Browsing by Author "Wogderes, Abiy"

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Detecting Land use/Land cover Change using Remote Sensing & GIS Techniques and Analysis of its Causes ,Consequences and trends in Ofla wereda, Tigray Region, Ethiopia
    (Addis Ababa University, 2014-06) Wogderes, Abiy; W/Tsadik, Muluneh (PhD)
    Land use/land cover (LULC) change is one of the challenges which strongly influence the process of agricultural development. The study intended to carry out land use /land cover changes, trends and their magnitude over the last 40 years using remote sensing and GIS and establish the main drivers of land use /land cover change in Ofla wereda of Tigray region. For the identification of land use/ land cover change landsat imagery of 1972, 1986 and 2013 were used to determine the change in land use/land cover using object based classification. In establishing the main drivers of land use/land cover change, the study utilized household questionnaire and a focus group discussion. A total of 362 respondents were randomly selected from the kebele’s where the land use/land cover change for the last 40 years is more than 60%, accordingly Sasela, Zata and Guara Kebeles were selected which satisfies the criteria. The object based classification result revealed that in 1972 MSS Landsat imagery, crop land (35.8%), grass land (19%), Forest land (43.7%) and water body (1.5%) were identified with their respective percentage. The change result showed a rapid reduction in forest cover of -49.2% and +18% increase occurred between the first (1972-1986) and second (1986-2013) study periods, respectively. Similarly water body decreased by -11.1% during the first and increased by +9.3% during the second period. On the contrary, crop land increased in the two periods by 31.7 % and 13.8% respectively. The analysis of the last 40 years in the study area revealed that about 48% of the landscape showed changes in LULC. Changes were also analyzed in relation to slope and agro ecological zone and it showed that in 1972, more than 69.2 % of the crop areas fall below 20° slope but in 2013 the percentage declined to 54.5% for the same slope indicating agriculture is expanding to the steep slopes and regarding agro ecological zone woina dega is more prone to change in the study area. From the analysis of the socio economic situation of households to identify the underlying causes of the change in land use/land cover, population growth and land tenure insecurity were identified as the major underlying causes. This study generally has shown that the recent advancement in spatial technology can provide a sound mechanism to quantify change at any scale. Keywords: GIS, LULC, MSS, Remote Sensing
  • No Thumbnail Available
    Item
    Spectro Agrometereological Maize Yield Forecast Model Using Remote Sensing and Gis in South Tigray Zone, Ethiopia
    (Addis Ababa University, 2014-05-05) Wogderes, Abiy
    For a country like Ethiopia whose economy is strongly dependent on rainfed agriculture; reliable, accurate and timely information on types of crops grown, their acreage, crop growth and Yield forecast are vital components for planning efficient management of resources. Remote-sensing data acquired by satellite have a wide scope for agricultural applications owing to their synoptic and repetitive coverage. This study reports the development of an operational spectro-agrometeorological yield model for maize crop derived from time series data of SPOTVEGETATION, actual and potential evapotranspiration, rainfall estimate satellite data for the years 2003-2012 which were utilized as input data for the indices while official grain yield data produced by the Central statistical Agency of Ethiopia was used to validate the strength of indices in explaining yield (quintal per hectare). One obstacle to successful modeling and prediction of crop yields using remotely sensed imagery is the identification of image masks. This process allows to consider only information pertaining to the crop of interest. Therefore crop masking at crop land area was applied and further refined by using agro ecological zone suitable for crop of interest(maize).Correlation analyses were used to determine associations between crop yield, spectral indices and agrometeorological variables for the maize crop of the longest rainy season (Meher). Indices with high correlation with maize yield were identified and were ready for further analysis, accordingly rainfall and average Normalized Difference Vegetation Index (NDVIa) have high correlation with yield (85% and 80% respectively). Many studies reported that linear regression modeling is the most common method to produce yield predictions by using remote sensing derived indicators together with bio climatic information. Statistical multiple linear regression model has been developed using variables which have high correlation with yield. Accordingly, NDVIa and rainfall were bring to the regression and lastly a regression model with P- value of less than 0.05 at 95 % confidence level were developed. The developed spectro-agrometerological yield model was validated by comparing the predicted Zone level yields (quintal per hectare) with those estimated by CSA(quintal per hectare). Very encouraging results were obtained by the model (r2 0.88 , RMSE 1.4 quintal/ ha and 21% CV). From this study we found that crop yield forecasting is possible using remote sensing and GIS in the fragmented agricultural lands of south Tigray. Since the data range we used for analysis was small we recommend application of the model after testing by newly appeared data with a long range of time series data before using for operational purposes.