Ahmed Asaad Zaeen

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Remote Sensing Unit, College of Science, University of Baghdad
Remote Sensing Unit, College of Science, University of Baghdad

Ahmed Asaad Zaeen


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https://researchid.co/ahmedzaeen
PhD in Agricultural Sciences-Remote Sensing from the University of Maine, USA (2020), supervised by Dr. Lakesh K. Sharma.
2-M.Sc. in agricultural sciences-remote sensing, soil and water resources from University ofBaghdad, Iraq, (2008), supervised by Dr. Ahmed S. Muhaimed.
3- B.Sc. in agriculture sciences, soil science & water resources from the University of Baghdad,Iraq (2005).

EDUCATION

PhD in Agricultural Sciences-Remote Sensing from the University of Maine, USA (2020), supervised by Dr. Lakesh K. Sharma.
2-M.Sc. in agricultural sciences-remote sensing, soil and water resources from University ofBaghdad, Iraq, (2008), supervised by Dr. Ahmed S. Muhaimed.
3- B.Sc. in agriculture sciences, soil science & water resources from the University of Baghdad,Iraq (2005).

RESEARCH, TEACHING, or OTHER INTERESTS

Soil Science, Plant Science, Agronomy and Crop Science
19

Scopus Publications

Scopus Publications

  • Land Use Decision Using Soil Indices and Fuzzy Inference System in AL-Khamisiyah
    Amal J. Hatem, Ahmed Asaad Zaeen, Heba Kh. Abbas, Mustafa A. Raheem
    Iraqi Journal of Science, 2026
    The selection of the most suitable land for cultivating a particular crop is one of the major problems facing the Ministry of Agriculture in general and farmers in particular, and this suitability for cultivation depends on many factors (natural and human), including soil type. This research used indicators, remote sensing, and spatial modeling to solve this problem. The method of band rationing was applied to calculate the salinity index (SI) and the Normalized Multi-Drought Index (NMDI) as a pre-processing for agricultural decision-making in specific areas in southern Iraq (Dhi Qar, Al-Khamisiyah), using the Landsat-8 satellite image of this area. Maximum likelihood classification was used to classify the study area into multiple classes. The soil was classified in a study area using a fuzzy inference system (FIS) to determine suitability for growing different types of crops according to the values of the salinity index and the multiple drought index measured for each crop. The results of the study showed that Al-Khamisiyah land is valid and suitable for the cultivation of specific crops (onions, lettuce, cabbage, cucumbers, celery, guava, and cowpeas) with an area of ​​946,541,700 m2 of the studied area, while it is not suitable for the cultivation of other crops namely pepper and beets.
  • Monitoring and Analyzing the Spread of Drug Dealers "Drug Pills Addiction" Using the Geographic Information System (GIS) in Baghdad City for the period 2020 – 2021
    Fouad K. Mashee Al-ramahi, Ahmed Asaad Zaeen, Faleh H. x Mahmood
    Iraqi Journal of Science, 2025
    The phenomenon of the drug trade has become a concern for the whole world, due to its negative effects on societies and the frustration that it caused when spreading to all parts of the society after being prevalent among young people only. The purpose of the study is to detect and identify the presence of drug dealers' gangs and the possibility of their presence and spread according to the neighboring areas and the number of residents. According to the data of the Iraqi Ministry of Interior for the period 2020-2021, organized gangs of the drug trade have become rampant in Iraqi society and are not confined to a specific group or place, but are practiced by many due to the multiple entry and exit outlets for this trade and the lack of control over it. There are many reasons for this organized attack. It was processed using remote sensing techniques and Geographic Information Systems (GIS) ArcMapV10.4 and the use of shapes that simulate reality (shape files) as the study area, which is the city of Baghdad, the capital of Iraq, which was made according to satellite images of the Landsat Satellite, to provide a model to help decision-makers make a set of measures to reduce the spread of the phenomenon of drug trade in Baghdad, confine, and restrict it. The results of the study were that the population had the highest probability of gang spread (1.983-61.52) in the areas of Rashydea, Husseiniya1, Al-Shaab, and Rafydean (Al-Sadr) sub-districts, and the least probability (61.53-189.4) represented the rest of the study areas. The highest probability of spreading the work of drug gangs in relation to the city of Baghdad was (255.52-1,004.3) in Al-Sadr City 1, Al-Sadr City 2, and Rafydean sub-districts. Our study has pioneered in giving results that we believe are the first to be proposed at the level of researchers in the world using modern technologies that simulate reality according to contemporary analysis.
  • Determining the Soil Elements Distribution of a Google Earth Image Using a New Processing Method: A Case Study in Iraq
    Khaleel Ibrahim Abood, Ahmed Asaad Zaeen, Faleh Hassan Mahmood
    Iraqi Journal of Science, 2025
