Adaptation of SEBAL for estimating groundnuts evapotranspiration, in Cyprus

The imperative need for data on irrigation management in Cyprushas led to a turnoff regarding the method of collecting and analyzing irrigation management primary data. The time and money consuming direct measurements of evapotranspiration (ETc), such as Pan-evaporation methods, lysimeters and others, are substituted from efficient energy and hydrological models which are adapted to satellite data. Remote sensing methods are attractive to estimate ET as they cover large areas and can provide estimates at a very high resolution. Intensive field monitoring is also not required, although some ground-truth measurements can be helpful in interpreting the satellite images. More specific, for the purposes of this paper, modeling and remote sensing techniques were integrated for estimating actual evapotranspiration (ETa) for a local cultivation (groundnut – Arachis hypogaea, L.), that is cultivated only at the specific area of interest. Data for irrigation management exist for the specific cultivation, from the past, based on the Epan method. These data were used as the reference data for this study and compared to the results.  Surface Energy Balance Algorithm for Land (SEBAL) methodology was followed for the first time in Cyprus employing the essential adaptations for the local soil and meteorological conditions. Three plots, cultivated with groundnuts, were selected at the area of interest. The plots are located by the seaside or at very low elevation level, where groundnuts are usually cultivated due to the requirement for mild climate conditions and well-drained soils. Landsat 5 and 7 images were used to retrieve the needed spectral data. Maps of ETa were created using SEBAL model for the area of interest, while irrigation scheduling was provided for a more efficient irrigation management. The results have been compared to the results of the Epan method and FAO-56. The comparison has revealed that SEBAL provides accurate results.without any important statistical difference from the direct measurements of Epan results

Impact of atmospheric effects on crop yield modelling in Cyprus, using Landsat's satellite imagery and field spectroscopy

Remote sensing, as the tool for spatially continuous measurements has become a trend for estimating Crop Yield since economically efficient agricultural management is highly dependent on detailed temporal and spatial knowledge of the processes affecting physiological crop development. This paper aims at examining the use of field spectroscopy along with Landsat's satellite imagery in order to test the accuracy of raw satellite data and the impact of atmospheric effects on determining crop yield derived from models using remotely sensed data. The spectroradiometric retrieved Vegetation Indices(VI) of Durum wheat, is directly compared to the corresponding VI of Landsat 7 ETM+ and 8 OLI, sourcing from both atmospherically corrected and not corrected satellite images in order to test the effects of atmosphere upon them. Vegetation Indices are vital in the procedure for estimating Crop Yield since they are used in stochastic or empirical models for describing or predicting crop yield. Leaf Area Index, which is also inferred using VI, is also compared to the real values of LAI that are measured using the SunScan instrument, during the satellite's overpass. Crop Yield is finally determined using the Cyprus Agricultural Research Institute's Crop Yield model for Durum wheat, adapted to satellite data, and is used to examine the impact of atmospheric effects. The results have prevailed that if crop yield models using remote sensing imagery, do not apply atmospheric effects algorithms, then there is statistically significant difference in the prediction from the real yield and hence a significant error regarding the model. The study's goal is to illustrate the need of atmospheric effects removal on remotely sensed data especially for models using satellite images

Impact of atmospheric effects on crop yield modelling in Cyprus, using Landsat's satellite imagery and field spectroscopy

