XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Type of content:: Konferenzschrift

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Reihe:: ISPRS archives

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Editor:: International Society for Photogrammetry and Remote Sensing

Author:: International Society for Photogrammetry and Remote Sensing, 22.; 2012; Melbourne

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Type of content:: Konferenzschrift

DOI:: 10.14463/KXP:1663822514

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Reihe:: ISPRS archives (volume 39, B8 (2012))

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Editor:: International Society for Photogrammetry and Remote Sensing

Author:: International Society for Photogrammetry and Remote Sensing, 22.; 2012; Melbourne

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/7: Forestry]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) F. Hoseini, A. A. Darvishsefat, N. Zargham*

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) F. Hoseini*, A. A. Darvishsefat" *, N. Zargham* a MSc Graduated, Faculty of Natural Resources, University of Tehran, Iran - Faezehhoseinil S@yahoo.com b Prof., Faculty of Natural Resources, University of Tehran, Iran - adarvish@ut.ac.ir * Associate Prof., Faculty of Natural Resources, University of Tehran, Iran - zargham@ut.ac.ir KEY WORDS: IRS-P6-LISS IV, Ground Truth, Pistachio Forests, Forest Density, Iran ABSTRACT: In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI and PCA were performed. A ground truth map included of 34 plots (each plot 1 ha) were prepared. Hard and soft supervised classifications were performed with 5 density classes (0-596, 5-10%, 10-15%, 15-20% and > 20%). Because of low separability of classes, some classes were merged and classifications were repeated with 3 classes. Finally, the highest overall accuracy and kappa coefficient of 70% and 0.44, respectively, were obtained with three classes (0-5%, 5-20%, and > 20%) by fuzzy classifier. Considering the low kappa value obtained, it could be concluded that the result of the classification was not desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests. 1. INTRODUCTION Pistachio (Pistacia vera) natural forests are one of the most important forest reserves in Iran which are considerable for their conservational and economical conditions. Providing spatial information and thematic maps are essential for recognize recognizing and manage managing these valuable forests. Unfortunately, there is not enough and comprehensive information related to this area. Forest canopy play a significant role in forest production, climate and ecosystem functions. Information describing forest canopy is essential for monitoring and sustainable management. There is a high urgency to develop new methods to map forest canopy in an efficient and timely manner. Remote sensing techniques are applied due to their synoptic and repetitive nature and ability to be utilized in areas which are not easily accessible. There are a variety of approaches that have been used to map forest canopy: (1) object-based classification [Dorren et al., 2003], (2) Maximum likelihood forest canopy density mapper (4) artificial neural network [Joshi ef al., 2006]. Due to importance of forest density maps, various satellite data and forest stands, continuing of these researches is needed. The main objective of this study is to investigate the capability of IRS-P6-LISS IV image for Pistachio forests density mapping in Khorasan province of Iran. 2. METHODOLOGY 2.1 Study area The study area in this research covered 500 hectares of the Khajekalat pistachio forest of Khorasan province in northeast of Iran at the border to Turkeminestan (36? 56' 56" N and 49? 53' 54" (Figure 1). This area is characterized by warm summer and cold winter with low precipitation which is located on 500-1243 meters above sea level. * Corresponding author. Pure stands of pistachio (Pistacia vera) with rarely associate species as Zygophylum eurypterum & Amygdalus scoparia in forms of bush, shrub and high trees are observed [Revised Plan of Pistachio Forest of Khajehkalat Studies, 2009]. Forest structure consists of coppice and high stands with low density (<25%) as sown in figure 2. a SER Figure 1. Location of the study area in Iran Figure 2. Overall view of the study area

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