Safwat H. Shakir Hanna

Earthworm survival in oil contaminated soil

Earthworms are an important component of the soil biota and their response to oil pollution needs to be better understood. Laboratory investigations were undertaken to determine the concentrations of crude oil in soil that leads to death of Lumbricus terrestris and Eisenia fetida and to determine the propensity of L. terrestris to move away from contaminated soil. Clemville sandy clay loam was amended to contain maximum oil contents of 1.5 – 2.5% depending on the particular experiment. Additionally, the ability of L. terrestristo survive in bioremediated oil-contaminated soil was evaluated. An oil content of 0.5% was not harmful to survival of earthworms for 7 d but an oil concentration of 1.5% reduced survival to less than 40%. Bioremediated soil containing 1.2% oil did not reduce survival of L. terrestrisduring 10 d. Survival of L. terrestrisin unweathered oil was improved when free movement between contaminated and uncontaminated soil was possible. Casts of earthworms exposed to oil-containing soil contained 0.2% total petroleum hydrocarbons. An allowable regulatory level of 1% oil contamination in soil may not allow for survival of earthworms.

Modeling and Evaluating the Global Energy Flow in Ecosystems and its Impacts on the Ecological Footprint

Abstract Energy is the source of the cycling in the global Earth ecosystems. Without it, the Earth will not be able to function to provide goods and services. While matter can be recycled in ecosystems essentially endlessly, energy can be used only once for each new cycle. In the Earth’s ecosystems, the two fundamental laws are the cycling of matter and the one-way flow of energy. Because the global ecological footprint and the demand for energy are rising, the impact of energy availability is of crucial importance and energy needs across the globe are not assured. What are the impacts of a continuously escalating demand for energy on the global ecosystem? The global ecosystem is the part of the Earth that assures the maintenance of production of natural resources that provide survivability of the global biological and human social systems. The modeling of energy in the global ecosystem will provide the scientific analysis that might be of interest to the global use of energy. In this respect, the energy enters an ecosystem through green plants (the producers) converting low-energy carbon dioxide into high-energy carbohydrate, then passes through one or more of the organisms (consumers and decomposers) of the community, and is then lost to the ecosystem into outer space and never returns; each new day needs the Sun to shine. Eventually, all the energy that enters the ecosystem is lost in the form of dissipated heat. Almost every aspect of life, and particularly human food production, is facing shortages. The Global Energy Model (GEM) in its theoretical approach has been developed using different time series of published data that are available on the websites of Earth-Trends of the World Research Institute (WRI), World Bank, Food and Agricultural Organization (FAO), United Nation Development Program, World Wildlife Fund (WWF), and Global Footprint Network. The data were incorporated into STELLA Modeling Tool using the fourth-order Runge–Kutta integration method. Further, the model incorporated the estimated density of power (in watts per square meter) received from the Sun from which we could calculate the energy reservoir on the Earth globally. The model provides the energy balance in the global ecosystems in light of the increase of human population. Accordingly, the human population is expected to reach 9.3 billion people by 2050 on the Earth and might reach between 11.0, 18.1, and 20.1 billion people in the year 2100 based on the very conservative estimates, the current trends of the estimates, and also the upper estimates. Additionally, the current needs of the human footprint for goods and services, including the energy from the Earth, are three to five times the current Earth size. The impacts of increasing human population will occur all along the energy chain from exploration, to production, distribution, and use. Ecosystems that are negatively affected by shifts in energy systems, for example, toward more intensive cropping for biofuels, may not be able to provide the range of goods and services, which they currently provide or potentially could provide. Changes in ecosystem services will affect the provisioning of goods and services further, impacting people, particularly those who rely directly on nature for their livelihoods. Further, climatic changes may have other impacts on establishing the links between ecosystem services, energy provision, human population by looking at the current status of ecosystems that directly provide energy services, anticipated demand for energy (production, distribution, consumption) and the key elements that impact the management of ecosystem services and related energy systems, as well as how climate-change impacts may change or shift energy demand and adaptation measures to be adopted globally.

