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Geology topics

Gary E. Johnson

Publications and source records attributed to Gary E. Johnson.

7 recordsLinked to original sources

Applying cumulative effects to strategically advance large‐scale ecosystem restoration

International efforts to restore degraded ecosystems will continue to expand over the coming decades, yet the factors contributing to the effectiveness of long‐term restoration across large areas remain largely unexplored. At large scales, outcomes are more complex and synergistic than the additive impacts of individual restoration projects. Here, we propose a cumulative‐effects conceptual framework to inform restoration design and implementation and to comprehensively measure ecological outcomes. To evaluate and illustrate this approach, we reviewed long‐term restoration in several large coastal and riverine areas across the US: the greater Florida Everglades; Gulf of Mexico coast; lower Columbia River and estuary; Puget Sound; San Francisco Bay and Sacramento–San Joaquin Delta; Missouri River; and northeastern coastal states. Evidence supported eight modes of cumulative effects of interacting restoration projects, which improved outcomes for species and ecosystems at landscape and regional scales. We conclude that cumulative effects, usually measured for ecosystem degradation, are also measurable for ecosystem restoration. The consideration of evidence‐based cumulative effects will help managers of large‐scale restoration capitalize on positive feedback and reduce countervailing effects.

Gulf of Mexico, San Francisco Bay/Sacramento Delta

Volgograd and vicinity: a Landsat view

Many diverse features can be discerned on the Landsat image of Volgograd and vicinity. Some of these features have resulted directly from man's alteration of the land surface in accordance with Stalin's and Khrushchev's plans for control of climate and for development in Volgograd and the surrounding area. Landsat images such as the one in this example provide the opportunity to inventory and assess man's imprint upon the land on a regional basis from a unique perspective.

Volgograd

Oahu: perspective from space

Satellite remote sensing provides us with a unique perspective from space. This perspective is synoptic in nature and provides regional views of most of the land areas of the earth. The orbital characteristics of the Landsat system are such that repetitive imagery of the same area may be obtained. Because of the permanent nature of the imagery, it may be retrieved for comparative analysis at any time. Comparisons of this image of Oahu with maps of the island (for example, the Oahu, Hawaii, 1:250,000-scale topographic map) will enable the reader to readily identify the place names discussed in this article and permit a more detailed interpretation of the image.

Hawaii

Overview of South‐east Asia land cover using a NOAA AVHRR one kilometer composite

A cloud free AVHRR composite of South‐East Asia at one kilometer resolution has been produced from 38 selected daily NOAA‐11 AVHRR images. Geometric accuracy of about 1 pixel is achieved using a two‐step rectification algorithm (orbital model and transformation by ground control points). A spatial and spectral enhancement has been performed, the sea masked out and political boundaries included in the final product. This AVHRR composite is particularly useful for a comprehensive overview of land cover at a regional scale. Qualitative comparison between a monthly composite and the existing forest maps highlights the forest cover change and points out the hot spots where the maps have to be updated.

Geocarto International

The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example

The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs. The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.

Oregon