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 
ESTIMATING MIXED BROADLEAVES FOREST STAND VOLUME USING DSM 
EXTRACTED FROM DIGITAL AERIAL IMAGES 
H. Sohrabi * * 
* Dept. of Forestry, Natural resources and Marine Science Faculty, Tarbiat Modares University, Iran - 
hsohrabi@modares.ac.ir 
Commission VIII, WG VIII/7 
KEY WORDS: Forest Volume, Digital Surface Model, Aerial Image, Regression Method, Hyrcanian Forests 
ABSTRACT: 
In mixed old growth broadleaves of Hyrcanian forests, it is difficult to estimate stand volume at plot level by remotely sensed data 
while LiDar data is absent. In this paper, a new approach has been proposed and tested for estimating stand forest volume. The 
approach is based on this idea that forest volume can be estimated by variation of trees height at plots. In the other word, the more 
the height variation in plot, the more the stand volume would be expected. For testing this idea, 120 circular 0.1 ha sample plots with 
systematic random design has been collected in Tonekaon forest located in Hyrcanian zone. 
Digital surface model (DSM) measure the height values of the first surface on the ground including terrain features, trees, building 
etc, which provides a topographic model of the earth's surface. The DSMs have been extracted automatically from aerial UltraCamD 
images so that ground pixel size for extracted DSM varied from 1 to 10 m size by 1m span. DSMs were checked manually for 
probable errors. Corresponded to ground samples, standard deviation and range of DSM pixels have been calculated. For modeling, 
non-linear regression method was used. 
The results showed that standard deviation of plot pixels with 5 m resolution was the most appropriate data for modeling. Relative 
bias and RMSE of estimation was 5.8 and 49.8 percent, respectively. 
Comparing to other approaches for estimating stand volume based on passive remote sensing data in mixed broadleaves forests, 
these results are more encouraging. One big problem in this method occurs when trees canopy cover is totally closed. In this 
situation, the standard deviation of height is low while stand volume is high. In future studies, applying forest stratification could be 
studied. 
1. INTRODUCTION most commercial packages use cross-correlation or matching of 
interest points (Waser et. al. 2008). 
Generally, forest stand volume is estimated using ground based In Iran, Airborne Laser Scanning (ALS) as the most precise 
measurements, but, many studies showed that remotely sensed source of canopy height data is not available and in the case of 
data have large capacity for such purposes. Several studies (e.g. availability, it is too expensive. Instead, DSMs which derived 
St-Onge and Achaichia, 2001; Watt and Donoghue, 2005) from aerial imagery could be used as a source of DSM. But in 
revealed that using traditional methods of field survey or aerial mountainous forests, with the lack of precise digital terrain 
photograph interpretation to gain information on exact forest model for deriving canopy height (by subtracting DSM and 
area and stand volume is not feasible for large programs DTM) they have limited uses. 
because of costs and time constraints. Here I presented a method based on statistical parameters (range 
Based on previous studies, accuracy of volume estimations and standard deviation) of DSM derived from aerial images at 
using only spectral information from 2D imagery obtained with plot level for estimating standing volume of old growth 
optical sensors is limited, especially for high volume (Patenaude Hyrcanian forests. 
et al, 2005; Sohrabi, 2008). Because, these data are relatively 
insensitive to canopy height and additional data about canopy 
height such as digital surface model is crucial. 2. MATERIAL AND METHODS 
Digital surface models (DSMs) are an important basis for many 
tasks of environmental analysis and environmental science, such 2.1 Study area, aerial images and DSM extraction 
as analysis of erosion and runoff dynamics or vegetation and 
infrastructure changes (Altmaier and Kany, 2002). Waser et. al. The test site was placed in a forest area of approximately 2240 
(2008) used logistic regression models and CIR aerial images, ha in Lirehsar forest, north of Tonekabon city, Mazandaran 
DSM derived from them to assess increase and decrease (2002— | Province, Iran. The terrain elevation in the study area ranges 
1997) of forest area and other wooded areas in a mire biotope. from 600 to 1360 m above sea level. 
DSMs can be achieved from various sources like radar The test sites were selected to provide variability of standing 
(Kellndorfer et al, 2003), laser scanning (Maltamo, et al, volume range and stand conditions that are typical of north 
2005), aerial images (Gruber and Schneider, 2007) and stereo Iranian forests. Forest stands in the test sites were largely 
satellite images (Altmaier and Kany, 2002). DSMs can be composed of beech (Fagus orientalis), hornbeam (Carpinus 
generated automatically by image matching methods, whereby betulus) trees with the presence of other species such as Oak 
(Quercus castaneifolia), Alder (Alnus subcordata), velvet 
  
* Corresponding author