Spectral Characterization of Water Stress Impact on Some Agricultural Crops: III. Studies on Sudan Grass and other Different Crops Using Handheld Radiometer

Vegetation monitoring has been one of the major targets of remote sensing studies. Remotely sensed reflectance concerning the impact of environmental factors upon crop vegetative cover can be predicted from two combinations of spectral bands as a ratio or as normalized vegetation indices. The most common spectral bands used lie in the red and infrared region (350 - 800 nm) and are dominated by the absorption of chlorophyll and other accessory pigments. In addition, reflectance in the middle infrared is dominated by absorption from liquid water contained in plants tissues. The objectives of the present work are: (1) to evaluate the reflectance data from frequently irrigated and water stressed Sudan grass and other crops using a handheld radiometer and assess the spectral correlation with the ground-truth; (2) to evaluate the applications of a Hyperspectral Structure Component Index (HSCI) developed by Shakir and Girmay-Gwahid in 1998; and (3) to evaluate the application of Index of Relative Stress (IRS) proposed by Shakir and Girmay-Gwahid in 1998. The experiment was designed to collect reflectance data from Sudan grass and other crops planted at the Blythe Research Station, California in rows. The size of the plots for Sudan grass was in rows, the unstressed mature stands were 9 feet tall, and the stressed mature stands were 5 feet tall. The other fields are in nearby and planted with cotton crops in different stages of maturity. With a field spectrometer, the scan over each treatment was made at 1-hr intervals between 10:00 a.m. and 2:00 p.m. Pacific DayTime (PDT). Vegetative samples were taken from the two treatments during the initial sampling for purposes of conducting chemical analysis. Soil samples were collected to determine the amount of available soil moisture differences in the two treatments. The results of this experiment showed that in the 850 - 1150 nm wavelength ranges, the stressed Sudan grass stands showed lower reflectance than unstressed stands. However, the reflectance of stressed Sudan grass stands was higher than the unstressed stands above the 1150 nm. This is probably due to the absorption from liquid water contained in the unstressed plant tissues. The same pattern was found in the cotton crop. The analysis of data using the (HSCI) model showed that the stressed Sudan grass stands have values less than 1 and under unstressed Sudan grass stands have the value greater than 1. This means that the model is differentiating between the stressed and unstressed vegetation. Additional work will evaluate the reflectance peaks and their relationship to other parameters that were collected and are relevant to the applications of the model. Furthermore; the Index of Relative Stress (IRS) showed that the unstressed vegetation stands is higher in values than in the stressed.

Spectral characterization of water stress impact on some agricultural crops: II. Studies on alfalfa using handheld radiometer

Remotely sensed reflectance from stressed and non-stressed crop vegetative cover can be predicted from two combination of spectral bands as a ratio or as normalized vegetation indices. The most common spectral bands used lie in the red and infrared region (350 - 800 nm) and are dominated by the absorption of chlorophyll and other accessory pigments. In addition, reflectance in the middle infrared is dominated by absorption from liquid water contained in plants tissues. The objectives of the present work are: (1) to evaluate the reflectance data from frequently irrigated and water stressed alfalfa using a handheld radiometer and assess the spectral correlation with the ground-truth and; (2) to evaluate the applications of a Hyperspectral Structure Component Index (HSCI) proposed by Shakir and Girmay-Gwahid (1998). The experiment was designed to collect reflectance data from alfalfa (pure alfalfa stand and a plot where alfalfa was mixed with sedge grass) planted at the Blythe Research Station, California. The size of the plots was 30 X 50 ft2. With a field spectrometer, the scan over each treatment was made at 1 hr intervals between 10:00 a.m. and 2:00 p.m. Pacific Day Time (PDT). Vegetative samples were taken from the two treatments during the initial sampling for purposes of conducting chemical analysis. Soil samples were collected to determine the amount of available soil moisture differences in the two treatments. The results of this experiment showed that in the 850 - 1150 nm wavelength range the stressed alfalfa plots showed lower reflectance than unstressed plots. However; the reflectance of stressed alfalfa was higher than the unstressed stands above the 1150 nm. This is probably due to the absorption from liquid water contained in the unstressed plant tissues. The analysis of data using the (HSCI) model showed that the stressed pure alfalfa plots have values less than 1 and under unstressed alfalfa plots have the value greater than 1. This means that the model is differentiating between the stressed and unstressed vegetation. Additional work will evaluate the reflectance peaks and their relationship to other parameters that were collected and are relevant to the applications of the model.

