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Articles containing the keyword 'satellite imagery'.

Category: Research article

article id 478, category Research article
Ronald E. McRoberts, Daniel G. Wendt, Greg C. Liknes. (2005). Stratified estimation of forest inventory variables using spatially summarized stratifications. Silva Fennica vol. 39 no. 4 article id 478. https://doi.org/10.14214/sf.478
Large area natural resource inventory programs typically report estimates for selected geographic areas such as states or provinces, counties, and municipalities. To increase the precision of estimates, inventory programs may use stratified estimation, with classified satellite imagery having been found to be an efficient and effective basis for stratification. For the benefit of users who desire additional analyses, the inventory programs often make data and estimation procedures available via the Internet. For their own analyses, users frequently request access to stratifications used by the inventory programs. When data analysis is via the Internet and stratifications are based on classifications of even medium resolution satellite imagery, the memory requirements for storing the stratifications and the online time for processing them may be excessive. One solution is to summarize the stratifications at coarser spatial scales, thus reducing both storage requirements and processing time. If the bias and loss of precision resulting from using summaries of stratifications is acceptably small, then this approach is viable. Methods were investigated for using summaries of stratifications that do not require storing and processing the entire pixel-level stratifications. Methods that summarized satellite image-based 30 m x 30 m pixel stratifications at spatial scales up to 2400 ha produced stratified estimates of the mean that were generally within 5-percent of estimates for the same areas obtained using the pixel stratifications. In addition, stratified estimates of variances using summarized stratifications realized nearly all the gain in precision that was obtained with the underlying pixel stratifications.
  • McRoberts, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 ORCID ID:E-mail: rmcroberts@fs.fed.us (email)
  • Wendt, Region 9, USDA Forest Service, 626 East Wisconsin Avenue, Milwaukee, Wisconsin 53202, USA ORCID ID:E-mail:
  • Liknes, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 ORCID ID:E-mail:
article id 367, category Research article
Sakari Tuominen, Markus Haakana. (2005). Landsat TM imagery and high altitude aerial photographs in estimation of forest characteristics. Silva Fennica vol. 39 no. 4 article id 367. https://doi.org/10.14214/sf.367
Satellite sensor data have traditionally been used in multi-source forest inventory for estimating forest characteristics. Their advantages generally are large geographic coverage and large spectral range. Another remote sensing data source for forest inventories offering a large geographic coverage is high altitude aerial photography. In high altitude aerial photographs the spectral range is very narrow but the spatial resolution is high. This allows the extraction of texture features for forest inventory purposes. In this study we utilized a Landsat 7 ETM satellite image, a photo mosaic composed of high altitude panchromatic aerial photographs, and a combination of the aforementioned in estimating forest attributes for an area covering approximately 281 000 ha in Forestry Centre Häme-Uusimaa in Southern Finland. Sample plots of 9th National Forest Inventory (NFI9) were used as field data. In the estimation, 6 Landsat 7 ETM image channels were used. For aerial photographs, 4 image channels were composed from the spectral averages and texture features. In combining both data sources, 6 Landsat channels and 3 aerial image texture channels were selected for the analysis. The accuracy of forest estimates based on the Landsat image was better than that of estimates based on high altitude aerial photographs. On the other hand, using the combination of Landsat ETM spectral features and textural features on high altitude aerial photographs improved the estimation accuracy of most forest attributes.
  • Tuominen, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland ORCID ID:E-mail: sakari.tuominen@metla.fi (email)
  • Haakana, Finnish Forest Research Institute, Unioninkatu 40 A, FI-00170 Helsinki, Finland ORCID ID:E-mail:

Category: Article

article id 5219, category Article
Simo Poso, Tuomas Häme, Raito Paananen. (1984). A method for estimating the stand characteristics of a forest compartment using satellite imagery. Silva Fennica vol. 18 no. 3 article id 5219. https://doi.org/10.14214/sf.a15398

The paper presents a method based on two phase sampling and applicable to forest inventories. The first phase estimates are obtained from satellite imagery and, if required, from extra material such as maps. Second phase estimates are measured in the field. The method is flexible and also applicable to compartmentwise forest inventories. The experiments were based on six study areas with 439 relascope plots. The correlation coefficients between first and second stage estimates varied largely according to the study area.

The PDF includes a summary in Finnish.

  • Poso, ORCID ID:E-mail:
  • Häme, ORCID ID:E-mail:
  • Paananen, ORCID ID:E-mail:

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