The growth rate monitoring of crops throughout their biological cycle is very important as it contributes to the
achievement of a uniformly optimum production, a proper harvest planning, and reliable yield estimation. Fertilizer
application often dramatically increases crop yields, but it is necessary to find out which is the ideal amount that has to
be applied in the field. Remote sensing collects spatially dense information that may contribute to, or provide feedback
about, fertilization management decisions. There is a potential goal to accurately predict the amount of fertilizer needed
so as to attain an ideal crop yield without excessive use of fertilizers cause financial loss and negative environmental
impacts.
The comparison of the reflectance values at different wavelengths, utilizing suitable vegetation indices, is commonly
used to determine plant vigor and growth. Unmanned Aerial Vehicles (UAVs) have several advantages; because they can
be deployed quickly and repeatedly, they are flexible regarding flying height and timing of missions, and they can obtain
very high-resolution imagery. In an experimental crop field in Eleftherio Larissa, Greece, different dose of pre-plant and
in-season fertilization was applied in 27 plots. A total of 102 aerial photos in two flights were taken using an Unmanned
Aerial Vehicle based on the scheduled fertilization.
Α correlation of experimental fertilization with the change of vegetation indices values and with the increase of the
vegetation cover rate during those days was made. The results of the analysis provide useful information regarding the
vigor and crop growth rate performance of various doses of fertilization.
Water allocation to crops has always been of great importance in agricultural process. In this context, and under the current conditions, where Cyprus is facing a severe drought the last five years, purpose of this study is basically to estimate the needed crop water requirements for supporting irrigation management and monitoring irrigation on a systematic basis for Cyprus using remote sensing techniques. The use of satellite images supported by ground measurements has provided quite accurate results. Intended purpose of this paper is to estimate the Evapotranspiration (ET) of specific crops which is the basis for irrigation scheduling and establish a procedure for monitoring and managing irrigation water over Cyprus, using remotely sensed data from Landsat TM/ ETM+ and a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). The methodology set in this paper refers to COST action ES1106 (Agri-Wat) for determining crop water requirements as part of the water footprint and virtual water-trade.
Accurate assessment of water use is an important issue in a globally changing climate and environment, where water is
becoming a scarce but essential resource. The concept ‘Water Footprint’ (WF) of a crop is defined as the volume of
water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. This
indicator provides valuable information for a global assessment of how water resources are used. Remote sensing (RS)
provides physically-based, worldwide, and consistent spatial information over space and time, and has been used in
hydrological applications in order to estimate relevant variables at different temporal and spatial scales. The paper
focuses on exploring and exploiting the potential of using RS techniques and data for WF assessment in agriculture.
Based on recent papers initiated in this research topic the investigation focuses on how variables needed in the
calculation of water footprint are obtained (based on non RS and on RS approaches), on identifying the inputs required
for estimating the WF of crops and whether it is feasible to integrate various RS approaches. The results of this study
demonstrate the usefulness of satellite data for water footprint assessment, which were obtained by the Remote Sensing
Working Group in the framework of the ESSEM COST Action ES1106, “Assessment of EUROpean AGRIculture
WATer use and trade under climate change” (EURO-AGRIWAT).
The objective of this work is the investigation of the specific relationships between actual evapotranspiration based crop coefficients and vegetation indices adapted to Karla Watershed, central Greece. Surface Energy Balance Algorithm for Land (SEBAL) was used to derive monthly actual evapotranspiration (ET) and ETrF values during the growing season of 2012. The methodology was developed using medium resolution Landsat 7 ETM+ images. Meteorological data from the archive of the Institute for Research and Technology, Thessaly (I.RE.TE.TH) have also been used. Fields with cotton, wheat, alfalfa, corn and sugar beets are utilized. During the same period, in-situ radiometric measurements were generated with the use of the field spectro-radiometer GER1500 giving specific spectral signatures for each crop. Filtering of reflectance values with the use of relative spectral responses (RSR) gives the opportunity to match the spectral measurements with Landsat ETM+ bands and compute VI like NDVI, SAVI, EVI and EVI2 using the same remote sensing formulas as the ETM+ conventional procedures. New relationships are derived and NDVI, SAVI, EVI and EVI2 are tested separately for each crop. Special attention is given to the constant L inside the SAVI relationship. The main advantage of the new approach is that is more crop specific and it less time consuming because there is no need for atmospheric correction.