Characterization model for crop stress using hand-held radiometer data

Remotely sensed reflectance from stressed and non-stressed crop vegetative cover can be predicted from two combinations of spectral bands as a ratio or as normalized vegetation indices. The most common spectral bands used lie in the red and infrared region (350-800 nm) and are dominated by the absorption of chlorophyll and other accessory pigments. In addition, reflectance in the middle infrared is dominated by absorption from liquid water contained in plants tissues. The objectives of the present work are: 1) to develop characterization model to evaluate the reflectance data from frequently irrigated and water stressed alfalfa, Sudan grass, and other crops such cotton as using a handheld radiometer and assess the spectral correlation with the ground-truth and; 2) The model will be better model to evaluate the stressed crops. The experiment was designed to collect reflectance data from cotton crops planted at the Blythe area, California. The fields are planted with cotton crops in different stages of maturity at Longitude of -1 14°32.79 and -1 14°32.80 and Latitude 33° 39.64. With a field spectrometer, the scan over each treatment was made at 1 hr intervals between 10:00 a.m. and 2:00 p.m. Pacific Day Time (PDT). Vegetative samples were taken from the two treatments (i.e. stressed and unstressed vegetation) during the initial sampling for purposes of conducting chemical analysis. Soil samples were collected to determine the amount of available soil moisture differences in the two treatments.Remotely sensed reflectance from stressed and non-stressed crop vegetative cover can be predicted from two combinations of spectral bands as a ratio or as normalized vegetation indices. The most common spectral bands used lie in the red and infrared region (350-800 nm) and are dominated by the absorption of chlorophyll and other accessory pigments. In addition, reflectance in the middle infrared is dominated by absorption from liquid water contained in plant’s tissues. The objectives of the present work are: 1) to develop characterization model to evaluate the reflectance data from frequently irrigated and water stressed alfalfa, Sudan grass, and other crops such cotton as using a handheld radiometer and assess the spectral correlation with the ground-truth and; 2) The model will be better model to evaluate the stressed crops. The experiment was designed to collect reflectance data from cotton crops planted at the Blythe area, California. The fields are planted with cotton crops in different stages of maturity at Longitude of -114°32.79 and -114°32.80 and Latitude 33° 39.64. With a field spectrometer, the scan over each treatment was made at 1 hr intervals between 10:00 a.m. and 2:00 p.m. Pacific Day Time (PDT). Vegetative samples were taken from the two treatments (i.e. stressed and unstressed vegetation) during the initial sampling for purposes of conducting chemical analysis. Soil samples were collected to determine the amount of available soil moisture differences in the two treatments. The suggested model in the present paper is called the Model of Water Stress (MWS) where it include in it the statistical values and parameters, indicates that the stressed crops have values higher than unstressed crops in MWS scale. This means that the model is differentiating between the stressed and unstressed vegetation. Additional work will evaluate the reflectance peaks and their relationship to other parameters that were collected and are relevant to the applications of the model. The model will be tested against the AVIRIS data that were collected at the same time of the collection of ground-truth data.

Lifestyles and internet: a new pathway for well-being sustainability

Highlighting the important role that the lifestyles can play for the pursuing of the well-being sustainability, this article focuses on the internet as a fundamental tool for the promotion of sustainable behavioural models. In particular, the internet plays a fundamental role in determining the so-called Sustainability Empowerment because it can improve the reference to a sustainable food lifestyle, guiding the visitors, for example, to new patterns of food behaviour most functional to the maintenance of their health, of the environment or economically more convenient.

