Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis

Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.

Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques

The use of three-dimensional maps is more effective than two-dimensional maps in representing the Earth’s surface. However, the traditional methods used to create digital surface models are not efficient for capturing the details of Earth’s features. This is because they represent only three-dimensional objects in a single texture and do not provide a realistic representation of the real world. Additionally, there is a growing demand for up-to-date and accurate geo-information, particularly in urban areas. To address this challenge, a new technique is proposed in this study that involves integrating remote sensing, Geographic Information System, and Architecture Environment software to generate a highly-detailed three-dimensional model. The method described in this study includes several steps such as acquiring high-resolution satellite imagery, gathering ground truth data, performing radiometric and geometric corrections during image preprocessing, producing a 2D map of the region of interest, constructing a digital surface model by extending the building outlines, and transforming the model into multi-patch layers to create a 3D model for each object individually. The research findings indicate that the digital surface model obtained with comprehensive information is suitable for different purposes, such as environmental research, urban development and expansion planning, and shape recognition tasks.

Application of Time Series Analysis to Annual Rainfall Values in Debre Markos Town, Ethiopia

For many years planning and management of water resources involved modeling and simulation of temporally sequenced and stochastic hydrologic events. Rainfall process is one of such hydrologic events which calls for time series analysis to better understand interesting features contained in it. Many statistics-based methods are available to simulate and predict such a kind of time series. Autoregressive (AR), moving average (MA), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) models are among those methods. In this study a search was conducted to identify and examine a capable stochastic model for annual rainfall series (over the period 1954-2015) of Debre Markos town, Ethiopia. For the historical series, normality and stationarity tests were conducted to check if the time series was from a normally distributed and stationary process. Shapiro-Wilk (SW), Anderson-Darling (AD) and Kolmogorov-Smirnov (KS) tests were among the normality tests conducted whereas, Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests were among the stationarity tests. Based on the test results, logarithmic transformation and first order differencing were performed to bring the original series to a normal and stationary series. Results of model fitting showed that three models namely, AR (2), MA (1) and ARMA (2,1) were capable in describing the annual rainfall series. A diagnostic check was performed on model residuals and ARMA (2,1) was found to be the best model among the candidates. Furthermore, three information criteria: Akaike Information Criterion (AIC), the corrected Akaike Information Criterion (AICc) and Bayesian Information Criterion (BIC) were used to select the best model. In this regard, too, the least information discrepancy between the underlying process and the fitted model was obtained from ARMA (2,1) model. Hence, this model was considered as a better representative of the annual rainfall values and was used to predict five years ahead values. The mean absolute percentage error (MAPE) of the prediction was found to be less than 10%. Thus, ARMA (2,1) model could be used for forecasting and simulation of annual rainfall for planning, management and design of water resources systems in Debre Markos town.

Investigation of Physical and Numerical Model of Archimedes Screw Turbine

Archimedes screw turbines have been developed as they work with a low head with high efficiency, where flow energy can be exploited in small rivers, streams, regulators and others. The power can be produced using Archimedes turbines and depends on some parameters including the number of blades, flow, and angle of the shaft inclination and the length of the pitch. A physical and numerical model has been developed to determine the performance of the Archimedes turbine on the Ramadi Dam in Iraq. The physical model was made of stainless steel with the following parameters (length 1000 mm, pitch 70 mm, diameter ratio 0.536, inclination angles 30°, 35°, 40°, 45°). Work was carried out on different flow rates and inclination angles. The experimental results showed that the highest efficiency was 81.4% at 35° inclination angle and a flow rate of 1.12 l/s; the maximum power of 9.03 watts was at a 45° inclination angle and a flow rate of 2.065 l/s and 72% efficiency. Also, the impact of the pitch and the number of blades were studied. The results show that torque is increase with an increase in the pitch length, and torque is decreased with increase in several blades. The numerical results showed that the using of two blades led to a greater power produced. The comparison of the numerical and experimental results showed a good agreement, also the comparison with the published data showed a good agreement. As a final result the Archimedes screw has many positive points making it a good potential candidate. The results that emerged show the possibility of using this type of turbine in the Euphrates River in Anbar Governorate—Iraq, as the province is characterized by the presence of many regulators on the river in which turbines can be employed.

Assessment of Consumption Rate of Solid Biomass Fuels and the Consequent Environmental Impact in Maiduguri Metropolis

A proper assessment of the rate of unsustainable consumption of biomass fuel is important to determine the extent of the consequent environmental effects. In this paper, an evaluation was made of the rate of fuelwood (firewood and charcoal) consumption in Maiduguri metropolis, the capital of Borno state in Nigeria. Firewood and charcoal are the main solid biomass fuels consumed in Maiduguri city, in addition to rarely used animal dung, thatch, leaves, etc. These fuels are usually used in households, markets and industries for cooking, roasting and bakery activities. To quantify the rate of consumption of these fuels in Maiduguri (and their eventual negative effects), data were collected on the rate of supply of the biomass along highways leading to the city. The result shows a total consumption rate of 366 t/day of solid biomass fuel, with firewood accounting for 288 t/day and charcoal makes up the remaining 78 t/day. This fuelwood consumption rate is around 0.15% of the national figure. The resulting emissions of CO2, CH4, N2O, SO2, NOx, NMVOC, CO, NH3, PM10 and PM2.5 in kg/day are 433,488, 2160, 46, 83, 394, 2796, 34,699, 19.01, 5031 and 4884 respectively. Emissions of greenhouse gases stood at 497 t COe/day or 181,314 t CO2/year. A strategic shift to cleaner stoves and low carbon fuels is feasible and will enhance sustainable energy use.

