*4.2. Results from SmartSkeMa*

Stakeholder impressions of the SmartSkeMa application were sought along three main dimensions: (1) ability to support conventional land tenure recording activities, (2) ability to facilitate community driven land tenure recording systems, and (3) applicability in other land administration functions. SmartSkeMa was generally judged to have the necessary functionality to support standard land tenure recording activities. Among 21 participants, 16 considered SmartSkeMa to be usable together with standard land administration systems, while two considered this to not be the case and three were ambivalent (they neither agreed nor disagreed to the statement). In addition, of the 21 participants, 18 agreed that the functionality of SmartSkeMa is useful for recording land tenure information while three mentioned that it was only partly useful for that purpose. The participants also indicated the reasons for their judgements or choice. Table 2 shows a summary of these data coded into themes as presented by the participants.


**Table 2.** Summary of participants perceptions in the usefulness of SmartSkeMa for land tenure recording.

In terms of facilitating community driven land tenure recording systems SmartSkeMa was considered more favorably. Of the 21 participants, 18 believed that SmartSkeMa could support communities to register and govern their lands according to local customs. There was no clear agreement on which other land administration tasks the SmartSkeMa application could be applied to. Several tasks stood out with land use documentation and land use planning mentioned by six participants; recording of historical and inaccessible information was mentioned by four participants; and aiding surveying and other traditional land information collection was mentioned by three participants. Finally, we asked the participants to perform a SWOT analysis of the tool based only on the functionalities that have been presented to them during the demonstration. The results of this analysis are shown in Table 3 below.

**Table 3.** SWOT results on SmartSkeMa.


The feedback obtained from the workshops laid the foundation for the development of the second method: use an aerial image as the background for a sketching exercise. This is expected to increase the precision and provide measurable accuracy. The alignment of a sketch traced on top of an aerial image is done by a 6-parameter affine transformation. The parameters for the transformation are estimated by ordinary least squares linear regression quadratic features.

The new method was tested on a small sample of parcels and three metrics were taken as shown in Table 4. The time for delineation cannot be compared with traditional method since the time to produce the parcels is mostly consumed by the field work. As field work is required to collect parcel information in other approaches as well, we conclude that the automatic delineation of sketch maps results in a faster process.


**Table 4.** Performance metrics of parcel delineation using SmartSkeMa's sketch-on-map.
