USGS ScienceSearch

Geology topics

R. H. Haas

Publications and source records attributed to R. H. Haas.

7 recordsLinked to original sources

Evaluating landsat thematic mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands

Ground data from the Central Plains Experimental Range in northeast Colorado and Landsat satellite images of that area acquired in August 1989, June 1990, and September 1990 were used to evaluate the level of association that can be expected from a univariate model relating spectrally derived vegetation indices (difference, ratio, and normalized difference vegetation indices) and dried green vegetation biomass. The vegetation indices were related to the ground sample estimates using a sample point, spectral class, and greenness strata approach. No strong relationships were found between the vegetation indices and sample estimates of dried green biomass using the sample point approach. The spectral class approach produced significant results only for the June 1990 sample period ( r =0.96). Significant relationships were found for the August 1989, June 1990, and September 1990 samples periods ( r 2 =0.95, 0.71, and 0.95, respectively) when the data were aggregated by greenness strata. The high degree of association between green biomass and the NDVI, obtained when the data were combined into greenness strata, indicated that it is possible to predict green biomass levels on semiarid rangelands using univariate regression models.

Remote Sensing of Environment

Combining remote sensing techniques with simulation modelling for assessing rangeland resources

Simulation modelling and remote sensing techniques can be used to describe ecological processes. When used together, these tools can increase our understanding of the spatial variability of ecosystems. Remotely sensed data can be combined with simulation models for predicting the accumulation of plant biomass, as surrogate variables within the models, or as correlative information for monitoring entire eco‐regions.

Geocarto International

BIA interpretation techniques for vegetation mapping using thematic mapper false color composites (interim report for San Carlos Reservation)

The Bureau of Indian Affairs (BIA) is responsible for the natural resource management of approximately 52 million acres of Trust lands in the contiguous United States. The lands are distributed in a "patchwork" fashion throughout the country. Management responsibilities on these areas include: minerals, range, timber, fish and wildlife, agricultural, cultural, and archaeological resources. In an age of decreasing natural resources and increasing natural resource values, effective multiple resource management is critical. BIA has adopted a "systems approach" to natural resource management which utilizes Geographic Information System (GIS) technology. The GIS encompasses a continuum of spatial and relational data elements, and included functional capabilities such as: data collection, data entry, data base development, data analysis, data base management, display, and report generalization. In support of database development activities, BIA and BLM/TGS conducted a cooperative effort to investigate the potential of 1:100,000 scale Thematic Mapper (TM) False Color Composites (FCCs) for providing vegetation information suitable for input to the GIS and to later be incorporated as a generalized Bureau wide land cover map. Land cover information is critical as the majority of reservations currently have no land cover information in either map or digital form. This poster outlines an approach which includes the manual interpretation of land cover using TM FCCs, the digitizing of interpreted polygons, and the editing of digital data, used upon ground truthing exercises. An efficient and cost-effective methodology for generating large area land cover information is illustrated for the Mineral Strip area on the San Carlos Indian Reservation in Arizona. Techniques which capitalize on the knowledge of the local natural resources professionals, while minimizing machine processing requirements, are suggested.

Arizona

Evaluation of thematic mapper data for natural resource assessment

The U.S. Geological Survey EROS Data Center evaluated the utility of Landsat Thematic Mapper (TM) date for natural resource assessment, emphasizing manual interpretation and digital classification of the data for U.S. Department of the Interior applications. Substantially more information was derived from TM data than from Landsat Multispectral Scanner (MSS) data. Greater resolution of TM data aided in locating roads, small stock ponds, and many other land features that could be used as landmarks. The improved spatial resolution of TM data also permitted more efficient visual interpretations of land use, better identification of resource types, and improved assessment of ecological status of natural vegetation. TM data also provided a new source of spectral information that was useful for natural resource assessment. New mid-infrared spectral bands, TM band 5 and band 7, aided in distinguishing water resources, wetland vegetation resources, and other important terrain features. The added information was useful for both manual interpretation and digital data classification of vegetation resources and land features. Results from the analyses of both TM and TM simulator (TMS) spectral data suggest that the coefficient of variation for major land cover types is generally less for TM data than for MSS data taken from the same area. This reduction in variance should contribute to an improved multispectral analysis, contributing new information about vegetation in natural ecosystems. Although the amount of new information in TM bands 5 and 7 is mall, it is unique in that the same information cannot be derived from four-band Landsat MSS spectral data.

Conference Paper