Fusion Landsat-8 Thermal TIRS and OLI Datasets for Superior Monitoring and Change Detection using Remote Sensing

Currently, updating the change detection (CD) of land use/land cover (LU/LC) geospatial information with high accuracy outcomes is important and very confusing with the different classification methods, datasets, satellite images, and ancillary dataset types available. However, using just the low spatial resolution visible bands of the remotely sensed images will not provide good information with high accuracy. Remotely sensed thermal data contains very valuable information to monitor and investigate the CD of the LU/LC. So, it needs to involve the thermal datasets for better outcomes. Fusion plays a big role to map the CD. Therefore, this study aims to find out a refining method for estimating the accurate CD method of the LU/LC patterns by investigating the integration of the effectiveness of the thermal satellite data with visible datasets by (a) adopting a noise removal model, (b) satellite images resampling, (c) image fusion, combining and integrating between the visible and thermal images using the Grim Schmidt spectral (GS) method, (d) applying image classification using Mahalanobis distances (MH), Maximum likelihood (ML) and artificial neural network (ANN) classifiers on datasets captured from the Landsat-8 TIRS and OLI satellite system, these images were captured from operational land imager (OLI) and the thermal infrared (TIRS) sensors of 2015 and 2020 to generate about of twelve LC maps. (e) The comparison was made among all the twelve classifiers' results. The results reveal that adopting the ANN technique on the integrated images of the combined TIRS and OLI datasets has the highest accuracy compared to the rest of the applied image classification approaches. The obtained overall accuracy was 96.31% and 98.40%, and the kappa coefficients were (0.94) and (0.97) for the years 2015 and 2020, respectively. However, the ML classifier obtains better results compared to the MH approach. The image fusion and integration of the thermal images improve the accuracy results by 5%–6% from the proposed method better than using low spatial-resolution visible datasets alone. Doi: 10.28991/ESJ-2023-07-02-09 Full Text: PD

Water quality index for Al-Gharraf River, southern Iraq

The Water Quality Index has been developed mathematically to evaluate the water quality of Al-Gharraf River, the main branch of the Tigris River in the south of Iraq. Water samples were collected monthly from five sampling stations during 2015–2016, and 11 parameters were analyzed: biological oxygen demand, total dissolved solids, the concentration of hydrogen ions, dissolved oxygen, turbidity, phosphates, nitrates, chlorides, as well as turbidity, total hardness, electrical conductivity and alkalinity. The index classified the river water, without including turbidity as a parameter, as good for drinking at the first station, poor at stations 2, 3, 4 and very poor at station 5. When turbidity was included, the index classified the river water as unsuitable for drinking purposes in the entire river. The study highlights the importance of applying the water quality indices which indicate the total effect of the ecological factors on surface water quality and which give a simple interpretation of the monitoring data to help local people in improving water quality

Evaluation of Water quality in the Tigris River within Baghdad, Iraq using Multivariate Statistical Techniques

This research concentrated on the Tigris River water quality monitoring information. Some multivariate statistical techniques were applied like basic Ingredient (PC) test, discriminant analysis (DA), multiple linear regression analysis (MLRA) to evaluate important parameters affecting water quality during year 2017-2018. The study included 25 water quality parameters, viz., Temperature (T), Potential of Hydrogen (pH), Turbidity (Tur), Total Alkaline (TA), Full rigidity (TH), Calcium (Ca+2), Chloride (Cl-1), Magnesium (Mg+2), Electrical Conductivity (EC), Sulfate (SO4-2), Total Solids (TS), Suspended Solids (SS), Iron (Fe+2), Fluoride (F-1), Aluminum (Al+3), Nitrite (NO2-1), Nitrate (NO3-1), Silica (SiO2), Phosphate (PO4-3), Ammonia (NH3), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), Sodium (Na+1), and Total Dissolved Solids (TDS). Generally, all the parameters were within the standards except Tur, TA, Ca+2, EC, SO4-2. The levels of Tur and EC are of critical factors influence upon the Tigris water quality. The PCA identified six principal components responsible for 78.12% of the variation caused by the industrial, domestic, municipal and agricultural runoff pollution sources. DA results produced the eight parameters; T, BOD5, EC, Mg+2, DO, Tur, Na+1, and COD as the most significant parameters differentiating the two parts of the year (the cold and warm seasons). The result of MLRA showed that BOD5, Na+1, T, DO, and PO4-3 are the important dependable factors for predicting the COD value as an indicator of organic and nonorganic pollution. This research demonstrated success importance utilizing Multivariate statistical methods like valuable instrument of administration, control, and preserve the water of the river.Konferensartikel i tidskrift</p

