# Education and Training in Applied Remote Sensing in Africa: The ARCSSTE-E Experience
## 3 Feedback from Participants  
ARCSSTE-E uses two independent surveys to collect feedback from participants. The first survey, which is an \"in-training survey\", was introduced to the PGD programme of ARCSSTE-E in 2009. This anonymous survey is conducted at the end of each of the common and core modules of the PGD programme to appraise the learning experience of the participants. The second evaluation by the participants, which is a \"post-training survey\" for alumni, was introduced in 2012 [10]. The survey for the alumni is designed to assess the impact of the training program of ARCSSTE-E on the professional life of each participant. This section deliberates on the outcome of a post-training survey that was conducted on the alumni of the PGD programme of ARCSSTE-E in 2019. For this survey, questionnaires were distributed to about 200 alumni via their emails. Thirty-eight alumni, including 27 males and 11 females, responded to the on-line \"post-training survey\". These respondents were drawn from eight countries: Botswana, Cameroon, Ethiopia, Ghana, Kenya, Liberia, Nigeria, and Zimbabwe. Figure 5 shows the geographic distribution of the respondents. The survey participants who were young professionals, with an average age between 25 and 44 years, included military personnel, health workers, meteorologists, engineers, and scientific officers from Space Agencies. Figure 6 shows the distribution of the respondents according to the sectors in which they work. The \"post-training survey\" was designed to assess the impact of the PGD programme on the work and career of the alumni, and to discover how the program enhanced the application of remote sensing data in their place of work. A total of 85% of the survey participants acknowledged a positive impact of the training program at ARCSSTE-E on their professional life. When the alumni were asked to specify the environmental areas that they have applied the knowledge and skills gained from the training in remote sensing at ARCSSTE-E, 41% of the respondents indicated that they apply remote sensing in land management. Other identified areas of remote sensing in their work applications included disaster management (39%), water resource management (37%), ecology (21%), and air pollution (11%). Figure 7 depicts the environmental areas in which the alumni specified use of the knowledge and skills that were gained from their training in remote sensing at ARCSSTE-E.  
Figure 5: Number of ARCSSTE-E survey respondents per country. There were 38 participants from eight African countries. Figure 6: The distribution of the ARCSSTE-E’s survey respondents according to self-identified work sectors (N = 38). The impact of the PGD programme on the work and career of the alumni is further expatiated by the following quotations from the alumni survey: \"I am currently working with the Forestry Commission of Ghana as a GIS/Mapping officer. I run image classification to produce landuse/landcover maps, and landuse/landcover change maps to assess the forest cover in the country. I also developed a geo-database for the forest reserves and other natural resources. The skills and knowledge that I gained during my postgraduate studies at ARCSSTE-E have helped me in performing these tasks\". Another alumnus stated that he applies \"the knowledge of remote sensing using Unmanned Aerial Vehicles (UAVs) to carry out mapping, real-time surveillance in military operations, and I also apply GIS techniques in updating topographical maps using satellite imageries or drone data (Orthophoto)\". Furthermore, in the educational sector, one alumnus indicated that he \"once got a job as a geography teacher in an international secondary school, only to realise that remote sensing had been included in the curriculum. I was employed because of my RS/GIS certificate acquired at ARCSSTE-E, as this topic is alien to most geography teachers\". On the use of remote sensing data, 69% of the participants indicated the integration of remote sensing data in their operational environment.