Remote sensing technology has been widely used for monitoring water quality parameters such as suspended solids (turbidity), Secchi Disk, chlorophyll, and phosphorus. Suspended matter plays an important role in water quality management of several inland- (such as lakes and reservoirs) and coastal-water bodies and can be used to estimate the Trophic State Index of different water bodies. However synoptic information on water quality parameters at a systematic basis is difficult to be obtained from routine in situ monitoring programs since suspended matter, phosphorus, and chlorophyll are spatially inhomogeneous parameters. To meet this need, an integrated use of Landsat satellite images, in situ data and water quality models can be used. Several algorithms were developed at a previous stage using water quality data collected during the in situ sampling campaigns taken place in 2010 and 2011 over Asprokremmos Reservoir (Paphos District) for the assessment of turbidity, Secchi Disk, and Trophic State Index fluctuations using spectroradiometric data. Remotely sensed data were atmospherically corrected and water quality models for the estimation of both the turbidity- and Secchi Disk- concentrations were further calibrated using in situ data for the case of Asprokremmos Reservoir and several coastal over Cyprus coastline (Limassol and Paphos District Areas). This methodology can be used as a supporting monitoring tool for water management authorities “gaining” additional information regarding the spatial and temporal alterations of the turbidity- and Secchi Disk- concentrations and the Trophic State Index values over several Case II water bodies.
Satellite remote sensing techniques play an important role in crop identification, acreage and production estimation, disease and stress detection, and soil and water resources characterization because they provide spatially explicit information and access to remote locations. The main objective of the study is to highlight the potential of using remote sensing techniques in the research field of water management, especially for “water footprint” assessment. In this paper, several vegetation indices (NDVI, NDWI, etc) and biophysical variables (LAI, fAPAR) are key variables to potentially be estimated by remote sensing and used in water footprint studies. The combination of these input parameters brings several limitations regarding the discrepancies in temporal and spatial resolution and data availability, which are described and discussed in detail. MODIS, Landsat, SPOT Vegetation and Meteosat data were used in order to estimate evapotranspiration and vegetation indices. The results of this study show the usefulness of satellite data for water footprint assessment and were obtained by the Remote Sensing Working Group in the framework of the ESSEM COST Action ES1106, “Assessment of EUROpean AGRIculture WATer use and trade under climate change” (EUROAGRIWAT).
In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to derive daily actual evapotranspiration (ETa) distributions from Landsat and MODIS images separately. The study area is the Lake Karla basin in Thessaly, Central Greece. Meteorological data from the archive of Center for Research and Technology, Thessaly (CERETETH) have also been used. The methodology was developed using satellite and ground data for the period of summer 2007. Landsat and MODIS imagery were combined in order to have data with high temporal and spatial resolution (downscaling). The downscaling technique applied is the output downscaling with regression between images. This technique disaggregates imagery by applying linear regression between two MODIS products to the previous or subsequent Landsat product. After the calculation of a first order linear regression between two MODIS-derived ETa maps the next step is the regression to the ETa map derived from the prior Landsat image to predict the disaggregated subsequent Landsat ETa map. The results are satisfactory, giving the general trend of ETa derived from the original SEBAL procedure.
