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Spatial analysis (spatial statistics) contain systematic techniques, that study actually geographic data have geographic properties such as topological and geometric, spatial analysis involve difference types of technique. Spatial analysis represented new understanding complex topics in form easy by any method or statistical for study area include mathematics and logic. Using function of point density which represented the Radon gas measurement geographic location, and limitation the density area by finding the radii (bandwidth) Kernel Density Estimation (KDE) techniques variation to reach interest regions and hotspot of point’s neighborhood. The aim of the research, applied the spatial statistical method to acknowledge concentrations of radon gas pollution for environmental and human life conservation, and focuses on the region affected by determination and orientation it in this method or tools for control outbreak to be facilitated, this potential possibility aid to avoid research randomly for radon gas pollution regions, this processing consist by extraction the spatial characteristics distribution that depending on distance measurements, by using geographic information system (GIS) technical, and which exploited Global Positioning system to accurate simultaneously the spectral bands of landsate satellite imagery to referencing the study area, and they have been determining the topology objects such as land cover (water, vegetation and soil) and land use, to connected with points measurement of Radon gas in Baghdad city only soils election, thought the soils were caused pollution based for objects type such as water and air, because, the natural formative of layer soils by decay of radioactive isotope Uranium with erosion the rocks and drift process with dissolved water or flood throughout the ages. Doing field the soil samples measurement by RAD7 Mobil detector for 58 point samples election, which represented using soil type such as vegetation land and land use touched with human life.

The hard environmental factors of AL-Abedh basin region forced the native tribes to make multitude migrations in it around the year seeking for water and pasture lands . Existence of sufficient water supplement will settle these tribes down and enhancing their eco system. The real capability of GIS software to be a decisions making support tool or operations management assistant mean came from its ability of data integration and information analysis. This capability was invested in this research to determine the optimum location of a dam that confine huge amount of water in its lake which can be used to provide water for drinking, pasture irrigation and land reclamation along the valley banks, and hydroelectricity power generation. In this location one dam with two possible heights could be constructed with a medium to few permeability reservoir soil behind it having 77.781 km2 and 1039.306 km2 areas respectively.

Ain Sokhna in Egypt has undergone profound anthropogenic geomorphological shifts, driven by the establishment of the Sokhna port, tourist resorts, industrial facilities, and transportation routes. These alterations, closely linked to the region's strategic importance since the early 2000s, have essentially turned it into a hub for various industries. The construction of the Sokhna port caught the attention of various sectors, leading to the development of infrastructure and the transformation of the area into an attractive destination for tourism. Despite their human origin, these features are intricately connected to natural processes like erosion and sedimentation, causing noticeable changes in the morphology of the study area. While these human-induced activities have altered Ain Sokhna's coastal landscape, they have also yielded economic advantages, job opportunities, and infrastructural advancements. Striking a balance between development and environmental sustainability remains a formidable challenge for policymakers and local communities in the region, to address this challenge, it is imperative to conduct thorough studies, maintain ongoing monitoring efforts, and adopt sustainable coastal management practices. These measures are crucial to minimizing the adverse impacts of human activities and ensuring the long-term ecological health of Ain Sokhna.

The floor of Wadi An-Natrun Depression has a high level of salinity and occupies by a shallow salt lakes, which are characteristic geomorphologic landforms. In general, Wadi An-Natrun Depression is characterized by very arid climate. The geological formations of Wadi An-Natrun Depression range from lower Miocene, lower Pliocene and Quaternary deposits. This study attempts to determine the effectiveness of using remote sensing indicators in deducing sabkhas in the Wadi El-Natrun depression utilizing Landsat 8 OLI satellite images based on field data of laboratory analyzes of sabkhas soil samples collected through the field study. To achieve this, linear and multiple regression models were applied between soil salinity and electrical conductivity (ECe) on the one hand and remote sensing indices on the other hand, where the NDSI index had the highest correlation coefficient of 0.872. This was followed by the derivation of the Enhanced soil salinity index from (NIR), (SWIR) 2 and the NDVI index, which had higher correlation than NDSI with electrical conductivity (ECe) of 0.918.

