ater 
  
79 
284 
ter 
2% 
6% 
ian 
ote 
pp. 
of 
EE 
«ov 
nal 
res. 
ual 
and 
ote 
and 
ern 
for 
the 
llar 
    
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
FOREST RESOURCES STUDY IN MONGOLIA USING 
ADVANCED SPATIAL TECHNOLOGIES 
D. Amarsaikhan * *, M. Saandar ", V. Battsengel ©, Sh. Amarjargal “ 
? Institute of Informatics and RS, MAS, Ulaanbaatar-51, Mongolia - amar64(@arvis.ac.mn 
® MonMap Engineering Services Co., Ulaanbaatar, Mongolia - msaandar@mongol.net 
* School of Geography and Geology, NUM, Ulaanbaatar, Mongolia - battsengel@num.edu.mn 
4 Research Centre of Astronomy and Geophysics, MAS, Ulaanbaatar, Mongolia - amarshrgl@yahoo.com 
Commission VII, WG VII/5 
KEY WORDS: Optical, Microwave, Forest mapping, Refined maximum likelihood classification 
ABSTRACT: 
The aim of this study is to conduct a forest resources study using optical and synthetic aperture radar (SAR) satellite images. For 
this purpose, a forest-dominated site around the Lake Khuvsgul located in northern Mongolia is selected. As remote sensing (RS) 
data sources, panchromatic and multispectral Landsat 7 images as well as ALOS PALSAR L-band HH polarization data are used. To 
produce a reliable land cover map from the multisensor images, a novel refined maximum likelihood classification based on the 
spectral and spatial thresholds are applied and for the accuracy assessment an overall accuracy is used. Overall, the research 
demonstrates that advanced spatial technologies based on optical and microwave RS are reliable tools for different forest studies. 
1. INTRODUCTION 
Forest is a very important natural resource that plays a 
significant role in keeping an environmental stability, 
ecological balance, environmental conservation, food security 
and sustainable development in both developed and developing 
countries. In recent years, deforestation and forest land 
degradation have become the main concern for forest 
specialists and ecologists as well as policy and decision-makers 
dealing with the environment. It has been found that much of 
the existing forests have been destroyed, mainly by shifting 
cultivation, timber preparation, legal and illegal logging, forest 
fires and increased number of people involved in agricultural 
activities Amarsaikhan ef al. 2011). To protect and conserve 
the deteriorating forest, it is very important to introduce a 
sustainable forest management policy. 
The concept of sustainable forest management should involve 
clear definition of the desired future condition of a forest, 
evaluation of the current management practices and thoroughly 
defined objectives to achieve a desired future condition. 
Achieving sustainable forest management should require 
effective measuring and monitoring activities which can 
provide reliable forest information to support policy and 
decision-making related to sustainable development (Haase 
and Camphausen, 2007). It is unambiguous that accurate and 
real-time forest related spatial information along with its 
attributes is the key for successful planning and management. 
In spatial context, such information might be collected from 
many different sources. However, the most reliable source that 
could provide real-time information for the accurate analysis 
could be RS (Amarsaikhan, 2011). 
  
* Corresponding author 
Traditionally, multispectral RS images have been widely used 
for forest monitoring and management. Since the end of the 
last century, single polarization SAR data sets have been 
increasingly accessible for the forest specialists. As the present 
space science and technology are so advanced, very high 
resolution multichannel optical and polarimetric SAR images 
are available for different forest studies. The combined 
application of optical and radar data sets can provide unique 
information for forest planning and management, because 
passive sensor images will represent spectral variations of the 
top layer of the forest classes, whereas microwave data with its 
penetrating capabilities can provide some additional 
information about forest canopy (Amarsaikhan ef al. 2004, 
Amarsaikhan et al. 2011). Moreover, it is clear that the 
integrated use of the optical and microwave data sets should 
improve an accuracy in a forest mapping, because as the 
images are acquired in different portions of electro-magnetic 
spectrum, could positively influence a decision-making in 
overlapping boundaries (Amarsaikhan et al. 2009). 
The aim of this research is to conduct a forest resources study 
using optical and microwave RS along with a geographical 
information system (GIS). For this purpose, a test site located in 
northern Mongolia has been selected. As RS data sources, 
multitemporal Landsat ETM+ images and ALOS PALSAR L- 
band HH polarization data were used. To produce a land cover 
map from the multisensor images, a novel refined maximum 
likelihood classification based on the spectral and spatial 
thresholds has been applied and for the accuracy assessment an 
overall accuracy was used. The analysis was carried out using 
Erdas Imagine and ArcGIS systems installed in a PC 
environment.