Sustainable agriculture is the heart of organic farming, and human resources are playing a vital role in directing the community toward sustainable development in agricultural practices. The research objective is to evaluate the Farmer’s Knowledge (FK) in land suitability variables for crop type’s suitability in Perlis. After that, the collected spatial information variables applied to allocate the spatial distribution for four main crop types in Perlis. Besides that, to investigate farmer’s awareness in organic farming in achieving sustainable agriculture and at the same time to identify young participants in the agriculture field. Participatory Geographical Information System (PGIS) practices and mixed-method approach has applied to collect spatial data information in the study area. Spatial data interpolated using the Kriging method in GIS software. It found that soil types and soil suitability are the most important variables that classed by farmers in land suitability evaluation. The spatial distribution map of crop suitability has the potential to indicate agreement or conflict with a land resource development for the study area. The results show the farmer’s awareness in applying organic farming still low, with the percentage of applying organic fertilizer is 18%. Besides, the results indicate that the young generation has a small contribution, with 30% involved in the agriculture sector. Nowadays, the participation of the young farmers is more realistic in applied new technology for instance Precision Agriculture (PA) practices.

This paper studies the potential of satellite imagery in mapping of soil compaction and land suitability using Remote Sensing and GIS method. GIS and remote sensing, play an important role in environmental study, monitoring and remediation which can be used for a great variety of application. Soil compaction is important part in crop growth and the major causes for reduced crop yield worldwide. The aim of this study is producing the potential of land suitability map through measuring soil compactness for implementation of precision farming. In addition, it analyzes the correlation between soil compaction data and pixel value of satellite imagery. For this study, soil penetrometer tool are used to record data manually while digital analysis uses satellite images. A Landsat 5 TM and SPOT 5 images of Perlis were acquired to illustrate the use of Remote Sensing to identify areas of possible soil compaction. Soil sampling data was collected and simultaneously recorded the coordinate using GPS handheld. The correlation was analyzed in identifying areas of potential soil compaction using linear regression and polynomial. The farmers can used the product of soil suitability map to identify areas suitable for particular crops. Furthermore, to increase crop production through the use of integrated remote sensing, GIS, GPS and sensor technologies simultaneously maintaining the quality of the environment.