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Nt1310 Unit 2 Rqs

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The focus of this section, will be collection and analysis of the data for the two RQs. First, I will state the needed data for each RQ, potential sources and process of analyzing it. For instance, estimation of desertified area or ESAs (Environmentally Sensitivity Areas) (11) for each year –1994, 2004 and 2014 – will be based on four indicators (NDVI, Albedo, Soil moisture and Sand dunes). The selection of these indicators based on many studies. For instance, the selection of the best indicators to monitor and assess the desertification in arid and semiarid region seen a lot of evolution. For the OECO the desertification is process of pressure, state and response (PSR) while the FAO, UNCCD and European commission for dry land (12) look the desertification process as results of five steps: Driving forces, pressure, state, impact and responses (DPSIR). …show more content…

For this case study, I selected these indicators because they met indicator evaluation criteria for UNCCD (15) and the SMART concept – Specific, Measurable, Achievable, Relevant and Time-related. The indicators estimation will depends on the Remote Sensing (RS) data. As explained in (16a), the RS (Landsat) data is suitable for quantification of spatio-temporal desertification or (ESAs) because it allows researcher to go back and examine the change. Here, I should mention that desertification is a slow process which takes years to happen (17a). For the RS data, I will request the Landsat data for Biskra for three years. (1994, 2004 and 2014). The RS imagery will be preprocess it in order to get a maximum accuracy. The preprocess mean will be ERDAS imagine software and possible GIS

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