In the
framework of the project work around the tree nursery in Schinznach, the water
balance is to be measured and assessed. Therefore, certain values must be
known, fortunately we already know some of the parameters of the water cycle. For
example, the exchange with groundwater can be neglected, as only a certain
quantity is taken and only something seeps away in the pond. Furthermore, there
is no inflow in the form of a stream. The water for irrigation is taken from
the groundwater and then preheated in the pond so that the plants do not get a
shock. Therefore, it is known how much water comes into the system "tree
nursery". What is not known is how much evaporates and how much remains in
the canopy of leaves. According to that the following research is based on the
question: Which remote sensing methods and indices are the easiest and most
effective for measuring evapotranspiration?
NDVI (normalized difference vegetation index) is one of the most commonly used applications for UAS(Xue & Su, 2017). NDVI is easy to use as there are very light and high-resolution cameras UAS can be equipped with. It is defined as:
Because of
the high reflectance of chlorophyll in the near infrared range this index is
used to detect the plants greenness and vegetation cover in certain areas. One
disadvantage of the NDVI is, that it doesn’t increase anymore above a certain
biomass level, which is why more sensitive VI’s where developed like the EVI
(enhanced vegetation index)(Xue & Su, 2017).
NDWI is a measure of
liquid water molecules in the vegetation that interacted with solar radiation(Gao, 1996). Therefore it can be used to measure water stress and
evaporation not only in the vegetation canopy but also in the soil in low depth(Nebo, Cesar &
Richard, 2014). The disadvantage is that many UAS are not equipped with the necessary
sensors and it can therefore not be used easily.
There are many more
indices which build on the concept of NDVI and improve it in terms of error
susceptibility and erroneous measurements, but they are all also a little more
complicated and elaborate to process. Therefore, I recommend the NDVI as an
index to measure the water balance in Schinznach. With the NDVI the vegetation
cover can be measured relatively easily. If you now know which kind of species the
vegetation consists of, you can find out how much this plant transpires and
calculate the transpiration rate. Since NDVI is sensitive to the effects of
soil brightness, soil colour, and leaf canopy shadow it needs to be calibrated
with ground data(Glenn, Huete, Nagler
& Nelson, 2008). To measure the evaporation, it would be useful to
see if it is possible to get satellite data for the region using NDWI.
Collecting our own data may turn out to be difficult because the necessary
sensors may not be available.
Sighted Literature:
Gao, B. (1996). NDWI—A
normalized difference water index for remote sensing of vegetation liquid water
from space. Remote Sensing of Environment, 58 (3), 257–266.
https://doi.org/10.1016/S0034-4257(96)00067-3
Glenn, E. P., Huete, A. R., Nagler, P. L. & Nelson, S. G. (2008).
Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and
Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us
About the Landscape. Sensors (Basel, Switzerland), 8 (4),
2136–2160.
Nebo, J., Cesar, G. & Richard, B. (2014, April). Validation of
remotely-sensed evapotranspiration and NDWI
using ground measurements at Riverlands, South Africa.
Xue, J. & Su, B. (2017). Significant Remote Sensing Vegetation
Indices: A Review of Developments and Applications. Journal of Sensors.
https://doi.org/10.1155/2017/1353691