Remote sensing, as the tool for spatially continuous measurements has become a trend for estimating Crop Yield since economically efficient agricultural management is highly dependent on detailed temporal and spatial knowledge of the processes affecting physiological crop development. This paper aims at examining the use of field spectroscopy along with Landsat's satellite imagery in order to test the accuracy of raw satellite data and the impact of atmospheric effects on determining crop yield derived from models using remotely sensed data. The spectroradiometric retrieved Vegetation Indices(VI) of Durum wheat, is directly compared to the corresponding VI of Landsat 7 ETM+ and 8 OLI, sourcing from both atmospherically corrected and not corrected satellite images in order to test the effects of atmosphere upon them. Vegetation Indices are vital in the procedure for estimating Crop Yield since they are used in stochastic or empirical models for describing or predicting crop yield. Leaf Area Index, which is also inferred using VI, is also compared to the real values of LAI that are measured using the SunScan instrument, during the satellite's overpass. Crop Yield is finally determined using the Cyprus Agricultural Research Institute's Crop Yield model for Durum wheat, adapted to satellite data, and is used to examine the impact of atmospheric effects. The results have prevailed that if crop yield models using remote sensing imagery, do not apply atmospheric effects algorithms, then there is statistically significant difference in the prediction from the real yield and hence a significant error regarding the model. The study's goal is to illustrate the need of atmospheric effects removal on remotely sensed data especially for models using satellite images

Remote sensing for determining evapotranspiration and irrigation demand for annual crops

Author Information Show + 1. Introduction Evapotranspiration (ETc) is the mean for exploiting irrigation water and constitutes a major component of the hydrological cycle (Telis et al., 2007; Papadavid, 2011). The ETc is a basic and crucial parameter for climate studies, weather forecasts and weather modeling, hydrological surveys, ecological monitoring and water resource management (Hoedjes et al., 2008). In the past decades, the estimation of ETc combining conventional meteorological ground measurements with remotely-sensed data, has been widely studied and several methods have been developed for this purpose (Tsouni, 2003). For hydrological resources management and irrigation scheduling, an accurate estimation of the ETc is necessary to be considered (Hoedjes et al., 2008 ; Papadavid et al., 2011). Crop evapotranspiration rate is highly important in various areas of the agricultural sector such as for identification of crop stress, water deficiency, for estimating the exact potential needs of crops for best yields. It is well accepted that water depletion methods, such as lysimeters, are the most accurate methods for estimating ETc. Methods that use meteorological parameters in order to estimate the ETc of different crops are well established and used by various studies (Telis et al., 2007; Rogers et al., 2007). A number of semi-empirical methods have been also developed in order to estimate the evapotranspiration from different climatic variables (Courault et al., 2005). Remotely sensed reflectance values can be used in combination with other detailed information for estimating ETc of different crops. Indeed, the potentiality of remote sensing techniques in ETc estimation and water resource management has been widely acknowledged (Papadavid et al., 2010). The possibility for monitoring irrigation demand from space is an important factor and tool for policy makers. It has been found that saving irrigation water through remote sensing techniques could diminish farm irrigation cost which reaches 25% of the total costs and increases the margin of net profit (Papadavid et al., 2011). Several researchers such as D’Urso et al., (1992), Bastiaanssen (2000), Ambast et al., (2006) and Papadavid et al., (2011) have highlighted the potentiality of multispectral satellite images for the appraisal of irrigation management. The integration of remotely sensed data with auxiliary ground truth data for obtaining better results is common in the literature. (Bastiaanssen et al., 2003; Ambast et al., 2006; Minaccapili et al., 2008). Ambast et al., (2006) have shown that the application of remote sensing data in irrigation is of high importance because it supports management of irrigation and is a powerful tool in the hands of policy makers. It has been found that research in ETc is directed towards energy balance algorithms that use remote sensing directly to calculate input parameters and, by combining empirical relationships to physical models, to estimate the energy budget components (Minaccapili et al., 2008; Papadavid et al., 2010; Papadavid et al., 2011). All the remote sensing models of this category are characterized by several approximations and need detailed experimental validations. Multispectral images are used to infer ETc, which is the main input for water balance methods-models. For estimations of ET, ground truth data (Leaf Area Index-LAI, crop height) and meteorological data (air temperature, wind speed, humidity) is needed to support this approach. In nearly every application of water balance model, knowledge of spatial variations in meteorological conditions is needed (Moran et al., 1997). The use of remote sensed data is very useful for the deployment of water strategies since it can offer a huge amount of information in short time, compared to conventional methods. Besides convenience and time reducing, remotely sensed data lessens the costs for data acquisition, especially when the area is extended (Thiruvengadachari et al., 1997). Although remote sensing based ETc models have been shown to have the potential to accurately estimate regional ETc, there are opportunities to further improve these models testing the equations used to estimate LAI and crop height for their accuracy under current agro-meteorological and soil conditions. This Chapter discusses the implementation of the most widely used models for estimating ETc, the ‘SEBAL’ and ‘Penman-Monteith’ which are used with satellite data. Such models are employed and modified, with semi-emprical models regarding crop canopy factors, to estimate accurately ETc for specific crops in the Cyprus area under local conditions. Crop Water Requirements have been determined based on the evapotranspiration values