Agriculture in Iraq

The climate of Iraq is of the subtropical semi-dry type; however, the country was rich in water resources until a few decades ago. The climate change, the construction of many dams on the Tigris and Euphrates Rivers in the neighboring countries, wasting water, and mismanagement caused water shortages. Now, there is a need to decrease consumption, good management of water resources and determining the water requirements and water footprints of the major crops because agriculture is the first consumer of water. The FAO CROPWAT 8.0 simulation model, the CLIMWAT 2.0 tool, and the Aqua-Crop model can be used in Iraq to find the crop water requirements (CWR), irrigation schedules and water footprint (WF) for major crops, the Aqua-Crop software can predict the effects of water deficits on crop productivity or yield to improve irrigation under limited water conditions. All of that is to improve the management of water resources to cope with drought. The objectives of this proposal study beside the calculating of wheat water footprint are to assess the capability of the AquaCrop model to simulate wheat (Triticum aestivum L.) performance in hot dry conditions under full and deficient water conditions in south of Iraq, to study the effect of various irrigation scenarios (stages of crop growth and water depth applied) on wheat yield. The AquaCrop model will be evaluated with experimental data during the field experiment. The AquaCrop model can accurately simulate root zone, crop biomass and grain yield soil water content, with less than 10 percent standardized root mean square error (RMSE).Validerad;2020;Nivå 1;2020-11-18 (alebob)</p

A novel neo-sex chromosome in Sylvietta brachyura (Macrosphenidae) adds to the extraordinary avian sex chromosome diversity among Sylvioidea songbirds

We report the discovery of a novel neo-sex chromosome in an African warbler, Sylvietta brachyura (northern crombec; Macrosphenidae). This species is part of the Sylvioidea superfamily, where four separate autosome–sex chromosome translocation events have previously been discovered via comparative genomics of 11 of the 22 families in this clade. Our discovery here resulted from analyses of genomic data of single species-representatives from three additional Sylvioidea families (Macrosphenidae, Pycnonotidae and Leiothrichidae). In all three species, we confirmed the translocation of a part of chromosome 4A to the sex chromosomes, which originated basally in Sylvioidea. In S. brachyura, we found that a part of chromosome 8 has been translocated to the sex chromosomes, forming a unique neo-sex chromosome in this lineage. Furthermore, the non-recombining part of 4A in S. brachyura is smaller than in other Sylvioidea species, which suggests that recombination continued along this region after the fusion event in the Sylvioidea ancestor. These findings reveal additional sex chromosome diversity among the Sylvioidea, where five separate translocation events are now confirmed

Crop Water Requirements and Irrigation Schedules for Some Major Crops in Southern Iraq

The climate of Iraq is of the subtropical semi-dry type; however, the country was rich in water resources until a few decades ago. Climate change and the construction of many dams on the Tigris and Euphrates rivers in the neighboring countries have caused water shortages and poor water quality. Now, there is a need to decrease consumption, improve management of water resources, and determine the water requirements of the major crops because agriculture is the first consumer of water in Iraq. The Food and Agriculture Organization (FAO) CROPWAT 8.0 simulation software and the CLIMWAT 2.0 tool attached to it have been used in this research for Dhi-Qar Province in southern Iraq to find the crop water requirements (CWRs) and irrigation schedules for some major crops. The CROPWAT Penman–Monteith method was used to calculate the reference crop evapotranspiration (ET0) and the United States Department of Agriculture (USDA) soil conservation (S.C.) method was used to estimate the effective rainfall. The study results showed that ET0 varied from 2.18 to 10.5 mm/day and the effective rainfall varied from 0.0 to 23.1 mm. The irrigation requirements were 1142, 203.2, 844.8, and 1180 mm/dec for wheat, barley, white corn, and tomatoes, respectively. There is a higher water demand for crops during the dry seasons (summer and autumn) and a lower demand during the wet seasons (winter and spring). The total gross irrigation and the total net irrigation were 343.8 mm and 240.7 mm for wheat, 175.2 mm and 122.6 mm for barley, 343.8 mm and 240.7 mm for white corn, and 203.3 mm and 142.3 mm for tomatoes. This study proved that the CROPWAT model is useful for calculating the crop irrigation needs for the proper management of water resources.Validerad;2019;Nivå 2;2019-04-15 (svasva)</p

Assessment of Main Cereal Crop Trade Impacts on Water and Land Security in Iraq

Growing populations, socio-economic development, the pollution of rivers, and the withdrawal of fresh water are all signs of increasing water scarcity, and with 85% of global use, agriculture is the biggest freshwater user. The water footprint (WF) and virtual water (VW) are concepts used recently for freshwater resources assessment. The WF reflects how much, when and where the water was used whereas VW reveals the volume of water embedded in goods when traded. The first goal of this research is to determine the WF per ton and the WF of production (Mm3/yr) of wheat, barley, rice, and maize in Iraq. The second goal is estimating the quantities of the 4 main cereal crops imported into Iraq and assessing the impact on reducing WF and land savings for 10 years from 2007 to 2016. The results showed that the WF per ton was 1736, 1769, 3694, 2238 m3/ton and the WF of production was 5271, 1475, 997, 820 Mm3/yr for wheat, barley, rice, and maize, respectively. The median total VW imported was 4408 Mm3/yr, the largest volume was 3478 Mm3/yr from wheat, and Iraq saved about 2676 Mm3 of irrigated water and 1,239,539 M ha of land by importing crops every year during 2007–2016. The study revealed the significance of better irrigation management methods to decrease the WF through a selection of crops that need less water and cultivation in rain-fed areas, as well as the use of cereal import to conserve scarce water resources, which is crucial both in terms of water resource management and preservation of the environment. The results of this research could be used as a guideline for better water management practices in Iraq and can provide helpful data for both stakeholders and policymakers.Validerad;2020;Nivå 2;2020-01-24 (johcin)</p

