Full text: Technical Commission VIII (B8)

  
  
    
   
     
    
   
    
   
   
   
    
     
   
  
  
  
  
  
     
    
   
    
  
    
    
    
   
   
   
   
   
   
    
   
   
    
  
   
    
   
   
    
    
    
        
  
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 
at + 106,91 
60.00 4 ; 
40.00 
20.00 
AteaNDVI (kem?) 
0.00 
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 
AreaNOVIE (km?) 
  
Flow (Ls) 
  
€} 
   
  
  
   
  
    
   
e AreaNDVI s—— Rainfalt 
50.00 100.00 
$ E 
= £ 
a 5000 = 
«+ = 
+ 0.00 
2000 2004 2002 2003 2004 2005 2006 2007 2008 2009 2010 
az # AreaNDVE zSimulsted ArsaNDVI 
0.604 Phragmites MR. 0.20 
ERE F 
a" i 
ue A i 
& 040 ," Ephemeral |... 947 
* ^a i 
Nw i 
0.20 + 0.44 
  
  
JR MA Bd LAS QHD 
Figure 3: Study of wetland area vegetation extends implemented using the 0.2 NDVI threshold. a) Multiannual values of AreaNDVI 
recorded between February 2000 and May 2010 (MODIS-Terra and —Aqua data) and linear trendline. b) Correlation between 
Areanpy, and spring flow recorded between 2002 and 2010 for the spring DAAO001 (Figure 1c). White circles indicate years 2007, 
2008, and 2009. c) Comparison between 6-months smoothed rainfall and Area NDVI values recorded between 2000 and 2010. d1) 
Mean monthly NDVI values calculated from NDVI times traces (2002 to 2010) recorded at 2 selected Phragmites australis and 
ephemeral pixels (P1 and E2, Figure 1b) d2) Comparison between the simulated mean monthly Areaypy; reconstructed from the P1 
and E2 monthly signal (c1) and the measured mean monthly Areaypy;. 
4. DISCUSSION 
Satellite imagery provides the synoptic view necessary for 
inventory and mapping of ecological systems (Hewitt and 
Mason, 1990). The different spatial and temporal resolutions 
of sensors are complementary for conducting comprehensive 
environmental monitoring. This study demonstrates the 
potential of 250-m MODIS Normalized Difference 
Vegetation Index for studying long-term dynamics of 
Dalhousie Springs wetland vegetation. 
4.1 Delineating wetland extent 
The scale, heterogeneity and complex spatial patterning of 
the dispersed wetland vegetation posed challenges for this 
MODIS NDVI study. Selection of pixels representative of 
homogeneous vegetation stands was difficult and required 
expert knowledge of the environment. However, even if the 
number of samples was limited by the landscape (Figure 1b), 
their distinctiveness is supported by the Non-Metric 
Multidimensional Scaling (Figure 2), as the six DSC cover 
types fall into six distinctive clusters. Intra-group variability 
can be attributed to sample site differences resulting from 
variation between vegetation stands, intermixing of species 
and variable influences of soil background: the scale and 
heterogeneity of the wetlands made it difficult to find 
homogeneous patches that would fill the MODIS 
instantaneous ground resolution. 
Despite these limitations, our study demonstrates that spring— 
fed vegetation photosynthetic activity can be differentiated 
from surrounding land responses in this medium resolution 
imagery. The higher P90 values recorded in photosynthetic 
activity traces are good indicators of wetland vegetation, 
when riverine ecosystems are excluded (Figure 2). Similar 
results were obtained by White et al. (2011), using NDVI 
data derived from a QuickBird image and field vegetation 
percentage cover. These authors also found low NDVI signal 
for the GAB surrounding dryland vegetation, medium signal 
for the ephemeral wetland ecosystems and higher NDVI 
values for the perennial wetland samples composed by 
Phragmites australis, and Melaleuca glomerata. The distinct 
differences in NDVI of the different vegetation types evident 
were attributed to the contrasting canopy structure and 
growth patterns between the different communities (White et 
al, 2011). This difference between non spring-fed and 
wetland vegetation greeneess signal allows the establishment 
of a NDVI threshold value of 0.2, above which NDVI values 
are considered to be indicative of wetland vegetation. 
4.0 Temporal dynamics of wetland extent 
Our study confirms the potential of photosynthetic wetland 
vegetation as an indicator of volume of the spring flow 
(Fatchen, 2001; Fatchen and Fatchen, 1993; Mudd, 1998; 
White and Lewis, 2011; Williams and Holmes, 1978), as 
correlations are demonstrated between multi-annual mean 
extent of vegetated spring areas and groundwater discharges 
for one large spring at DSC (Figure 3b). The temporal 
frequency and archive of MODIS NDVI measurements allow 
us to demonstrate this relationship with more observations 
over a longer period than previous studies. 
   
Intern: 
Howeve 
controlle 
variabili 
historica 
variatior 
rain mea 
wetland 
monthly 
(Figure 
also pla 
wetland 
Therefor 
wetland 
longer c 
flow m 
studies 
strong b 
context 
White : 
wetland 
satellite 
of wetla 
50% (F 
over the 
2010), 1 
these re 
area, th 
increase 
While t| 
give pr 
objectis 
area, ai 
annual 
Observe 
phenolc 
differer 
trends « 
suggest 
a return 
MODIS 
with hi 
extende 
and tri 
imple 
variatic 
for thi 
manage 
thresho 
changii 
researc 
limits : 
will e 
dynam 
The ai 
NDVI 
Dalhot 
Result: 
DSC 1 
respon
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.