John E. Estes

NATURE RESERVES: DO THEY CAPTURE THE FULL RANGE OF AMERICA'S BIOLOGICAL DIVERSITY?

Less than 6% of the coterminous United States is in nature reserves. As- sessment of the occurrence of nature reserves across ranges of elevation and soil productivity classes indicates that nature reserves are most frequently found at higher elevations and on less productive soils. The distribution of plants and animals suggests that the greatest number of species is found at lower elevations. A preliminary assessment of the occurrence of mapped land cover types indicates that ;60% of mapped cover types have ,10% of their area in nature reserves. Land ownership patterns show that areas of lower elevation and more productive soils are most often privately owned and already extensively converted to urban and agricultural uses. Thus any effort to establish a system of nature reserves that captures the full geographical and ecological range of cover types and species must fully engage the private sector.

A remote sensing research agenda for mapping and monitoring biodiversity

Abstract There is an urgent need to inventory and monitor indicators of biological diversity, such as species richness. Remotely-sensed data provide a means to accomplish part of this task, but there has been no comprehensive scientific framework to guide its effective application. Here we propose a remote sensing research agenda designed to improve the quality and quantity of information available for testing scientific hypotheses, monitoring, and conservation planning. Biodiversity should be more fully incorporated into ongoing Earth system science and global change programmes, with remote sensing featured as a prominent data acquisition and analysis tool.

Requirements and principles for the implementation and construction of large-scale geographic information systems

Abstract This paper provides a brief survey of the history, structure and functions of ‘traditional’ geographic information systems (GIS), and then suggests a set of requirements that large-scale GIS should satisfy, together with a set of principles for their satisfaction. These principles, which include the systematic application of techniques from several sub-fields of computer science to the design and implementation of GIS and the integration of techniques from computer vision and image processing into standard GIS technology, are discussed in some detail. In particular, the paper provides a detailed discussion of questions relating to appropriate data models, data structures and computational procedures for the efficient storage, retrieval and analysis of spatially-indexed data.

An information systems approach to the preservation of biological diversity

Abstract Although biological diversity has emerged in the 1980s as a major scientific and political issue, efforts at scientific assessment have been hampered by the lack of cohesive sets of data. We describe, in concept, a comprehensive national diversity information system, using geographical information system (GIS) techniques to organize existing data and improve spatial aspects of the assessment. One potential GIS analysis, to identify gaps in the network of nature reserves for California, is discussed in greater detail. By employing an information systems approach, available data can be used more effectively and better management strategies can be formulated.

Applications of NOAA-AVHRR 1 km data for environmental monitoring

Abstract This paper reviews the applications of NOAA-AVHRR 1 km data for environmental monitoring. This topic is very significant in view of the development of 1 km global datasets. Research papers reviewed herein largely describe application of AVHRR data for North America, Sahelian Africa and tropical forests of both Africa and South America. All 5 AVHRR bands have found some level of use for land-cover studies. However, the majority of the land characterization research papers used AVHRR/ NDVI as the main data source. Multi-temporal NDVI datasets have found wide use to describe vegetation phenology. AVHRR thermal bands have also been employed by a number of researchers for both surface temperature mapping and for land-cover discrimination especially in tropical rain forests. The most common data analysis techniques employed in these papers were regressions between bands and supervised classification procedures. The review indicated that land-cover mapping and direct estimation of land-cover parameters ...

Studying the Earth's Vegetation from Space

Understanding the effects of modern technological civilization on the biosphere requires greatly improved global estimates of the spatial distribution and temporal dynamics of major types of terrestrial vegetation, as well as information on biomass, productivity, and exchange of energy and chemical elements between the vegetation and the atmosphere, oceans, and soils. Past estimates of these vegetation characteristics have been, by necessity, based on extremely limited data; they have been little more than expert testimony of knowledgeable ecologists and biogeographers. Advances during the past decade in satellite remote sensing technology and computer processing, however, have made accurate, repeatable measurements of these characteristics possible. Remote sensing is the study of objects and phenomena from a great distance by systems that are not in contact with the object or phenomenon being investigated. A number of factors have contributed to the development of remote sensing as we know it today; these include the invention and development of multispectral scanners producing digital information, advances in computer processing and its applications to remote sensing, the development of stable highaltitude aircraft and satellites to carry the sensors, and scientific interest in using these tools. The technological advances in remote sensing have largely developed to satisfy needs for specific information for specific applications; interest among scientists in using remote sensing for basic research has arisen secondarily.

Using satellite remote sensing analysis to evaluate a socio-economic and ecological model of deforestation in Rondônia, Brazil

The effectiveness of an integrated socio-economic and ecological simulation model for estimating patterns and rates of deforestation in Rondonia, Brazil is evaluated using Landsat data and landscape pattern metrics. The Percent Cleared, Contagion, and Fractal Dimension of image classifications are compared to those determined from model outputs. Results indicate that rates and spatial patterns of deforestation are similar between model outputs and Landsat image analysis. Differences in clearing patterns between the model and Landsat data are due in part to topography, localized farming obstacles and the patchiness of clearings. The effects of varying spatial resolution on the metrics is also examined.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Coordinating hazardous waste management activities using geographical information systems

Abstract This paper describes a framework for the role of geographical information systems (GIS) in the monitoring and management of hazardous waste sites. Compilation of required information, incorporation of existing strategies for waste monitoring, analysis of these data in a GIS environment and the integration of computerized models for transport processes are discussed. Examples for the analysis of spatial data using techniques of cartographic overlay and the implementation of geo-statistical methods on monitoring data are provided from work in progress by the authors. These examples are set in the context of developing a fully integrated monitoring and management system utilizing GIS technology.

Performance analysis of image processing algorithms for classification of natural vegetation in the mountains of Southern California

Abstract The Earths forests fix carbon from the atmosphere during photosynthesis. Scientists are concerned that massive forest removals may promote an increase in atmospheric carbon dioxide, with possible global warming and related environmental effects. Space-based remote sensing may enable the production of accurate world forest maps needed to examine this concern objectively. To test the limits of remote sensing for large-area forest mapping, we use LANDSAT data acquired over a site in the forested mountains of southern California to examine the relative capacities of a variety of popular image processing algorithms to discriminate different forest types. Results indicate that certain algorithms are best suited to forest classification. Differences in performance between the algorithms tested appear related to variations in their sensitivities to spectral variations caused by background reflectance, differential illumination, and spatial pattern by species. Results emphasize the complexity between the...