نوع مقاله : مقالة‌ تحقیقی‌ (پژوهشی‌)

نویسندگان

1 گروه پژوهشی سیستم‌های فضایی، پژوهشکده فضانوردی، پژوهشگاه هوافضا، وزارت علوم، تحقیقات و فناوری، تهران، ایران

2 گروه مهندسی نقشه‌برداری، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

3 پژوهشگاه هوافضا، وزارت علوم، تحقیقات و فناوری، تهران، ایران

10.22034/jsst.2021.1191

چکیده

آگاهی از روند تغییرات تراکمی عرصه‌های جنگلی نیازمند مدلی کارآ برای طبقه‌بندی تاج‌پوشش جنگل است. چالش مقدماتی تفکیک تاج‌پوشش جنگل از سایر پوشش‌های گیاهی غیرجنگلی نظیر بوته‌زارها، نیزارها و بیشه‌های متراکم است. در ادامه تلاش‌های قبلی برای بهبود عملکرد مدل FCD در این پژوهش با افزودن شاخص FCCI توأم با اعمال کرنل میانگین عملکرد مدل FCD ارتقاء یافت. طبقه‌بندی تاج پوشش تراکمی جنگل‌های هیرکانی مبتنی بر تصاویر سال 1396 سنجنده لندست 8 به منظور پیاده‌سازی، ارزیابی، صحت‌سنجی و تحلیل نتایج برگزیده شد. افزایش دقت مدل و حصول نتایج بهتر کاملا ملموس بوده و حتی از تفسیر چشمی نتایج نیز قابل تأیید است. تحلیل آماری نتایج نیز از افزایش 10% و 24% دقت کلی و ضریب کاپا مدل بهبودیافته نسبت به مدل اولیه حکایت دارد که البته در دو کلاس متراکم و بدون جنگل بارزتر می‌نمود. بصورت مشخص دقت کلاسی این دو منطقه در نتایج حاصل از مدل بهبودیافته به ترتیب حدود 13% و 7% افزایش نشان می‌دهد

کلیدواژه‌ها

عنوان مقاله [English]

Improvement of the forest canopy density model based on the addition of the FCC index and the average kernel implementation

نویسندگان [English]

  • Masoud Taefi Feijani 1
  • Saeed Azadnejad 2
  • Masoud Moradi 3

1 Space System Research group, Astronautic Dep., Aerospace Research Institute, Ministry of Science, Research and TechnologyوTehran, Iran

2 Faculty of Geodesy & Geomatics Engineering, K. N. Toosi University of Technology

3 Aerospace Research Institute, Ministry of Science, Research and Technology,Tehran, Iran

چکیده [English]

Awareness of the trend of forest canopy density classification requires an operational exact model for forest crown classification. The preliminary challenge is the separation of the forest crown from other non-warlike vegetation coverings. In the following, previous attempts to improve the performance of the FCD model, in this study, by adding the FCC index and the kernel, improved the average performance of the FCD model. The crown classification of Hyrcanian forests based on images of 1396 Landsat 8 was selected for implementation, evaluation, validation and analysis of the results. Improving the accuracy of the model is entirely sensible and even manual interpretation confirm it. The statistical analysis of the results also indicates a 10% and 24% increase in overall accuracy and kappa coefficient of the improved model compared to the initial model. Specifically, the accuracy of these two classes in the results of the improved model is about 13% and 7%, respectively.

کلیدواژه‌ها [English]

  • Forest canopy density
  • Forest color composite Index (FCCI)
  • Kernel function
  • Landsat 8
  • Hyrcanian forest
[1] Rikimaru, A., "TM Data Processing Guide for forest Canopy Density Mapping and Monitoring Model," ITTO workshop on Utilization of Remote Sensing in Site Assessment and Planning for Rehabilitation of Logged-over Forest, July 30-August 1, Bangkok, Thailand, 1996.
[2] Taefi Feijani, M.,. "Evaluation and Optimization of FCD Model in Estimating Forest Canopy Density Classes Using Data Fusion Methods and Image Indices Substitution," Master's Thesis, Tehran, Iran, 2006, 85 p. (In Persian).
[3] Jamalabad, M.S. and A. A. Abkar, "Forest Canopy Density Monitoring Using Satellite Images," In Geo-Imagery Bridging Continents XXth ISPRS Congress, Istanbul, Turkey, 2004.
[4] Azizi, Z., A. Najafi and H. Sohrabi, "Forest Canopy Density Estimating Using Satellite Images," The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 8. 2008.

[5] Huang, C., Yang, L., Wylie, B. K. & Homer, C.,. "A Strategy for Estimating Tree Canopy Density Using Landsat 7 ETM+ and High-resolution Images Over Large Areas," Published in the proceedings of the Third International Conference on Geospatial Information in Agriculture and Forestry held in Denver, Colorado, 5 -7 November, 2001.

[6] Hosseini, S.Z., M. Kappas and P. Propastin, Estimating Relationship between Vegetation Dynamic and Precipitation in Central Iran, Toledo. Spain, 2011.
[7] Yin, G, Z. Hu, X. Chen, T. Tiyip, "Vegetation Dynamics and its Response to Climate Change in Central Asia," Journal of Arid Land, Vol. 8, No. 3, 2016, pp. 375-388.
[8] Mosavi, B., "Comparison of High Resolution (Quick bird) and Medium Resolution (Landsat8-OLI) Satellite Images Capability In Estimation of Trees Aboveground Biomass," A Thesis of Master Student in Forest Science, Gorgan University of Agriculture and Natural Resources, 2015, 132 p.
[9] Ronoud, Gh. "Estimating Aboveground Woody Biomass of Fagus Orientalis Stands in Hyrcanian forest of Iran using Landsat 8 Satellite Data (Case study: Khyroud forest)," A Thesis of Master Student in forest science, University of Tehran, 2016103p.
[10] Attarchi, S. "Complex Land Cover Classification and Physical Properties Retrieval of the Hyrcanian Forest: A Multi-Source Remote Sensing Approach," A thesis of PhD student, TU Bergakademie Freiberg, 2014, 130p.
[11] Attarchi, S., and R. Gloaguen, "Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)." Remote Sensing, Vol. 6, No. 5, 2014, pp. 3693-3715.
[12] Mohammadi, J., S. Shataee, M. Namiranian, and E. Næsset, "Modeling Biophysical Properties of Broad-Leaved Stands in the Hyrcanian Forests of Iran using Fused Airborne Laser Scanner Data and Ultracam-D Images,"  International Journal of Applied Earth Observation and Geoinformation, Vol. 61, 2017, pp.32-45.
[13]Liu, J.G., "Evaluation of Landsat-7 ETM+ Panchromatic Band for Image Fusion with Multispectral Bands," Natural Resources Research, Vol. 9, No. 4, 2000, pp.269-276.
[14] Sharma, R., K. Hara, and R. Tateishi, "Developing Forest Cover Composites through a Combination of Landsat-8 Optical and Sentinel-1 SAR Data for the Visualization and Extraction of Forested Areas," Journal of Imaging, Vol. 4, No. 9, 2018, p.105.