Remote sensing may be used for quick and cost effective detection and monitoring of water leakages, since traditional field survey methods for detection of water pipeline leakages are costly and time consuming. Vegetation indices are widely used by researchers for many applications. Among them, NDVI, RVI and SAVI are indices that can be used for pipeline leakage detection. In this study, the above vegetation indices were evaluated based on Landsat ETM+ multispectral images in a multi-temporal mode. The evaluation was performed in the semiarid environment in Cyprus, in order to detect the position of points/areas where water leakage occurs and to examine the accuracy of the vegetation indices in detecting such events. In addition, a low altitude system was used to record spectral differences before and after a leakage event. The results showed that there are leakage points that could be detected using satellite images due to the increasing and decreasing of the surrounding vegetation affected by the water leaked of the pipeline. Other characteristics such as the soil type and precipitation were also examined. Finally, the low altitude system highlighted the advantages of using such non contact techniques for monitoring water leakages.
Remote sensing (RS) has long been a useful tool in global and regional applications. The Water Footprint (WF) of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage. RS provides new tools for global WF assessment and represents an innovative approach to regional and global irrigation mapping, enabling the estimation of green and blue water use. This paper presents an overview of the EU COST Action ES 1106 "Assessment of European agriculture water use and trade under climate change (EURO-AGRIWAT)", regarding the evaluation of the potential of remote sensing to improve the WF and Virtual Water Trade (VWT) assessment. The main objective is the analysis of the role of satellite data in the suitable models and indices concerned with the analysis of WF and VWT. The main tasks include: an inventory of the existing and near future satellite data records for several European regions that could be used for the WF and VWT assessment; the study of satellite data resolution requirements, in time and space; the analysis of the assimilation of satellite data into models for the determination of green and blue water use; conclusions and recommendations concerning the possibility to integrate remote sensing into WF and VWT accounting. The combination of RS data to assess the volume of irrigation applied, and the green and blue WF faces several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which will be studied.
This paper aims to model leaf area index (LAI) and crop height to spectral vegetation indices (VI), such as normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), and weighted difference vegetation index (WDVI). The intended purpose is to create empirical statistical models to support evapotranspiration algorithms applied under the current conditions in the island of Cyprus. Indeed, a traditionally agricultural area was selected in the Mandria Village in the Paphos District area in Cyprus, where one of the island's main exported crops, potatoes, are cultivated. A GER-1500 field spectroradiometer was used in this study in order to retrieve the necessary spectrum data of the different crops for estimating the VI's. A field campaign was undertaken with spectral measurements of LAI and crop height using the Sun-Scan canopy analyzer, acquired simultaneously with the spectroradiometric measurements between March and April of 2008 and 2009. Regarding the measurements, the phenological cycle of potatoes was followed. Several regression models have been applied to relate LAI/crop height and the three indices. It was found that the best fitted vegetation index to both LAI and crop height was WDVI. When LAI was regressed against WDVI for potatoes, the determination coefficient (R2) was 0.72, while for crop height R2 reached 0.78. Two Landsat TM-5 images acquired simultaneously during the spectroradiometric and LAI and crop height measurements are used to validate the proposed regression model. From the whole analysis it was found that the modeled results are very close to real values. This fact enables the specific empirical models to be used in the future for hydrological purposes.
The use of satellite remote sensing for water quality monitoring in inland waters has substantial advantages over the insitu
sampling method since it provides the ability for overall area coverage and also for study and supervision of isolated
locations. The development of algorithms for water quality monitoring using satellite data and surface measurements can
be widely found in literature. Such algorithms require validation and one of the major problems faced during these
attempts was the need for continuous surface measurements requiring numerous in-situ samplings that imply also very
high costs due to the need of increased human labour. The development of an automatic and autonomous sensor system
able to be remotely controlled, will cover this gap and will allow the real time combined analysis of satellite and surface
data for the continuous monitoring of water quality in dams as well as the overall water resources management. Wireless
Sensor Networks (WSN) can provide continuous measurements of parameters taken from the field by deploying a lot of
wireless sensors to cover a specific geographical area. An innovative, energy-autonomous floating sensor platform
(buoy) transferring data via wireless network to a remote central database has been developed for this study which can be
applied on all dams in Cyprus. Indeed this project describes the results obtained by an existing running campaign in
which in-situ spectroradiometric (GER1500 field spectroradiometer) measurements, water sampling measurements
(turbidity), sensor measurements (turbidity) and Landsat TM/ETM+ data have been acquired at the Asprokremmos Dam
in Paphos (Cyprus). By applying several regression analyses between reflectance against turbidity for all the spectral
bands that correspond to Landsat TM/ETM+ 1-2-3-4, the highest correlation was found for TM band 3 (R2=0.83).