Acute toxicity of the water chlorinationbyproduct (chloroform) in male mice

Drinking water disinfection has been one of the biggest advances in public health. However, animal studies have suggested that when tested at high concentrations, certain disinfection byproducts disinfection (DBPs) in drinking water can cause an increased incidence of cancer and reproductive effects. In this study, sixty male white mice were kept under the laboratory conditions, divided into six exposure groups and administrated with single oral dose 0, 50, 300, 700, 1000 or 1500 mg/kg BW chloroform dissolves in corn oil as a vehicle. Clinical observations and gross pathologic examination made after dosing on surviving died, and animals that were killed on the 7th day. At end of 14 days, animal weights were recorded, liver and kidneys removed, weigh and examined with the naked eye then it was fixed in 10% Neutral Buffered Formalin (NBF), transfer to 70% ethanol and included in paraffin. Tissue parts were cut 4-5 μm soiled with hematoxylin and eosin. Clinical signs observed at high doses consisted of behavioral effects, reduced body weight, livers and kidneys were congested, enlarged and their weights increased. Liver damage was characterized mainly through centrilobular necrosis and massive necrosis at higher doses. The kidney damage containing raised kidney weight, inflammation, renal cell proliferation and proximal tubular necrosis. Lethal dose causes death in 50% of exposed animals (LD 50) value calculated by the probit analysis was 550 mg/kg Body Weight (BW).Godkänd;2021;Nivå 0;2021-01-01 (johcin);Konferensartikel i tidskrift</p

Fusion Landsat-8 Thermal TIRS and OLI Datasets for Superior Monitoring and Change Detection using Remote Sensing

Currently, updating the change detection (CD) of land use/land cover (LU/LC) geospatial information with high accuracy outcomes is important and very confusing with the different classification methods, datasets, satellite images, and ancillary dataset types available. However, using just the low spatial resolution visible bands of the remotely sensed images will not provide good information with high accuracy. Remotely sensed thermal data contains very valuable information to monitor and investigate the CD of the LU/LC. So, it needs to involve the thermal datasets for better outcomes. Fusion plays a big role to map the CD. Therefore, this study aims to find out a refining method for estimating the accurate CD method of the LU/LC patterns by investigating the integration of the effectiveness of the thermal satellite data with visible datasets by (a) adopting a noise removal model, (b) satellite images resampling, (c) image fusion, combining and integrating between the visible and thermal images using the Grim Schmidt spectral (GS) method, (d) applying image classification using Mahalanobis distances (MH), Maximum likelihood (ML) and artificial neural network (ANN) classifiers on datasets captured from the Landsat-8 TIRS and OLI satellite system, these images were captured from operational land imager (OLI) and the thermal infrared (TIRS) sensors of 2015 and 2020 to generate about of twelve LC maps. (e) The comparison was made among all the twelve classifiers' results. The results reveal that adopting the ANN technique on the integrated images of the combined TIRS and OLI datasets has the highest accuracy compared to the rest of the applied image classification approaches. The obtained overall accuracy was 96.31% and 98.40%, and the kappa coefficients were (0.94) and (0.97) for the years 2015 and 2020, respectively. However, the ML classifier obtains better results compared to the MH approach. The image fusion and integration of the thermal images improve the accuracy results by 5%–6% from the proposed method better than using low spatial-resolution visible datasets alone.Validerad;2023;Nivå 1;2023-02-17 (joosat);Licens fulltext: CC BY License</p

Water Footprint of Wheat in Iraq

The water footprint (WF) is an indicator of indirect and direct fresh water use. In respect of facilitating decision-making processes,WF gives an excellent perspective on how and where fresh water is used in the supply chain. More than 39million people live in Iraq and,with a growing population, there is a water shortage and a rising demand for food that cannot be met in the future. In this study, theWF of wheat production is estimated for the year 2016–2017 for 15 Iraqi provinces. TheWF was calculated using the method ofMekonnen and Hoekstra (2011) and the CROPWAT and CLIMWAT softwares’ crop water requirement option. It was found that theWF in m 3/ton was 1876 m3/ton. The 15 provinces showed variations inWFs, which can be ascribed to the difference in climate and production values. The highest wheat WF was found in Nineveh province, followed by Muthanna, Anbar, and Basra. The last three provinces produce little and have a highWF so, in these provinces, wheat can be replaced with crops that need less water and provide more economic benefit. There is an opportunity to reduce the greenWF by increasing production from the 4 rain-fed provinces, which will reduce the need for production from the irrigated provinces and, therefore, reduce the use of blue water.Validerad;2019;Nivå 2;2019-03-22 (johcin)</p