FOREST COVER DENSITY MAPPING IN SPARSE AND SEMI DENSE FORESTS USING FOREST CANOPY DENSITY MODEL (CASE STUDY: MARIVAN FORESTS)

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SHAHVALI KOUHSHOUR A.; PIR BAVAGHAR M.; FATEHI P.

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of RS and GIS for Natural Resources Year:2012 | Volume:3 | Issue:3 Page(s): 73-83

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,888

Download:

Cites:

Information Journal Paper

Title

FOREST COVER DENSITY MAPPING IN SPARSE AND SEMI DENSE FORESTS USING FOREST CANOPY DENSITY MODEL (CASE STUDY: MARIVAN FORESTS)

Author(s)

SHAHVALI KOUHSHOUR A. | PIR BAVAGHAR M. | FATEHI P. | Issue Writer Certificate

Keywords

LANDSAT-7 SATELLITEQ2

FCD MODELQ2

FOREST CANOPY DENSITYQ2

ACCURACY ASSESSMENTQ2

MARIVAN FORESTSQ2

Abstract

The main aim of this study was the evaluation of the FOREST CANOPY DENSITY Model for prediction of FOREST CANOPY DENSITY, using Landsat-7 ETM+. The study area was the eastern part of Marivan city that situated in Kurdistan province. A Landsat image was geo-referenced with sub pixel accuracy. First, all bands (1-5 of ETM+ imagery) except band 6 was normalized and then four main indices of FCD MODEL, including Advanced Vegetation Index, Bare soil Index, Shadow Index and thermal Index was calculated, and the FOREST CANOPY DENSITY map was derived finally. Forest’s canopy densities according to 6, 4 and three classes were classified. To assess the accuracy of classified maps, a ground truth map using aerial photos with the scale 1: 20000 was produced. The overall accuracy and kappa coefficient for classification 6 and four classes were obtained equal to 52%, 0.29 and 53%, 0.30, respectively. Spectral similarity between open density classes and irradiance of background soil in these classes reduced the accuracy as the result. Actually, in the dense forest, the result will be more accurate. According to the results, this method could be relatively desired for Zagro’s forests.

Cites

EVALUATION OF FOUR ALGORITHMS FOR ESTIMATION OF CANOPY COVER OF MANGROVE FORESTS BY USING AERIAL IMAGERY

References

Cite

APA: Copy

SHAHVALI KOUHSHOUR, A., PIR BAVAGHAR, M., & FATEHI, P.. (2012). FOREST COVER DENSITY MAPPING IN SPARSE AND SEMI DENSE FORESTS USING FOREST CANOPY DENSITY MODEL (CASE STUDY: MARIVAN FORESTS). JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE), 3(3), 73-83. SID. https://sid.ir/paper/189423/en

Vancouver: Copy

SHAHVALI KOUHSHOUR A., PIR BAVAGHAR M., FATEHI P.. FOREST COVER DENSITY MAPPING IN SPARSE AND SEMI DENSE FORESTS USING FOREST CANOPY DENSITY MODEL (CASE STUDY: MARIVAN FORESTS). JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE)[Internet]. 2012;3(3):73-83. Available from: https://sid.ir/paper/189423/en

IEEE: Copy

A. SHAHVALI KOUHSHOUR, M. PIR BAVAGHAR, and P. FATEHI, “FOREST COVER DENSITY MAPPING IN SPARSE AND SEMI DENSE FORESTS USING FOREST CANOPY DENSITY MODEL (CASE STUDY: MARIVAN FORESTS),” JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE), vol. 3, no. 3, pp. 73–83, 2012, [Online]. Available: https://sid.ir/paper/189423/en

Related Journal Papers