Characteristics of AVIRIS bands measurements in agricultural crops at Blythe area, California: V. studies on alfalfa spectral data

The present study is focusing on the following main objectives that are: 1) to compare the spectral and radiometric characteristics of AVIRIS data from Alfalfa crops with the spectra measured by FieldSpecR ASD radiometer; 2) to study the impact of growth regulators that applied on alfalfa in comparison of data collected from AVIRIS seen and; 3) to build a spectral library for the alfalfa crop that exposed to growth regulators that were studied. AVIRIS data from Blythe were acquired in June 1997 to study the agricultural spectra from different crops and for identification of crops in other areas with similar environmental factors and similar spectral properties. On June 26-28, 2001 spectra were collected from Alfalfa fields using the FieldSpecR ASD spectrometer at Blythe area, California (at the 114o 33.52 W Longitude and 33o 39.76 N Latitude to Longitude 114o 33.54 W and Latitude 33 39.88 N). The alfalfa crop fields were treated with different chemicals of growth regulators. These growth regulators were AuxiGro, Apogee and Messenger. These chemicals were used in different concentrations. Environmental parameters were studied such as the soil water content (WC), pH, and organic matter (OM). The results of this study showed that there is a significant correlation between the data that were collected by AVIRIS image scene in 1997 and spectral data collected by the FieldSpec spectrometer in the same places that were scanned by AVIRIS. This correlation allowed us to build a spectral library to be used in ENVI-IDL software. Furthermore, using IDL algorithms of Spectral Angle Mapper classification (SAM), Spectral Feature Fitting (SFF) and Spectral Binary Encoding (SPE) showed an excellent agreement between the traced spectra from the AVIRIS image and the spectral radiometer data collected from the alfalfa crops treated with growth regulators (i.e. the correlation is between 75 - 94% match). Three widely used vegetation indices such as NDVI, WBI, and PRI, showed that there are significant correlations between WBI and NDVI (r2= 0.44 - 0.88 for alfalfa crops treated by growth regulators. Further use of the AVIRIS images can be of a value to crops identification or crops yield for commercial use.

Characteristics of AVIRIS bands measurements in agricultural: crops at Blythe Area, California: IV: studies on cotton varieties spectral data

AVIRIS data from Blythe were acquired in June 1997 to study the agricultural spectra from different crops and for identification of crops in other areas with similar environmental factors and similar spectral properties. The main objectives of this study are: 1) to compare the spectral and radiometric characteristics of AVIRIS data from verities of cotton crop with the spectra measured by FieldSpecR ASD radiometer; 2) to explore the use of AVIRIS images in identifying agricultural crops; 3) to study the impact of environmental factors on selected crops and; 4) to build a spectral library for the cotton crop varieties that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth or different varieties. In order to support our study, on June 26, 2001 we collected spectral data using the FieldSpec spectrometer from selected fields planted with different cotton varieties at Blythe area, California (at the Longitude 114° 41.88 W and Latitude 33° 24.27N to Longitude 114° 41.86 W and Latitude 33° 24.00N). The spectral data of cotton varieties were studied. Environmental parameters were studied such as the soil water content (WC), pH, organic matter (OM), C% and nitrogen (N%). The results of this study showed that there were differences in the signatures of different cotton varieties. Also, there was a significant correlation between the data that were collected by AVIRIS image scene in 1997 and spectral data collected by the FieldSpec spectrometer. This correlation allowed us to build a spectral library to be used in ENVI-IDL software. This leads to identification of different cotton varieties and in particular the visible part of the spectra. AVIRIS data are in agreement with FieldSpec data. Using IDL algorithms of Spectral Angle Mapper classification (SAM), Spectral Feature Fitting (SFF) and Spectral Binary Encoding (SPE) showed that there is an excellent agreement between the predicted and the actual crop type (i.e. the correlation is between 85 - 90% match). Further use of the AVIRIS images can be of a value to crops identification or crops yield for commercial use. The yield data of Cotton varieties were correlated significantly with the spectral data from the AVIRIS and from the hand-held radiometer and it showed the impact of different environmental parameters on the yield of the crop.