Photosynthetic characteristics of intercropped winter wheat under limited supplemental irrigation in the semiarid northwestern China

A field experiment was conducted for intercropped winter wheat （Triticum aestivum） in 2002/2003 to evaluate the effects of limited supplemental irrigation on photosynthetic characteristics of intercropped winter wheat in semiarid environment. The result indicated that significances occurred in grain yield between the intercropped wheat treatments and sole wheat control （CKW）, and in yield between the irrigated intercropped wheat plots （WC2W, WC3W, WC5W） and not irrigated （WC1W） except for WC4W plots with nearly the same yield as WC1W. In comparison with CKW, 11.8%, 18.5%, 23.6%, 11.5%, and 30.7% of yield increase in the intercropped wheat plots were obtained in WCIW, WC2W, WC3W, WC4W, and WC5W respectively. Compared to the intercropped wheat plots without irrigation, yields in WC2W, WC3W, and WC5W were improved by 5.9%, 10.5%, and 16.9%, respectively. The dynamics of CGR and NAR in both intercropped （WC1W-WC5W） and solely cropped wheat （CKW） showed a type of ＂single peak＂ curves, with both the maximum CGR and NAR occurred during jointing to heading （14/4-6/5） of wheat. In addition, soil water potential （SWP） fluctuated as a function of the precipitation and limited supplemental irrigation.

Geometric Correction Analysis of Highly Distortion of Near Equatorial Satellite Images Using Remote Sensing and Digital Image Processing Techniques

The Near-equatorial orbit (NEqO) satellite represents a new generation of optical satellite images characterized by nonlinear distortion when captured. Conventional modeling techniques are insufficient to overcome the geometric distortion in these satellite images. This study proposes a new methodology for overcoming the geometric distortion of the NEqO images. The data used are obtained from RazakSAT and SPOT-5 satellite images in Malaysia. The method starts with applying the RI-SIFT algorithm to extract control points (CPs) automatically. These CPs are used to solve for the transformation parameters of the geometric correction model by applying spline transformations. The result is verified through statistical comparison: 1) geometric correction on the RazakSAT image is performed with Spot satellite image with using first-order polynomial trans-formation. 2) Then calculate the root mean square error (RMSE). 3) Compare the calculated RMSE with that obtained from the first step with that of the proposed method. The RMSE value of the geometric corrections using the proposed method was 7.08 × 10−9 m. The proposed method provides promising results.

青藏高原干旱与洪涝事件演变及应对关键问题

青藏高原是全球气候变化的敏感区,区域旱涝事件特性迥异,诱发了系列水安全和生态环境问题,亟须创新旱涝灾害适应性调控理论与方法.本文识别了青藏高原干旱与洪涝事件演变新情势,从旱涝监测模拟、预报预警、风险防控与应急处置等方面解析已有研究进展,发现存在多源数据融合不足、预报预警精度低、旱涝灾害链驱动机制不明晰和风险防控措施针对性不强等问题.在此基础上提出未来研究热点,并详细阐述水资源系统视角下青藏高原旱涝演变规律及遭遇特性识别、耦合数值模拟与知识挖掘的旱涝预测预警、旱涝灾害链风险阻断点识别与适应性调控等可能的研发路径,以期为青藏高原水旱灾害防治、水资源保护、生态修复及气候变化应对等提供技术支撑.

Evolution of drought and flood events on the Qinghai-Tibet Plateau and key issues for response

The Qinghai-Tibet Plateau is a climate-sensitive region.The characteristics of drought and flood events in this region are significantly different as compared to other areas in the country,which could potentially induce a series of water security,ecological and environmental problems.It is urgent that innovative theories and methods for estimation of drought and flood disasters as well as their adaptive regulations are required.Based on extensive literature review,this paper identifies new situations of the evolution of drought and flood events on the Qinghai-Tibet Plateau,and analyzes the research progress in terms of monitoring and simulation,forecasting and early warning,risk prevention and emergency response.The study found that there were problems such as insufficient integration of multi-source data,low accuracy of forecasting and early warning,unclear driving mechanisms of drought and flood disaster chains,and lack of targeted risk prevention and regulation measures.On this basis,future research priorities are proposed,and the possible research and development paths are elaborated,including the evolution law of drought and flood on the Qinghai-Tibet Plateau,the coincidence characteristics of drought and flood from the perspective of a water resources system,prediction and early warning of drought and flood coupled with numerical simulation and knowledge mining,identification of risk blocking points of drought and flood disaster chain and the adaptive regulations.Hopefully,the paper will provide technical support for preventing flood and drought disasters,water resources protection,ecological restoration and climate change adaptation on the Qinghai-Tibet Plateau.

Generation of rainfall data series by using the Markov Chain model in three selected sites in the Kurdistan Region,Iraq

Rainfall forecasting can play a significant role in the planning and management of water resource systems.This study employs a Markov chain model to examine the patterns,distributions and forecast of annual maximum rainfall(AMR)data collected at three selected stations in the Kurdistan Region of Iraq using 32 years of 1990 to 2021 rainfall data.A stochastic process is used to formulate three states(i.e.,decrease-"d";stability-"s";and increase-"i")in a given year for estimating quantitatively the probability of making a transition to any other one of the three states in the following year(s)and in the long run.In addition,the Markov model is also used to forecast the AMR data for the upcoming five years(i.e.,2022-2026).The results indicate that in the upcoming 5 years,the probability of the annual maximum rainfall becoming decreased is 44%,that becoming stable is 16%,and that becoming increased is 40%.Furthermore,it is shown that for the AMR data series,the probabilities will drop slowly from 0.433 to 0.409 in about 11 years,as indi-cated by the average data of the three stations.This study reveals that the Markov model can be used as an appropri-ate tool to forecast future rainfalls in such semi-arid areas as the Kurdistan Region of Iraq.