Data Input and Collection Training for Villages around Magepanda Watershed, Maumere, East Nusa Tenggara

Dagesime Magepanda watershed passes across many areas in East Nusa Tenggara. This watershed became important because its main function to support people who live around the river. Due of its importance, there should be some regulations to maintain and manage the existence of this watershed from the upstream down.

Picture of Dagesime Magepanda watershed from above (source:

The Caritas Diocese of Maumere (CKM) as a humanitarian organization is working on the documentation of watershed management plans. CKM aims to collect field data that can be used to support the making of the watershed management plan document. Assisting the data collection, CKM collaborated with Humanitarian OpenStreetMap Team (HOT) Indonesia organized series of training to support the documentation of Dagesime Magepanda watershed management plan.

This program is similar to the previous training held back in 2016. What makes this year’s training different is the focus area because there is one additional village, rising from 6 to 7 villages. The watershed Dagesime Magepanda spans across all 7 villages, located in 2 districts, Magepanda and Mego. The villages are Magepanda, Done, Parabubu, Kolisia B, Gera, Liakutu, and the new village, Reroroja.

This training consists of various activities started from April 24 until May 4, 2017. All activities were held in CKM office, Jl. Soegiyopranoto No. 1, Maumere, East Nusa Tenggara.

The purpose of this training was to complete all spatial data in each village. The new village (Reroroja) became the main location to observe because it does not have any spatial data yet. The other village also needs to collect more spatial data to complete all the data requested.  The requested data that need to be collected are:

  • Public facilities
  • Fountains
  • Households
  • Land use
  • Disaster risk

Trainings were separated into two phases, data collection and data input. Data collection training was held on April 24-25, 2017. One week after first training, the data input training was held on May 1-4, 2017.

The first training was attended by 2 representatives from each village who know about their village well. This is important because we need to collect all field data such as a fountain, points of interest from each village, so it will be more suitable if all the surveyor from each village are familiar with their neighborhood.

Kegiatan pelatihan pengumpulan data

Data collection training photos

In this training, all the participants learned how to collect field data using GPS and form survey. On 24 April 2017, all participants learned about GPS, function, and how to use GPS. Not only GPS, participants learned about how to use form survey to collect additional information of each object that will be surveyed later.

Example of form survey used for survey

After the theory, all participants must use their skills more often.  In order to do that, all participants must practice collecting data through the real survey near the area of training. On the last day (25 April 2017), HOT Indonesia and CKM lend them GPS and give them survey forms to collect data in their villages. All participants need to collect field data for 5 days and must report them on 1 May 2017 because the data will be needed to use in the next training.

All participants practice how to collect data through field survey

After the first training was done, on 1 May 2017, the participants from the first training gave the data to participants of the second training. Quite different from the first training, the participants for second training attended by village officials who have computer skills.

Training of input data, started from 1-4 May 2017

In the second training, all participants learned how to process data collected from the survey until they can produce a map based on the data gathered. The first thing to do was that they need to transfer the data from survey forms to excel sheets. After that, all participants learned how to input data based on GPS coordinate into OpenStreetMap. Next, participants were taught how to do a map layout, configure symbol for each object, and make a map using Map Composer in QGIS.

Example of GPS data collected by representative of Kolisia B village

The problem found in this training is the absence of Reroroja’s representative. Because of that, Reroroja village can not be mapped as well as the other village. As a solution, Reroroja’s representative replaced by the staff of CKM.

Photos from training of input data

Overall, the training can be organized well. At the end of the training, all participants have been able to map, input data and produce a map for each village. From all participants, Done, Kolisia B, and Liakutu village became the best village map from this training.

The village with the best map result. From left to right: Done, Kolisia B, Liakutu.

At the end of the training. all villages that don’t have any spatial data before now have their spatial data. You can check them in the OpenStreetMap too!

Reroroja village spatial data comparison before (left) and after (right) mapped using OpenStreetMap

Magepanda village spatial data comparison before (left) and after (right) mapped using OpenStreetMap