Site Assessment For Large Scale Oganic Agriculture Plot Using Integrated Geoinformatic and Sub-Global Assessment

Abstract

Organic agriculture has been currently promoted by the governmental policy to meet sustainable agriculture development. To enhance organic agriculture, Nong Wang Sok Phra, Phon District, Khon Kaen, Thailand has designated organic agriculture   plot covering the area of   2,000 rai (320 hectare) along the creek. It is necessary to identify boundary of organic agriculture plot with land use and perception of organic agriculture plot member. The objective of this research, thus, was to assess the large scale of organic agriculture plot by integrating Geoinformatic together with Unmanned Arial Vehicle and Sub-global Assessment (SGA).    The study steps and results are as follows.  Firstly, creating the study area and land use map with physical characteristics identified by photography and video record.  Secondly, establishing the systematic maps of large scale of organic agriculture. by criteria weighting and rating scale for analysis of land suitability, using  Geoinformatic and UAV Arial Photography  of 7 factors consisting of land use, soil suitability, water resource, transportation, average debt of village, acceptation of member, organic agriculture plot definition. Social study using SGA approach was carried out after getting   systematic by focus group interview on debt of farmers and acceptation of organic agriculture plot’s members.    Thirdly, Arial Photography taken from Unmanned Aerial Vehicle (UAV) for the potential large organic agriculture plot covering many land parcels.   Again, SGA identified the suitable plot ranked from the potential large organic agriculture plot.  Finally, with the overlay technic with processing UAV Imagery and parcel maps, the output was the map of suitable organic agriculture plot, located at Ban Kok Lam Village no.3, covering plot of 129 rai (20.64 hectare), where the agriculture parcels were belonged to 25 owners.  With technical and social acceptance would identify the actual organic agriculture area.