Measuring long-term ecological changes in densely populated landscapes using current and historical high resolution imagery

Abstract

Long-term ecological changes within densely populated landscapes account for a growing share of global environmental change. Measuring the causes and consequences of these changes remains a challenge because of their fine spatial scale and complexity. Here, we measure long-term ecological changes, circa 1950 to 2002, within six 1 km² sites in densely populated rural China and in urban and suburban Baltimore, Maryland, USA using a standardized procedure for fine-scale feature-based ecological mapping from high spatial resolution (≤ 1 m) imagery. The median size of ecologically distinct landscape features (ecotopes) mapped by this procedure was just 520 m², though size, count and perimeter of features varied considerably both within and between sites. Land management and vegetation cover changed substantially, over 28% to 87% of site areas, but most of this change occurred in small patches with area < 4000 m². Landscape complexity also increased over time by the fragmentation of landscapes into a larger number of smaller features with an increasing diversity of ecotope classes. Detailed analysis of fine-scale landscape transformations helped identify the causes and consequences of ecologically significant changes within and across sites, including unexpected increases in perennial vegetation cover and the linkage of impervious surface area with population density. These and other results demonstrate the general utility of anthropogenic ecotope mapping as a tool for cross-site comparison and sampled regional estimates of long-term ecological changes within densely populated landscapes.

Introduction

Densely populated rural, urban and suburban landscapes now cover as great an extent of Earth's land surface as do tropical rainforests and many other globally important ecosystems (Achard et al., 2002, Ellis, 2004, Foley et al., 2003). Ecosystem processes and their spatial patterns within these anthropogenic landscapes are profoundly altered by human activity and contribute disproportionately more per unit area to global changes in climate, biogeochemical cycles and biodiversity (Foley et al., 2005, Hope et al., 2003, Kalnay and Cai, 2003, Kaye et al., 2004, Matson et al., 1997, Vitousek et al., 1997). Given their global impacts and the fact that most humans live within them (∼5.8 of 6.2 billion persons live in areas with ≥ 25 persons km^− 2; Oak Ridge National Laboratory, 2004), the measurement and mediation of long-term ecological changes within densely populated landscapes are a matter of serious global, regional, and local concern (Foley et al., 2005, Vitousek et al., 1997).

In comparison with deforestation, urban expansion, and other extensive landscape transformations that often precede dense human occupation, the causes and consequences of long-term ecological changes within densely populated landscapes are only beginning to be understood (Foster, 1992, Green et al., 2005, Grimm et al., 2000, Heilig, 1994, Hope et al., 2003, Kaye et al., 2004, Lambin et al., 2001, Turner et al., 1994). This is not surprising, considering that landscape transformations within densely populated landscapes incorporate a wide variety of complex land management practices that are characterized by fine-scale changes in landscape structure (< 30 m) caused by the creation, transformation, and abandonment of anthropogenic features with distinct boundaries, such as buildings, roads, yards and small agricultural plots (Ellis et al., 2000a, Foster, 1992, Jensen and Cowen, 1999). These complex fine-scale changes in land use are a challenge to measure by conventional remote sensing approaches (Cihlar and Jansen, 2001, Forster, 1985, Guindon et al., 2004, Lobell and Asner, 2004, Price, 2003, Rindfuss et al., 2004, Thomas et al., 2003, Woodcock and Strahler, 1987) and are usually left out of global and regional ecological change estimates, potentially introducing substantial errors into these (Easterling, 1997, Houghton, 2003, House et al., 2003, Hurtt et al., 2003, Johnes and Butterfield, 2002, Turner et al., 1994).

Long-term ecological changes within anthropogenic landscapes are the combined result of changes in landscape structure, land management practices, and ecosystem processes (Binford et al., 2004, Ellis, 2004, Grimm et al., 2000, Kaye et al., 2004, Matson et al., 1998, Rindfuss et al., 2004, Turner et al., 1994). Usually, these are measured by different methods, each with different land units, and the results are then integrated to estimate ecological change (review by Rindfuss et al., 2004). However, the simplest way to link these measurements is to use the same land units when measuring changes in landscape structure, when obtaining land management data by interviewing local land managers, and when sampling and measuring ecological parameters in the field (Ellis, 2004). To accomplish this, landscapes must first be stratified into ecologically distinct features identifiable to both land managers and ecologists in the field and in imagery, a task best accomplished by field-validated interpretation of ecologically distinct features in high spatial resolution imagery (≤ 1 m; Ellis, 2004, Jensen and Cowen, 1999, Thomas et al., 2003). Moreover, to measure ecological changes over the long term (> 50 y) and across the full range of anthropogenic landscapes, from rural to urban, from floodplain to mountainous, and from pre-industrial to contemporary, a standardized a priori ecological classification procedure is necessary that can produce consistent results from historical aerial photographs and other sources of high spatial resolution imagery, including IKONOS and Quickbird (Cihlar and Jansen, 2001, Jansen and Gregorio, 2002, Kadmon and Harari-Kremer, 1999, Sawaya et al., 2003, Thomlinson et al., 1996).

