estimates. Land cover and landscape metrics for the Toolik region of Alaska were derived using satellite imagery and Fragstats software. The metrics, treated as independent variables in a stepwise regression, were derived for two levels of land cover. The first comprised the entire watershed studied; the second was derived using buffers created around water channels within each watershed. A statistically significant model for each dependent variable was obtained. Results suggest that, of the metrics tested; those related to broad leaf vegetation complexes were most useful in predicting lake primary productivity. The Landscape Shape Index for riparian patches and the Patch Density for heath complex were the two most important metrics for predicting variation in chlorophyll a (p<0.001, r² = 0.52). For total nitrogen estimates, the most significant metrics were Percentage of riparian complex and Patch Density for fen complex (p<0.001, r² = 0.48). Total phosphorus estimates were most influenced by the Patch Density for shrub complex, the Mean Shape Index for moist acidic tundra complex, and the Patch Density for aquatic vegetation (p<0.001, r² = 0.52).     

Cartographic Aspects of Land Cover Change Detection (Over- and Underestimation in the I&CORINE Land Cover 2000 Project)

Abstract

This paper presents the results of analysis of the data obtained by the method of computer-aided visual interpretation of satellite images used for identification of changes in land cover within the framework of the Image and CORINE Land Cover 2000 (I&CLC2000) Project (jointly managed by the European Environment Agency in Copenhagen, Denmark and the Joint Research Centre of the European Commission in Ispra, Italy). These data are also relevant in cartography. Land cover changes identified by the method mentioned may contain mistakes caused by over- or underestimation. The paper describes these mistakes. Overestimation (technical change) of the extent of land cover change is caused by adding the residual polygons (smaller than 25 ha) to neighbouring polygons. Underestimation is caused by the fact that discernible changes concerning areas larger than 5 ha which showed up in objects with areas smaller than 25 ha were not identified and, consequently, not included in either CLC90 or CLC2000 data layers; e.g. Dutch CLC_change database users' accuracy indicates an overestimation of 8.8% whereas the comparison of net change indicates a small, insignificant underestimation. In spite of the problems referred to, caused by overestimation or underestimation, the datasets on land cover changes in Europe for the 1990s and the year 2000 (± one year) can also be used for the compilation of land cover change maps at the regional, national and European levels.