**8. Use of wireless sensors for supporting evapotranspiration measurements and smart management of irrigation demand**

for calculating each parameter can be found extensively in 'FAO Irrigation and Drainage pa‐ per No. 56' by FAO (1998). As in all ETc algorithms the final product is an ETc maps (Figure

11) of the area of interest where users can infer the ETc values for specific crops.

44 Remote Sensing of Environment: Integrated Approaches

**Figure 11.** ETc map of the area of interest (Landsat 7 TM image 2/1/2009) using P-M (Papadavid, 2011)

methodology for modeling crop parameters to satellite data.

**Table 3.** Crop Water Requirements for the different crops (m3/ha/month)

The results regarding crop water requirements of the different crops can be found on Table 3. The water needs for each crop is average value, for each month, based on the crop evapo‐ transpiration found employing the two algorithms described above, after applying the

**Crop J F M A M J J A S O N D Total** Potatoes 450 850 1200 1550 1300 5330 Ground nuts 620 1450 1650 300 4020 Beans 450 850 1200 990 3490 Chick peas 200 800 480 1480

Wireless sensors have been used in this study as an extra tool for supporting evapo‐ transpiration measurements in the same area of interest (Hadjimitsis et al., 2008a & 2008b). Such sensors were used as smart meteorological stations (relative humidity, tem‐ perature, wind speed) as well as tools for retrieving soil moisture, soil temperature leaves wetness and temperature. These information can be used to assess our evapo‐ transpiration results.

**Figure 12.** Wireless nodes in the Mandria area in Paphos (Papadavid, 2012)

The Wireless Sensor Network (WSN) consisted of a number of wireless nodes (near to 20 nodes) placed at various locations in the surrounding agriculture fields irrigated from the Asprokremmos Dam in Paphos District area in Cyprus (see Figure 12). The WSN acts as a wide area distributed data collection system deployed to collect and reliably transmit soil and air environmental data to a remote base-station hosted at Cyprus University of Technol‐ ogy (at the Remote Sensing Laboratory), as shown in Figure 13.

The micro-sensors were deployed using ad-hoc multi-hop communication protocol and transmit their data to a gateway which is responsible to collect, save and forward them to a remote database through a GPRS connection. The solar powered gateway, shown in Figure 14, was equipped with various meteorology sensors required to assist the indeed research project such as rain, wind, barometric pressure, temperature etc, which give ad‐ ditional information to the system. The gateway also hosts a GPS sensor for identifying the exact position of the WSN an event-driven smart camera for acquiring real-time pic‐ tures of the area and also a GPRS modem for communicating with the remote server which is deployed tens of thousands of kilometers away. The absence of power and com‐ munication infrastructure was tackled by creating a fully solar operated gateway (autono‐ my of three days without sunshine) and by incorporating a low power GPRS modem for communication. A multi-parameter decision system running on the remote server would be able to process the sensor data and produce valuable information about watering dif‐ ferent vegetables and create early notifications and suggestions which are then distribut‐ ed to farmers and water management authorities. The system was able to process multi parameter data collected from different sensors such as soil moisture, soil temperature (Figures 15 and 16), leaves wetness and temperature, humidity, rainfall, wind speed and direction and ambient light.

**Figure 14.** The WSN Gateway and Meteorology Station (Hadjimitsis et al., 2008a & 2008b)

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**Figure 15.** Soil moisture measurements using micro-sensor technology in agricultural field

**Figure 13.** Wirelesses Sensor Network Schema (Hadjimitsis et al., 2008a & 2008b)

Remote Sensing for Determining Evapotranspiration and Irrigation Demand for Annual Crops http://dx.doi.org/10.5772/39305 47

**Figure 14.** The WSN Gateway and Meteorology Station (Hadjimitsis et al., 2008a & 2008b)

to a remote database through a GPRS connection. The solar powered gateway, shown in Figure 14, was equipped with various meteorology sensors required to assist the indeed research project such as rain, wind, barometric pressure, temperature etc, which give ad‐ ditional information to the system. The gateway also hosts a GPS sensor for identifying the exact position of the WSN an event-driven smart camera for acquiring real-time pic‐ tures of the area and also a GPRS modem for communicating with the remote server which is deployed tens of thousands of kilometers away. The absence of power and com‐ munication infrastructure was tackled by creating a fully solar operated gateway (autono‐ my of three days without sunshine) and by incorporating a low power GPRS modem for communication. A multi-parameter decision system running on the remote server would be able to process the sensor data and produce valuable information about watering dif‐ ferent vegetables and create early notifications and suggestions which are then distribut‐ ed to farmers and water management authorities. The system was able to process multi parameter data collected from different sensors such as soil moisture, soil temperature (Figures 15 and 16), leaves wetness and temperature, humidity, rainfall, wind speed and

direction and ambient light.