Combining the color difference formula of CIEDE2000 and the printing industry standard for visual verification, we present an objective color image quality assessment method correlated with subjective vision perception. An objective score conformed to subjective perception (OSCSP) Q was proposed to directly reflect the subjective visual perception. In addition, we present a general method to calibrate correction factors of color difference formula under real experimental conditions. Our experiment results show that the present DE2000-based metric can be consistent with human visual system in general application environment.

Many studies house indicated the increase of the proportion of urban areas over the arable land in many provinces of the Sultanate of Oman. This came as a result of urban growth and development processes taking place since the era of the Renaissance which started in 1970. Consequently, spatial variation in land use is an important issue to be taken into consideration, because lands are being converted to be less productive, due to the lack of raw soil, vegetation, and water as a result of human exploitation of the limited resources in different ways, in addition to the natural factors of droughts and floods and all that will eventually lead to land degradation. Barka province (wilayat) in al Batinah Governorate is one of the provinces, which has been affected by land cover/land use changes due to several reasons. Therefore, this study will focus on the determination of land use changes, whether commercial or residential that have been occurred in the province, in addition to the loss of agricultural areas and fertile land during the period from 1987 to 2015. Remote sensing and geographic information system (GIS) were utilized in order to delineate and to determine the cause of shrinking in the arable land and fertile land. Satellite images were used to detect the change in land use/land cover by applying selective digital image processing techniques such as supervised classification and change detection. Thematic maps were prepared using GIS software with attribute data about the land uses in the study area, which highlights and show the impact of urban growth on land degradation.

A study was conducted to investigate the effect of the brick industry on the environmental system of these project soils of the brick factories in Alnahrawan district. Remote sensing techniques was used to study the relationship between the spectral reflectivity and the vegetative index on the one hand and some surface soil characters of the project and to determine the variation in vegetation cover for the same area and for two different periods.Ten sites were selected to study spectral reflectivity under similar geomorphological conditions near the brickworks project in the Anahrawan district with an area of 10,000 hectares. Soil samples were taken from the surface and at a depth of 0-30 cm. Some chemical and physical characters of research soil were analyzed in the soil department laboratories, college of Agriculture, Baghdad University.Several satellite images taken from the satellite Land sat (ETM) 2013 and another from same satellite in 1990 T.M to determining the change between the two periods. After obtaining remote sensing data (reflectivity and vegetation index).the correlation analysis was carried out between these data. It was observed that the soil salinity values were decreased due to the drainage that the area was confined between the Tigris River and the Diyala tributary which leads to good natural drainage.The attached tables indicate that thedigital numbers of the soil sampling sites in 2013 are highly significant correlated, While some of the characters did not show the use of this region industrially. After calculating the difference between the two images to determine the change. A 100% change was observed and the vegetation cover was sharply reduced between the two images. as well as the extension of the land of empty land, although these lands are still suitable for agriculture.

The study adopts a number of soil salinity indices by applying geoinformatics techniques in the northeast of the Nile River Delta, based on the different spectral reflectance of soil salinity. The field investigation is carried out by collecting soil samples, and chemically analyzing them in order to compare them with the results of the indices (8 indices), relying on field review so as to capture images indicative of soil salinity and its impact on the land use that is most vulnerable to it, and this is vegetation. This is mainly for the sake of supporting the accuracy of the spectral resolution. It is found that each index relies on different variables of spectral reflectance. Accordingly, the study identifies the most appropriate and effective indices for assessing salinity, both spatially and temporally, in the northeast of the Nile River Delta. This is done through determining the highest degree of correlation between the results of the indices and the results of the chemical analysis of soil samples. Moreover, the study relies on the best indices in determining vegetation, which is EVI, so as to find out the degree to which the vegetation density is affected by soil salinity. This is carried out with the aim of coming up with results that help decision-makers in addressing the problems resulting from soil salinity with the least effort, the lowest cost, and the highest accuracy and realism.