This study applies the first standardized fine-scale ecological mapping procedure designed explicitly for densely populated landscapes by measuring long-term ecological changes, circa 1950 to 2002, within six densely populated ecological research sites across rural China and in urban and suburban Baltimore, Maryland, USA. Consistent with the ecosystem concept, which combines biotic and abiotic components within a single unit (the ecosystem), our procedure stratifies landscapes into ecologically distinct units (ecotopes) based on a combination of biotic and abiotic classification terms (Ellis et al., 2000a, Klijn and Udo De Haes, 1994). The procedure maps ecotope features based on relatively stable boundaries between ecologically distinct classes of land management and vegetation cover observable in the field at ground level, facilitating ecological fieldwork and land management interviews and providing a consistent mapping product from the complex layered mixture of land cover and land use that predominates in densely populated landscapes (Fig. 1; Sawaya et al., 2003, Jensen and Cowen, 1999). To our knowledge, all existing a priori standards for thematic environmental mapping are either lower resolution pixel based methods (30–1000 m; e.g. Cruickshank and Tomlinson, 1996, Hansen et al., 2000, Homer et al., 2004, Latifovic et al., 2004) or are site- or sensor-based systems that were not designed for consistent long-term change measurements across different regions of the world prior to the 1990s (e.g. Akbari et al., 2003, Anderson et al., 1976, Freeman and Buck, 2003, Kadmon and Harari-Kremer, 1999, Lu et al., 2004, Thomas et al., 2003, Thomlinson et al., 1999). Moreover, we know of no other existing ecological mapping system designed specifically to stratify anthropogenic landscapes into ecologically distinct features that are as useful for surveying local land management practices as they are for sampled ecological measurements in the field.

There are several key challenges in measuring fine-scale ecological changes based on field-validated feature-based mapping. First of all, like land management surveys and ecological sampling in the field, fine-scale mapping is highly resource-intensive. As a result, regional measurements of fine-scale ecological changes are best accomplished by the parsimonious application of these methods within regionally stratified sampling designs linked to data obtained by coarser-resolution remote sensing, such as area frame sampling (Achard et al., 2002, Cihlar et al., 2000, Ellis, 2004, Gallego, 2004, Gallego et al., 1994, Hurtt et al., 2003, Price, 2003, Stehman, 2005). Our fine-scale mapping procedure was therefore designed expressly for application within sample cells selected by regional analysis, so that fine-scale measurements within sample cells, such as crop area, tree biomass, and fertilizer inputs can be linked directly with regional remote sensing data to estimate the causes and consequences of fine-scale ecological changes at regional scales (Ellis, 2004).

Another issue in measuring fine-scale ecological changes is that changes measured by comparing current and historical maps are highly sensitive to “false change” errors caused by misregistration between maps (Foody, 2002, Townshend et al., 1992). This error can be avoided by estimating changes in ecological map class areas across entire sample cells, if sample cells are large enough (Wang & Ellis, 2005b). Another major source of error is disagreement between trained interpreters in both feature mapping (shape-based error) and feature classification, even when maps are field-validated by interpreters (Cherrill and McClean, 1999, Ellis and Wang, submitted for publication, Green and Hartley, 2000, Powell et al., 2004). Though interpreter error is unavoidable, it can be reduced by standardized collaborative training to calibrate results across interpreters, by scale-explicit rules for mapping and classification, and by the continuous centralized supervision of local mapping efforts (Cherrill and McClean, 1999, Cherrill et al., 1995, Ellis and Wang, submitted for publication, Powell et al., 2004). Most importantly, interpreter error in map class area estimates can be quantified to predict conservative error intervals that prevent false detection of changes and differences in map class areas (Type I error; Ellis and Wang, submitted for publication, Schenker and Gentleman, 2001).

This study will demonstrate that fine-scale change measurements reveal substantial and often unexpected long-term ecological changes that would not be observable by coarser scale approaches. The general utility of a priori hierarchical ecological classification will be established by comparing land form, use and cover across environmentally diverse rural and urban landscapes across China and in the USA, and by comparing long-term changes in land use and land cover across sites. The causes and consequences of pronounced long-term changes in land use and land cover across sites are then investigated using the more detailed information available in fine-scale ecotope maps of densely populated landscapes.