46 Remote Sensing of Environment: Integrated Approaches

**Figure 13.** Wirelesses Sensor Network Schema (Hadjimitsis et al., 2008a & 2008b)

**Figure 15.** Soil moisture measurements using micro-sensor technology in agricultural field

High spatial resolution of water management information (approx. 30 m x 30 m using Land‐ sat 5) allows farmers to better manage spatial variability to maximise production, minimise

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As a key component in water resources management, it is essential to estimate evapo‐ transpiration accurately for water resources evaluation, drought monitoring and crop pro‐ duction simulation. Accurate estimates of ETc are needed for numerous agricultural and natural resource management procedures. However, this is difficult to achieve in practice because actual evapotranspiration cannot be measured directly and varies considerably in

Satellite images are collected across Mediterranean areas with frequencies ranging from dai‐ ly to monthly. The clear skies enable the gathering of good quality information and it is now possible to use satellite remote sensing to estimate the rates of ETc as shown in this chapter. Research has shown that there is a direct relationship between vegetation cover such as indi‐ ces and ETc. This means that the standard approach of using static crop water requirement look-up tables can be improved by using the more dynamic and customised information provided by satellite imagery. Satellite Remote sensing can assist in improving the estima‐ tion of ETc, and consequently water demand in cultivated areas for irrigation purposes and

In this Chapter remotely sensed data along with meteorological data, modeling techni‐ ques and surface energy balance algorithms were combined. All these procedures com‐ bined can provide the spatial distribution of ETc in maps where users can derive the value of ETc for each crop in mm/day. The methodology followed can be applied for any place since it can be considered as 'algorithm adaptation' to local conditions. The parameters that are required in the empirical equations can be easily evaluated using re‐ mote sensing techniques and field spectroscopy. Modeling techniques (for example, re‐ gression analysis) are used to correlate and evaluate measured crop canopy factors, such as Leaf Are Index (LAI) and Crop Height (CH), to remotely sensed data uring the entire phenological cycle of each crop. The intention is to create semi-empirical models describ‐ ing LAI and CH, which are indispensible parameters in almost all ETc algorithms, using remotely sensed data. Using these models, users can avoid direct measurements of these

The methodology as described in this chapter can support decision makers of Water Au‐ thorities. The methodology was applied for Landsats' images but it can easily be adapted for other satellite sensors. The use of field-spectroradiometer can facilitate the procedure since it provides a spectrum which can be adapted to satellites' bands by simple transformation, us‐

parameters every time there is an application of an ETc algorithm.

ing relative spectral response (RSR) filters of each satellite.

costs and environmental impacts.

**10. Concluding remarks**

sustainable water resources management.

time and space.

**Figure 16.** Temperature measurements coming from MSN.

#### **9. Smart management of evapotranspiration using 3G telephony**

As ETc is calculated each night based on that day's both weather readings and satellite images using the previously described method, the ETc results from these calculations are sent to farmers each morning giving them the water balance (Crop water require‐ ments) for their area for the irrigation season until the previous day. Using the existing method by combining satellite-derived crop coefficients and the 3G telephony with SMS delivery service, now offers the potential to provide low cost, site specific and personal‐ ised (for crop type and management conditions) irrigation water management informa‐ tion to individual famers across an irrigation region (Papadavid et al., 2012). Automatically triggered text messages can be generated by server-based software that combine data and formatting and then send the message out to mobile phones via an In‐ ternet cellular network gateway services. 3G phones can not only send SMS but can also send extended multimedia.

High spatial resolution of water management information (approx. 30 m x 30 m using Land‐ sat 5) allows farmers to better manage spatial variability to maximise production, minimise costs and environmental impacts.
