أجريت التجربة في مزرعة كلية الزراعة جامعة الفاتح بطرابلس خلال عام كامل من (21/5/2006)إلى (30/5/2007) بهدف تقدير البخر بواسطة ثلاثة أحجام من اللايزيمترات الموضوعة في ثلاثة أماكن وهي الصوبة و الهواء الطلق و الظل وبعد تجميع التربة و تجفيفها وبواسطة ميزان حساس تم وزن التربة ووضعت في كل ليزيمتر التربة المقدر له و من قطر وطول كل ليزيمتر و الكثافة الظاهرية و السعة الحقلية للتربة تم تحديد حجم الماء المضاف لكل ليزيمتروتم قياس الوزن قبل عملية الري و من تم إضافة الماء اللازم لري كل ليزيمترو تم قياس الوزن يوم بعد يوم بواسطة ميزان حساس وعلى أساس هذا الفرق نقوم بإضافة ماء الري إلي اللايزيمترات وتم أخذ البيانات المناخية و هي كمية المطر و درجة الحرارة و الرطوبة النسبية و سرعة الرياح من مركز الأرصاد الجوية للايزيمترات الموضوعة في الهواء الطلق و في الظل و قياس درجة الحرارة بواسطة جهاز الترمومتر و الرطوبة النسبية بواسطة جهاز Hygrometre للايزيمترات الموضوعة في الصوبة و من خلال النتائج المتحصل عليها من قياس معدل متوسط التبخر اليومي والتحليل الإحصائي الذي أجري علي النتائج علي مدار السنة وجد أن هناك تأثير معنوي ( عند مستوى المعنوي 5٪ ) بين أحجام اللايزيمترات أي أن معدل التبخر اليومي من اللايزيمترات الصغيرة الحجم أكبر من اللايزيمترات المتوسطة و الكبيرة الحجم علي التوالي أي أن معدل التبخر يقل كلما زادت المساحة السطحية للايزيمترات وهناك تأثير معنوي ( عند مستوى المعنوي 5٪ ) بين الأماكن الموضوعة فيها اللايزيمترات إي أن معدل التبخر اليومي للايزيمترات الموضوعة في الهواء الطلق أكبر من اللايزيمترات الموضوعة في الظل و الصوبة علي التوالي و من معادلة اتزان الطاقة توضح أن قيمة معدل البخر و النتح القياسي تتوافق مع قيمة متوسط معدل التبخر من اللايزيمترات أي أن كلما زادت المساحة السطحية للايزيمترات قل معدل البخر و أصبح أقرب من البخر و النتح القياسي المقدر بطريقة معادلة اتزان الطاقة. Abstract The Experiment was conducted at the farm of collage of agriculture university of Elfateh for aperiod of one year starting May 21- 2006 and ending May 30 – 2007. The aim was estimating evaporation using three small lysimeter with different sizes(a inside diameter 7-10.5-14.9 cm) and located of glass house, open and under shade, soil sampels was collected, dride and weighed by sensitive balance. The weight of the soil was estimated by knowing, the volume of each lysimeter, soil bulk density and soil field capacity used to estimate the amount of water added to each lysimeter. The volume of water conducted was add to each lysimeter to reach the field capacity every two days the lysimeter weight and the amount of water lost by evaporation and drainage was added to reach the field capacity.Rainfall record , air temperature , relative humidity and wind speed for the open area was collected from the near station , Hygrometer and thermometer used on site in the green house for humidity and temperature record . The results and the analysis of data at level 5 % show asignifecant difference between sizes, the rate of evaporation decrease as the surface area of the lysimeter increase, concerning the location of the lysimeter, at the level of 5 % significant difference was clear, the evaporation rate for the lysimeter in the open was higher the evaporation rate for the lysimeter under shade higher than the lysimeter in the green house. Comparing the average evaporation from the lysimeter with the results of energy balance equation, the evaporation from the lysimeter less than the one from the equation and this indicate that the rate of evaporation increase as the surface area of lysimeter increase and get close to the rate of evaporation from the energy balance equation.
كريمة خليل التركي (2009)

Different methods accessible for remote sensing image classification; they include supervised, unsupervised and fuzzy classifications. This paper investigates the performance of the supervised classification on remote sensing data for land cover/ land use in North-West Region of Jeffara Plain of Libya. The study used SPOT 5 satellite image taken on January 2009 as a main data. Maximum likelihood classification (MLC) which is based on the probability that a pixel belongs to a particular class were chosen to classifying land cover data/ land use in the study area. The land cover /land use classes for the study area were classified into 5 homogeneous land cover classes of a single land cover and 4 heterogeneous land cover classes. Ground verification was applied to verify and evaluate the accuracy of supervised classification. 48 field points were collected using Systematic Random Sampling. The results showed that 65 % of the study area was classified into heterogeneous land cover classes, while 25 % of the study area classified into homogeneous land cover classes. Derivation heterogonous or mixed land cover classes from the use supervised classification (i.e. crisp classification) led to producing uncertain or vague land cover classes in the study area. For future work, the authors will test the fuzzy image classification to derive land cover and land use data in the study area. Keywords: Supervised classification, spot image, land cover /land use, Jeffara Plain
Mukhtar Mahmud Elaalem(3-2013)

Boolean approaches to land suitability treat both the spatial units and the value ranges as clearly defined. This is to ignore the continuous nature of land properties as well as the differences and uncertainties in measurement. The objective of this paper was to compare two approaches to land suitability evaluations; Parametric and Fuzzy Multi-Criteria Methods to model the opportunities for olive production in Jeffara Plain of Libya. In this paper a number of soil and landscape criteria were identified and their weights specified as a result of discussions with local experts. The Fuzzy MCE approach was found to be better than the parametric approach. The Fuzzy MCE approaches accommodate the continuous nature of many soil properties and produce more intuitive distributions of land suitabilities value for olive. The results of Fuzzy MCE showed that the majority of the study area is highly suitable for olive production, while the results obtained from the use the parametric method showed that most of the study area is moderately suitable for olive production.
Mukhtar Mahmud Elaalem(1-2013)