Introduction

Proceedings of SPIE - The International Society for Optical Engineering Volume 9688, 2016, Article number 968801, Pages xvii-xvii

Proceedings of SPIE - The International Society for Optical Engineering: Introduction

This PDF file contains the front matter associated with SPIE Proceedings Volume 9535, including the Title Page, Copyright information, Table of Contents, Introduction, Authors, and Conference Committee listing

Introduction

Proceedings of SPIE - The International Society for Optical Engineering Volume 9229, 2014, Article number 922901, Pages x

Proceedings of SPIE - The International Society for Optical Engineering: Introduction

This PDF file contains the front matter associated with SPIE Proceedings Volume 9535, including the Title Page, Copyright information, Table of Contents, Introduction, Authors, and Conference Committee listing

Using SEBAL to Investigate How Variations in Climate Impact on Crop Evapotranspiration

Water allocation to crops, and especially to the most water intensive ones, has always been of great importance in agricultural processes. Deficit or excessive irrigation could create either crop health-related problems or water over-consumption, respectively. The latter could lead to groundwater depletion and deterioration of its quality through deep percolation of agrichemical residuals. In this context, and under the current conditions where Cyprus is facing effects of possible climate changes, the purpose of this study seeks to estimate the needed crop water requirements of the past (1995-2004) and the corresponding ones of the present (2005-2015) in order to test if there were any significant changes regarding the crop water requirements of the most water-intensive trees in Cyprus. The Mediterranean region has been identified as the region that will suffer the most from variations of climate. Thus the paper refers to effects of these variations on crop evapotranspiration (ETc) using remotely-sensed data from Landsat TM/ETM+/OLI employing a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). Though the general feeling is that of changes on climate will consequently affect ETc, our results indicate that there is no significant effect of climate variation on crop evapotranspiration, despite the fact that some climatic factors have changed. Applying Student's t-test, the mean values for the most water-intensive trees in Cyprus of the 1994-2004 decade have shown no statistical difference from the mean values of 2005-2015 for all the cases, concluding that the climate change taking place in the past decades in Cyprus have either not affected the crop evapotranspiration or the crops have managed to adapt to the new environmental conditions through time

Detection of archaeological crop marks in Cyprus using vegetation indices from Landsat TM/ETM+ satellite images and field spectroscopy measurements

Archaeological remains can be detected using crop marks, during different periods of crop cycle. Vegetation indices and spectral signatures can be used in order to examine and evaluate such crop marks. This paper presents the methodology applied for detecting crop marks over an archaeological site of Cyprus using Landsat TM/ETM+ satellite images. Moreover the GER1500 spectro-radiometer was used to retrieve in-situ spectral signatures over the area of interest (Kouklia Village in Paphos Cyprus). The results found are characterizing very promising since crop marks were identified as spectral anomalies. This paper aims to record the phenological cycle of barley crops, over agricultural fields in which archaeological areas existed and areas where only healthy agricultural fields are presented. NDVI values from the available satellite images (Landsat TM and Landsat ETM+) are used to plot the life cycle of barley crops. For the area in which archeological crop marks were found, the NDVI plot is significantly differs from one non-stressed crop. Such area covered by barley crop has been recently excavated (summer 2010) and the excavations have verified some linear buried archaeological remains -probably houses- just 30cm below ground surfac