Estimation of Land Surface Temperature Using Landsat by Split Window Algorithm: A Case Study in Bahir Dar Zuria, Ethiopia

Urbanization is global issue that have both positive and negative impact on environment. With the modern development the rural of world changed to urban it may change the livelihood of the nation.in the other hand the rural poor migrating to urban areas this is the negative impact of urbanization in urban area. In the other hand it influencing temperature raise in the city area when compared with surrounding rural. The peri-urban area of Bahir dar is converted to city center, agricultural in around the city gradually converted to residential area. The agricultural land and vegetation in peri-urban of the city converted to different land use, industrial zone, residential. This proses negative impact on the city condition with rise of land surface temperature. Large area of peri-urban of Bahir dar city is surrounded by different industrial zone.This study found that the land surface temperature is increasing gradually between the selected study periods (1995 to 2016).  The mean temperature estimated between the selected years are varied depending on the factor considered. The result of this study shows that the mean temperature of the area was 25.7°C in 1995 which became 25.9°C in 2001 and down to 26.4°C in 2010, the temperature in 2016 estimated 28.7°C. The Temperature change between 11 years study periods revealed that 3 °C increased. The correlation between air temperature observed during the study period from meteorological station and estimated land surface temperature is found positively correlated with a R2 value of 0.84 in 2010 the other year are not done because of the absence of metrological data at the study period. The study found that green space in city center, wetland and water body is very important to moderate land surface temperature.  The mayor of municipality have to keep the existing wetland and green space in city center. Keywords: LST, NDVI, Climate variability, Climat

Accuracy analysis and Calibration of Total Station based on the Reflectorless Distance Measurement

Abstract Reflectorless EDM technology uses phase measuring or pulsed lasers to measure targets of a reflective and non-reflective nature. Reflectorless distance measurement provides rapid measurement by saving time and labour for surveyors. However, the accuracy of these types of measurements is under question because of the variety of constraints that affect the measurement. This paper attempts to show the techniques of total station calibration and to investigate the possible sources of error in reflectorless distance measurement. As a result, the effects of different color targets and angle incidence on distance measurement were checked. The precision of reflectorless distance measurement also investigated. In addition, comparison was made for manual and automatic target recognition measurement. Further experiment was performed on how to calibrate the total station instrument and the performance of the instrument was checked by KTH-TSC software. The experiments were evaluated by taking the reflector reading as ‘true value’ to check the accuracy of reflectorless measurement. The effects of colour surfaces on distance measurement have no significant difference. Besides, the result shows that the error in distance increased as the angle of incidence in the target increases. The result also indicates that automatic target recognition mode is the most advisable technique for precise measurement. Finally, an optimal number of seven target points was found for the calculation of prism constant.Sammandrag Reflektorlös EDM-tekniken använder fas mätning eller pulsade lasrar för att mäta mål en reflekterande och icke-reflekterande karaktär. Reflektorlös avståndsmätning ger snabb mätning genom att spara tid och arbete för inspektörer. Emellertid är noggrannheten hos dessa typer av mätningar under fråga på grund av olika begränsningar som påverkar mätningen. Denna uppsats försöker visa de metoder för totalstation kalibrering och att undersöka eventuella felkällor i reflektorlös avståndsmätning. Som ett resultat var effekterna av olika färger mål och vinkel inverkan på avståndsmätning kontrolleras. Noggrannheten i reflektorlös avståndsmätning undersökt också. Dessutom gjordes jämförelse för manuell och automatisk måligenkännande mätning. Ytterligare experiment utfördes på hur man kalibrerar totalstationen instrumentet och prestanda instrumentet kontrollerades av KTH-TSC programvara. Experimenten utvärderades genom att reflektorn läsning som "sanna värdet" för att kontrollera riktigheten i reflektorlös mätning. Effekterna av färgytor på avståndsmätning har ingen signifikant skillnad. Dessutom visar resultatet felet i avståndet ökade infallsvinkeln i målet ökar. Resultatet visar också automatiskt måligenkännande läget är det mest lämpligt tekniken för exakt mätning. Slutligen ett optimalt antal av sju målpunkter hittades för beräkning av prismakonstanten

Impacts of Soil and Water Conservation Practice on Soil Moisture in Debre Mewi and Sholit Watersheds, Abbay Basin, Ethiopia

Soil and water conservation (SWC) practices have been widely implemented to reduce surface runoff in the Debre Mewi watershed. However, studies on the issue have disproportionately focused on the lost or preserved soils, expressed in tons per hectare, while the impacts on the lost or preserved moisture were inadequately addressed. This study aimed to investigate the impacts of soil and water conservation practice on soil moisture in the Debre Mewi and Sholit watersheds, Abbay basin, Ethiopia. We compared soil moisture between the treated (Debre Mewi) and the untreated (Sholit) watersheds with SWCs, based on Sentinel-1A data and the field-measured soil moisture, Leaf Area Index (LAI), and water cloud model (WCM). Field-measurement was based on satellite-synchronized 63 soil moisture samples, systematically collected from the two treatment slope positions, two treatment positions, and two depths. We employed ANOVA to compare samples and discern patterns along space and time. The result indicated that the LAI, a predictor of crop yield, was higher in the SWC treated watershed, demonstrating the potential of conserving moisture for boosting crop production. In addition, the results reveal that the higher soil moisture was recorded on the grasslands of the treated watershed at a depth of 15–30 cm, while the lowest was from croplands and eucalyptus trees at 0–15 cm depth. A higher correlation was observed between the measured and estimated soil moisture across three stages of crop development. The soil moisture estimation using WCM from the Sentinel-1 satellite data gives promising results with good correlation (R2 = 0.69, 0.43 and 0.75, RMSE = 0.16, 2.24 and 0.02, and in Sholit (0.7539, 0.933, and 0.3673 and the RMSEs are 0.17%, 0.02%, and 1.02%) for different dates: August, September, and November 2020, respectively. We conclude that in the face of climate change-induced rainfall variability in tropical countries, predicted to elongate the dry spell during the cropping season, the accurate measurement of soil moistures with the mix of satellite and in-situ data could support rain-fed agriculture planning and assist in fine-tuning the climate adaptation measures at the local and regional scales