ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Collection
Keywords
Years
  • 1
    facet.materialart.
    Unknown
    LANDSAT applications to wetlands classification in the upper Mississippi River Valley (1980)
    In:  CASI
    Details
    Publication Date: 2016-06-07
    Description: A 25% improvement in average classification accuracy was realized by processing double-date vs. single-date data. Under the spectrally and spatially complex site conditions characterizing the geographical area used, further improvement in wetland classification accuracy is apparently precluded by the spectral and spatial resolution restrictions of the LANDSAT MSS. Full scene analysis of scanning densitometer data extracted from scale infrared photography failed to permit discrimination of many wetland and nonwetland cover types. When classification of photographic data was limited to wetland areas only, much more detailed and accurate classification could be made. The integration of conventional image interpretation (to simply delineate wetland boundaries) and machine assisted classification (to discriminate among cover types present within the wetland areas) appears to warrant further research to study the feasibility and cost of extending this methodology over a large area using LANDSAT and/or small scale photography.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Minnesota Univ. A Study of Minn. Land and Water Resources Using Remote Sensing, Vol. 13; p 5-29
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
  • 2
    facet.materialart.
    Unknown
    An evaluation of ISOCLS and CLASSY clustering algorithms for forest classification in northern Idaho (1981)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: Both the iterative self-organizing clustering system (ISOCLS) and the CLASSY algorithms were applied to forest and nonforest classes for one 1:24,000 quadrangle map of northern Idaho and the classification and mapping accuracies were evaluated with 1:30,000 color infrared aerial photography. Confusion matrices for the two clustering algorithms were generated and studied to determine which is most applicable to forest and rangeland inventories in future projects. In an unsupervised mode, ISOCLS requires many trial-and-error runs to find the proper parameters to separate desired information classes. CLASSY tells more in a single run concerning the classes that can be separated, shows more promise for forest stratification than ISOCLS, and shows more promise for consistency. One major drawback to CLASSY is that important forest and range classes that are smaller than a minimum cluster size will be combined with other classes. The algorithm requires so much computer storage that only data sets as small as a quadrangle can be used at one time.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E82-10109 , NASA-CR-167447 , NAS 1.26:167447 , RRI-L1-04143 , JSC-17418 , LEMSCO-17154
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
  • 3
    facet.materialart.
    Unknown
    San Juan National Forest Land Management Planning Support System (LMPSS) requirements definition (1981)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: The role of remote sensing data as it relates to a three-component land management planning system (geographic information, data base management, and planning model) can be understood only when user requirements are known. Personnel at the San Juan National Forest in southwestern Colorado were interviewed to determine data needs for managing and monitoring timber, rangelands, wildlife, fisheries, soils, water, geology and recreation facilities. While all the information required for land management planning cannot be obtained using remote sensing techniques, valuable information can be provided for the geographic information system. A wide range of sensors such as small and large format cameras, synthetic aperture radar, and LANDSAT data should be utilized. Because of the detail and accuracy required, high altitude color infrared photography should serve as the baseline data base and be supplemented and updated with data from the other sensors.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E82-10108 , NASA-CR-167448 , NAS 1.26:167448 , RR-L1-04146 , JSC-17422 , LEMSCO-17163
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
  • 4
    facet.materialart.
    Unknown
    A comparison of remote sensing techniques for Minnesota wetlands classification (1981)
    In:  Other Sources
    Details
    Publication Date: 2019-07-13
    Description: A wetland classification study in a typically complex 650 sq km test site in east central Minnesota compared the time, cost and accuracy of manually interpreted 1:24,000 scale color infrared aerial photographs with digital analysis of Landsat data. The comparison was between the same general wetland and non-wetland classes; accuracy of both systems was evaluated with intensive ground verification. For the same general classes, the overall mapping accuracy was 96 percent for the aerial photo interpretation and 71 percent for Landsat double-date classification. Results with maximum likelihood and SECHO classifiers were the same, 71 percent, while mapping accuracy with a layered classifier was only 66 percent. Compared to a general geometric correction and a single-date data set, geographic position and classification accuracy improved when a precision geometric correction and a double-date data set were used. Landsat digital analysis was faster, 24 vs. 90 days, but photointerpretation was more economical at $0.15/hectare (including all costs of procurement, processing and analysis), compared with Landsat costs of $0.35/hectare (not including costs of data procurement, processing prior to delivery to user and related overhead).
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Annual William T. Pecora Memorial Symposium on Remote Sensing; Jun 10, 1979 - Jun 15, 1979; Sioux Falls, SD
    Format: text
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...