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 surface.
The monitoring of agricultural areas in Cyprus provides important data for efficient water supply plans and for avoiding
unnecessary water lost due to inefficient irrigation. In this context, satellite remote sensing techniques may be useful as
an efficient tool for monitoring agricultural areas. The objective of this study is to present the overall methodology for
monitoring agricultural areas and estimating the irrigation demand in Cyprus using satellite remote sensing, irrigation
models and other auxiliary data. Field spectro-radiometric measurements using SVC-HR 1024 and GER 1500 were
undertaken to determine the spectral signature of different types of crops so as to assist our classification techniques.
Final crop maps using Landsat TM and ETM+ can be produced and the optimal amount of irrigation demand required
for certain types of crops can be determined in order to avoid any non-effective water management. This paper presents
the overall methodology of the proposed research study designed to enable the implementation of an integrated approach
by combining satellite remote sensing, irrigation models, micro-sensor technology and in-situ spectroradiometric
measurements to determine the irrigation demand and finally to validate our results.
The aim of this study is the discrimination of the main cereals cultivated in Greece (namely soft and durum wheat, barley and oat), using spectral data. In a field experiment, the spectral response in the visible and the near infrared was measured over the above crops, during a 17-week period from early growth to harvesting, for five days a week. An 8-channel ground-based hand-held radiometer, with spectral wavelength range 500-850 nm, was used for the measurements of the spectral reflectance. The ratio vegetation index (RVI) and the normalised difference vegetation index (NDVI) values were also calculated, using all combinations between the near infrared and the visible bands. The results show that all reflectance values are developed in similar way, as canopy geometry was almost similar for all four crops. However, oat presents remarkable differences with regards to the three other crops, in bands 7 and 8. NDVI and RVI values for oat also present the same differences with respect to the rest crops and these differences are better distinguished in some of the studied weeks. A statistical analysis based on the above observations confirmed the significance of the differences of the spectral values between crop pairs, for only the first eight weeks of the studied period. Moreover, differences between the three other crops (soft and durum wheat and barley) are very small. For discrimination applications, the more bands available, the better the chances for detection and identification.
Dominique Medal, Jacques Stakenborg, Graham Russell, Frederic Biard, Dorothea Aifantopoulou, Marino Palacios, Jean Riglet, Leonidas Toulios, Miguel Soler, J. Masson
The goal of CALIS is to monitor vegetation condition and to evaluate the impact of climate hazards on both agriculture production and environment. CALIS will warn the end-users, e.g. insurance companies, when crop damage arises, and help them in evaluating compensation for farmers who have been hit. CALIS target calamities are: night frost in early spring, drought in late spring and early summer, heat excess. Impact of climate hazards on vegetation will be assessed through use of meteorological and Earth Observation satellite data, as well as complementary information such as agricultural statistics, tables of local phenological stages, and ground data measurements. A specific methodology has been set for each climatic hazard. The project has been very much a collaborative, interdisciplinary one. End-users have been responsible for defining the goals, selecting meteorological events and checking the results. Scientists provided expertise in selecting and tuning the methods, while value added companies brought their knowledge and experience in the thematic area to specify the system, to generate and interpret the products. Before the end of 1998, the system will be operational for assessing frost damage over the test sites (France, Greece and Spain).
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