| Unsupervised zoning of cultivation areas with similar cultivation pattern in Golestan province based on the vegetation products of MODIS sensor |
| Paper ID : 1081-SMPR |
| Authors: |
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Fahimeh Youssefi *1, Mohammad Javad Valadan Zoej1, Alireza Safdari Nezhad2, Mahmod Reza Sahebi3 1Facalty of photogrammetry and remote sensing of K.N.Toosi university - Tehran - Iran 2Department of geodesy and surveying of Tafresh university - Arak - Iran 3Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology |
| Abstract: |
| The estimation of cultivation area and categorizing the agricultural product types is one of the prerequisites for achieving sustainable development in the agricultural studies. Due to wide spatial range, high temporal resolution and easy access of 16-day products of the vegetation of the MODIS sensor which acquired in a year , these images are used in this research. In the proposed method, after the generating of NDVI vegetation time series as a hyper-cube and separating farmlands’ boundaries in Golestan province using the land-use map; the Sequential Maximum Angle Convex Cone (SMACC) endmember extraction algorithm and the maximum number of product variation using the statistical information of the region (Obtained from the statistics center of Iran) are used to extract endmembers of the hyper-cube. In the following, the timing responses of the NDVI, identified as endmembers, will be refined in the second phase. In this process, identifying and eliminating noise signals (unrelated to cultivating patterns) and integrating the same cultivating patterns will be on the agenda. At the last stage of the proposed method and after refinement of the endmembers, the hyper-cube is clustered by Spectral Angle Mapper (SAM) algorithm. In the proposed method, the zoning of agricultural land is based solely on the statistical knowledge of the variety of cultivation and the results have led to the production of interconnected spatial parts. The visual comparison of results with large scale satellite images illustrates that there is a significant relationship between clustering results and ground truth in terms of cultivating pattern. |
| Keywords: |
| Cultivation area - Cultivation pattern – Clustering - Sequential maximum angle convex cone endmember extraction - Spectral angle mapper |
| Status : Conditional Accept (Poster) |