    The study uses the photometric method, which depends on the intensity of color scale levels in the image pixels. The work is based on converting color into a wavelength in each pixel; in the beginning, the work has been verified by measuring the monochromatic wavelengths of rays, such as lasers. The Matlab program (image processing) calculated the number of lasers as 325 nm, 473 nm, 477 nm, 535 nm, 603, and 785 nm, where the results were very good and had a low error rate. The elements had distinctive colors, which indicated wavelengths in the visible range. The work was done for the sulfur element found in specific Iraqi locations, such as Al-Mashraq field in Mosul province. The image processing techniques by Matlab software, with the assistance of the Google Earth tool, zoomed the land from a scale of about 700 km to 5m, as shown in the research results. The result showed that the sulfur element locations on the map revealed that Iraq contains significant quantities of the element in western and southwestern regions, which essentially concentrate in referred locations compared to some fields in northern Iraq. This study and its results can help companies identify specific sulfur fields.
  • Measuring Urban Heat Island Indicators from Surface Temperature Using Spatial Techniques
    Yusra K. H. Moussa, Ahmed Asaad Zaeen, Hala A. Jasim, Mohammed I. Abd-Almajied, Eman H. Khudhair, et al.
    Journal of Physics Conference Series, 2025
    Using remote sensing technology and modeling methodologies to monitor changes in land surface temperature (LST) and urban heat islands (UHI) has become an essential reference for making decisions on sustainable land use. This study estimates LST and UHI in Salah al-din Province to contribute to land management, Urban planning, or climate resilience in the region; as a result of environmental changes in recent years, LANDSAT Satellite Imagery from 2014- 2024 was implemented to estimate the LST and UHI indexes in Salah al-din Province, ArcGIS 10.7 was use to calculate the indices, and The normalized mean vegetation index (NDVI) was calculated as it is closely related to extracting (LST & UHI) indices. Results confirmed that extracting the vegetation index, atmospheric radiation, brightness temperature of the satellite, and earth’s surface emissivity from (Landsat-8) bands and processing them on ArcGIS facilitates the estimation of each of (LST and UHI) indexes. Results showed that (UHI) forms a complete correlation with (LST). The correlation coefficient in 2014 and 2024.
  • Novel Fusion Approaches for Enhanced Image Processing with Smoothed Images
    Ahmed Asaad Zaeen, Nawras Badeaa Mohammed, Haidar J. Mohamad, Heba Kh. Abbas, Anwar. H. Al-Saleh, et al.
    Iraqi Journal of Science, 2025
    Image fusion is integrating multiple images from many sources and changing them into a single image with clearer and more accurate information. Image fusion techniques have been proposed to enhance distorted input images using a smooth filter to improve the clarity of distorted images. This work fused images resulting from smooth filters (half left and half right) with size windows of (3×3), (5×5), (7×7), (9×9), and (11×11) pixels. The image resulting from the smooth filter towards the right was combined with the image from the smooth filter towards the left using traditional techniques such as addition, multiplication, and new suggested techniques, namely absolute real standard deviation, binary standard deviation, real covariance, and binary covariance. The data examined by quality assessment methods with reference depend on Mutual Information, Correlation Coefficient, Structural Similarity Index metric, Structural Content, Normalized Cross Correlation, and without references like Blind Reference less Image Spatial Quality Evaluator, Naturalness Image Quality Evaluator, Perception-based Image Quality Evaluator, and Entropy. Lena's image shows a different behavior than the cameraman and the personal images because Lena's image has more details, resolution, and sharper contrasts. The best combination method was binary standard division.
  • Smart fertilizer technologies: An environmental impact assessment for sustainable agriculture
    Sukhdeep Singh, Ravinder Singh, Kulpreet Singh, Karun Katoch, Ahmed A. Zaeen, et al.
    Smart Agricultural Technology, 2024
  • Horan Valley Basin Geomorphological Aspects Assessment by Integrating Hypsometric Analysis with Remotely Sensed Morphometric Characteristics
    Laith A. Jawad, Ahmed A. Zaeen, Tariq Z. Hamood
    Iraqi Journal of Science, 2024
    The extraction, study, and accurate interpretation of the morphology database of a basin are the basic blocks for building a valid geomorphological understanding of this basin. In this work, a new approach is presented which is to use three different GIS based methods to extract databases with specific geographical information and then use the concept of information intersection to make a realistic geomorphological perspective for the study area. In the first method, data integration of remote sensing images from Google Map and SRTM DEM images were used to identify Horan basin borders. In the second method, the principle of data integration was represented by extracting the quantitative values of the morphometric characteristics that were affected by the geomorphological condition of the studied basin, such as the shape factor, circulation factor, and relief ratio, then eliciting an optimal conception of the geomorphological condition of the basin from the meanings and connotations of these combined transactions. The third method used the same principle by taking the optimal inferences from the integration of the interpretation of the values of the Hypsometry integration coefficients for each area in the basin separately with the integration value of the drawing curve for the relative heights of the basin areas with their relative areas. It was found, from the values of the coefficients, that the areas (A, B, C, D, and F) were still in the early stages of youth. Whereas the E region was in the maturity stage and the G region was in the monadnock stage of the geomorphological cycle. As for the integral value of the curve, it indicated 48. 559 % erosion from the surface of the basin only, and that its boundaries were subject to change and widening.
  • Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
    Khalid H. Abbas Al-Aarajy, Ahmed A. Zaeen, Khaleel I. Abood
    TEM Journal, 2024
    Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings, water bodies, and bare lands. During 2013-2022, vegetation cover increased from 63% in 2013 to 66% in 2022; buildings roughly increased by 1% to 3% yearly; water bodies showed a decrease of 2% to 1%; the amount of unoccupied land showed a decrease from 34% to 30%. Therefore, the classification accuracy was assessed using the approach of comparison with field data; the classification accuracy was about 85%.
  • An Application for Smartphones and Computers to Diagnose and Control Potatoes Insects
    Ahmed Asaad Zaeen, Ruaa Muhammed Dhedan, Lakesh K. Sharma
    Iraqi Journal of Science, 2023
    Nowadays, a strong relationship between the agriculture sectors and digital technologies is really interesting. The article describes how recent intelligent technologies can improve agricultural fields. Mobile applications are software programs created on smartphones, tablets, and computers. Agricultural fields mainly represent the pillar of the economy and the business sector that fulfills the world's food requirements. The United States has a valuable rank in potato production, which depends on this production economically. Nevertheless, so many insects affect potato yield production quantitatively and qualitatively. So, a smartphone App was created to help potato growers diagnose insects that directly attack potato crops and treat them. The created App focuses on a list of the common insects that attack potato crops in Maine State. App Inventor Platform, run by the Massachusetts Institute of Technology (MIT), was used to develop the application. Insect images and insecticides information were collected from the Cooperative Extension Department at Presque Isle City, Aroostook County, Maine, USA. The App provides essential details regarding insect types, life cycles, where they are coming from, and the time of attacking the plants. The App includes a list of effective insecticides that control insects. The App also provides helpful instructions concerning trade names, dose per acre of insecticides, and whether it should be applied to soil or plant leaves. Money and time are saved by applying this App since farmers do not need to spend time collecting samples and bringing them to the lab.
  • Sensors Work in Agriculture: Where Are We? What Are the Prospects?
    Ahmed Asaad Zaeen, Laith Aziz Jawad, Lakesh K. Sharma, Tareq Zaid Hamood
    Iraqi Journal of Science, 2023
    The increased food requirement puts intense pressure on the agriculture community to grow more from the same resources resulting in people leaving the farming business. This happened not exclusively due to the industrial pressure to produce more but to the lack of technology adoption among growers. The use of the sensor in agriculture is not new, but its adoption among agriculture producers is a challenge for industry and scientists. This study aimed to determine sensors used in agricultural fields with challenges and prospects. The study found that sensors have successfully been used at the industry level with highly skilled labor; however, their adoption is challenging in rural agriculture systems due to the lack of a support system. The study found that the sensors used in predicting crop parameters, yield, quality, insect attacks, leaf damage, and several plants are crucial parameters to study. Sensors, particularly ground-based active optical sensors, have performed well while developing algorithms where soil parameters, environmental factors, and sensors have successfully predicted crop yield and quality.
  • ACTIVE OPTICAL SENSORS TO DEVELOP NITROGEN FERTILIZER RECOMMENDATIONS FOR POTATO CROP
    Ahmed. A. Z., L. Sharma, S. Bali, A. Buzza, A. Alyokhin
    Iraqi Journal of Agricultural Sciences, 2023
  • Spatial Analysis of Relative Humidity and Its Effect on Baghdad City for The Years 2008, 2013 and 2018
    Iraqi Journal of Science, 2022
  • Growing potatoes
    Lakesh K. Sharma, Ahmed Zaeen, Sukhwinder Bali
    Insect Pests of Potato Global Perspectives on Biology and Management, 2022
  • Predicting phosphorus and potato yield using active and passive sensors
    Ahmed Jasim, Ahmed Zaeen, Lakesh K. Sharma, Sukhwinder K. Bali, Chunzeng Wang, et al.
    Agriculture Switzerland, 2020
  • Potato phosphorus response in soils with high value of phosphorus
    Ahmed Jasim, Lakesh K. Sharma, Ahmed Zaeen, Sukhwinder K. Bali, Aaron Buzza, et al.
    Agriculture Switzerland, 2020
  • In-season potato yield prediction with active optical sensors
    Ahmed A. Zaeen, Lakesh Sharma, Ahmed Jasim, Sukhwinder Bali, Aaron Buzza, et al.
    Agrosystems Geosciences and Environment, 2020
  • Yield and quality of three potato cultivars under series of nitrogen rates
    Ahmed A. Zaeen, Lakesh K. Sharma, Ahmed Jasim, Sukhwinder Bali, Aaron Buzza, et al.
    Agrosystems Geosciences and Environment, 2020
  • Use of rainfall data to improve ground-based active optical sensors yield estimates
    L.K. Sharma, S.K. Bali, A.A. Zaeen, P. Baldwin, D.W. Franzen
    Agronomy Journal, 2018
  • A case study of potential reasons of increased soil phosphorus levels in the Northeast United States
    Lakesh Sharma, Sukhwinder Bali, Ahmed Zaeen
    Agronomy, 2017