Technology of precision agriculture has caused to the remote sensors development that compute Normalized Difference Vegetation Index (NDVI) parameters. Vegetation indices obtained from remote sensing data can help to summarize climate conditions. Artificial Neural Networks (ANNs), as a soft computing methods, are one of the most efficient methods for computing as compared to the statistical and analytical techniques for spectral data. This study was employed experimental radial basis function (RBF) of ANN models and adaptive neural-fuzzy inference system (ANFIS) to design the network in order to predict the soil plant analysis development (SPAD), protein content and grain yield of wheat plant based on spectral reflectance value and to compare two models. Results indicated that the obtained results of RBF method with high average correlation coefficient (0.984, 0.981 and 0.9807 in 2015 for SPAD, yield and protein, respectively and 0.979, 0.9805 and 0.984 in 2016) and low RMSE (0.271, 103.315 and 0.111 in 2015 for SPAD, yield and protein, respectively and 0.407, 105.482 and 0.121 in 2016) has the high accuracy and high performance compared to ANFIS models.

يحتاج نخيل التمر إلى كمية كافية من المياه ذات الجودة المقبولة للوصول إلى الإنتاجية المتوقعة. أجريت هذه الدراسة في واحة الأحساء التي تقع بالمنطقة الشرقية من المملكة العربية السعودية بهدف تقدير البخرنتح الفعلي (ETa) اليومي، الشهري و السنوي لنخيل التمر باستخدام بيانات القمر الصناعي لاندسات-8 خلال العام 2017/2018. أيضا تمت مقارنة ETa المحسوب و كمية المياه الفعلية المطبقة في الحقل. استخدمت خوارزمية توازن الطاقة السطحية للأرض (SEBAL) المدعومة بالبيانات المناخية لحساب ETa. تم التحقق من صحة مخرجات نمذجة SEBAL باستخدام طريقة Penman-Monteith الخاصة بمنظمة الزراعة و الأغذية التابعة للأمم التحدة (FAO) بجانب المشاهدات و القياسات الحقلية. أوضحت النتائج أن أعلى قيمة يومية لـ ETa لوحظت خلال موسم الصيف كانت 9 ملم/يوم، و أدنى قيمة كانت 2 ملم / يوم كانت أثناء الشتاء. وجد أن متوسط المياه الشهرية المطبقة في المزارع أعلى بنسبة 15 ٪ من المعدل الذي اقترحته نمذجة SEBAL خلال ذروة الصيف. تراوحت ETa السنوية بين 800 و 1400 ملم / السنة، في حين تراوحت متطلبات الري السنوية لنخيل التمر بين 11000-13000 متر3/ السنة. أظهر قياس دقة التحقق وجود توافق كبير بين نمذجة SEBAL و طريقة Penman-Monteith بمتوسط خطأ قياس للجذر التربيعي (RMSE) يبلغ 0.84 ملم/يوم. خلصت الدراسة إلى أن ETa المحسوبة من بيانات الأقمار الصناعية و نمذجة SEBAL تساعد في عملية إدارة مياه ري نخيل التمر اليومية على نطاق المزرعة. كما أن هذه المعلومات ضرورية لمخططي المياه و واضعي السياسات لصياغة الاستراتيجيات و اتخاذ القرارات المناسبة لإدارة الموارد المائية في المناطق الزراعية الكبيرة. Date palm needs sufficient water of acceptable quality to reach its potential yield. The present study conducted in Al-Hassa Oasis located in the Eastern Region of the Kingdom of Saudi Arabia aiming to estimate the daily, monthly and annual actual evapotranspiration (ETa) for date palm using Landsat-8 satellite data during 2017/2018. Also, an attempted was made to compare between the computed ETa and the actual water applied in the field. The Surface Energy Balance Algorithm for Land (SEBAL) supported by climate data was used to calculate the ETa. The SEBAL model outputs were validated using the FAO Penman-Monteith method coupled with field observation and measurements. The results showed that the highest daily ETa value observed during the summer season was 9 mm. day−1, and the lowest value was 2 mm. day−1 in winter. The mean monthly water applied in the farms was 15% higher than that suggested by SEBAL during the peak summertime. The annual ETa varied between 800 and 1, 400 mm. year−1, while the annual irrigation requirement for date palm was in the range of 11000 – 13000 m3. ha−1. The validation measure showed a significant agreement level between the SEBAL model and the FAO Penman-Monteith method with RMSE of 0.84 mm. day−1. The study concludes that the ETa calculated from the satellite data and the SEBAL model is useful for guiding the daily operation of date palm water management at the farm scale. Also, this information is essential for water planners and policymakers to formulate strategies and make decisions for managing water resources over large agricultural areas.