Characteristics of AVIRIS bands measurements in agricultural crops at Blythe area, California: III. Studies on Teff Grass

AVIRIS data from Blythe were acquired in June 1997 to study the agricultural spectra from different crops and for identification of crops in other areas with similar environmental factors and similar spectral properties. In this respect; the main objectives of this study are: 1) to compare the spectral and radiometric characteristics of AVIRIS data from agriculture crops with the spectra measured by FieldSpec ASD radiometer; 2) to explore the use of AVIRIS images in identifying agricultural crops; 3) to study the impact of environmental factors on selected crops and; 4) to build a spectral library for the crops that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth. In order to support our study, on July 18-19, 2000 we collected spectra using the FieldSpec spectrometer from selected fields planted with different crops at Blythe area, California (at the Longitude 114° 33.28 W and Latitude 33° 25.42 N to Longitude of 114° 44.53 W and 33° 39.77 N Latitude. The teff grass spectra were studied. Teff grass fields were treated with different types of irrigation (i.e. wet to dry conditions). Additional parameters were studied such as the soil water content (WC), pH, organic matter (OM) and nitrogen (N%). The results of this study showed that there is a significant correlation between the data that were collected by AVIRIS image scene in 1997 and spectral data collected by the FieldSpec spectrometer. This correlation allowed us to build a spectral library to be used in ENVI-IDL software. This leads to identification of different crops and in particular the visible part of the spectra. AVIRIS data are in agreement with FieldSpec data. Using IDL algorithms of Spectral Angle Mapper classification (SAM), Spectral Feature Fitting (SFF) and Spectral Binary Encoding (SPE) showed that there is an excellent agreement between the predicted and the actual crop type (i.e. the correlation is between 85 - 90% match). Further use of the AVIRIS images can be of a value to crops identification or crops yield for commercial use. The yield data of Teff grass were correlated significantly with the spectral data from the AVIRIS and from the hand-held radiometer and it showed the impact of irrigation on the yield of the crop.

Characteristics of AVIRIS Bands Measurements in Agricultural Crops at Blythe Area, California: II. Studies on Kenaf, Hibiscus canabinus

AVIRIS data from Blythe,Calfornia , were acquired in June 1997 to study the agricultural spectra from different crops and for identification of crops in other areas with similar environmental factors and similar spectral properties. In this respect; the main objectives of this study are: 1) to compare the spectral and radiometric characteristics of AVIRIS data from agriculture crops with the spectra measured by FieldSpecR ASD radiometer; 2) to explore the use of AVIRIS images in identifying agriculture crops; and; 3) to build a spectral library for the crops that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth. In order to support our study, on July 18-19, 2000 we collected spectra using the FieldSpecR ASD spectrometer from selected fields planted with different crops at Blythe area, California (at the Longitude 114 degree(s) 33.28 W and Latitude 33 degree(s) 25.42 N to Longitude 114 degree(s) 44.35 W and 33 degree(s) 39.77 N Latitude). The results of this study showed that there is a significant correlation between the data that were collected by AVIRIS image scene in 1997 and spectral data collected by the FieldSpecR spectrometer. This correlation allowed us to build a spectral library to be used in ENVI_IDL software. This leads to identification of different crops and in particular the visible part of the spectra. Furthermore, using IDL-ENVI algorithms of Spectral Angle Mapper classification (SAM), Spectral Feature Fitting (SFF) and Spectral Binary Encoding (SPE) showed that there is an excellent agreement between the predicted and the actual crop type (i.e. The correlation is between 85-90% match). Further use of the AVIRIS images can be of a value to crops identification or crops yield for commercial use. Kenaf crop spectra were studied. The kenaf varieties (Tainung 2, Everglades 41) were significantly differentiated by both the spectral data from AVIRIS and from the hand-held radiometer.