Research Papers

Canopy cover estimation across semi-Mediterranean woodlands: application of high-resolution earth observation data

[+] Author Affiliations
Hamed Naghavi

Sari University of Agricultural Sciences and Natural Resources, Department of Forestry, P. O. Box 578, Sari, Iran

Asghar Fallah

Sari University of Agricultural Sciences and Natural Resources, Department of Forestry, P. O. Box 578, Sari, Iran

Shaban Shataee

Gorgan University of Agricultural Sciences and Natural Resources, Department of Forestry, P. O. Box 386, Gorgan, Iran

Hooman Latifi

University of Wuerzburg, Department of Remote Sensing, Oswald-Kuelpe-Weg 86, D-97074 Wuerzburg, Germany

Javad Soosani

Lorestan University, Department of Forestry, P. O. Box 465, Khorram Abad, Iran

Habib Ramezani

Swedish University of Agricultural Sciences, Department of Forest Resource Management, 901 83 Umeå, Sweden

Christopher Conrad

University of Wuerzburg, Department of Remote Sensing, Oswald-Kuelpe-Weg 86, D-97074 Wuerzburg, Germany

J. Appl. Remote Sens. 8(1), 083524 (Nov 06, 2014). doi:10.1117/1.JRS.8.083524
History: Received May 23, 2014; Revised September 14, 2014; Accepted October 3, 2014
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Abstract.  The semi-Mediterranean Zagros forests in western Iran are a crucial source of environmental services, but are severely threatened by climatic and anthropological constraints. Thus, an adequate inventory of existing tree cover is essential for conservation purposes. We combined ground samples and Quickbird imagery for mapping the canopy cover in a portion of unmanaged Quercus brantii stands. Orthorectified Quickbird imagery was preprocessed to derive a set of features to enhance the vegetation signal by minimizing solar irradiance effects. A recursive feature elimination was conducted to screen the predictor feature space. The random forest (RF) and support vector machines (SVMs) were applied for modeling. The input datasets were composed of four sets of predictors including the full set of predictors, the four original Quickbird bands, selected vegetation indices, and the soil line-based vegetation indices. The highest r2 and lowest relative root mean square error (RMSE) were observed in modeling with total indices and the full data set in both modeling methods. Regardless of the input dataset used, the RF models outperformed the SVM by returning higher r2 and lower relative RMSEs. It can be concluded that applying these methods and vegetation indices can provide useful information for the retrieval of canopy cover in mountainous, semiarid stands which is crucial for conservation practices in such areas.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Hamed Naghavi ; Asghar Fallah ; Shaban Shataee ; Hooman Latifi ; Javad Soosani, et al.
"Canopy cover estimation across semi-Mediterranean woodlands: application of high-resolution earth observation data", J. Appl. Remote Sens. 8(1), 083524 (Nov 06, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083524


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