Algorithm for Detection of Cropping Pattern Analysis of Hisar-I & II Blocks of HISAR District Using Satellite Data & Dip Algorithm Model

Abstract

Cropping Pattern recognition has its roots in artificial intelligence and is a branch of machine learning that focuses on the recognition of patterns and regularities in data. Data can be in the form of image, text, video or any other format. Under normal scenario, pattern recognition is implemented by first formalizing a problem, explain and at last visualize the pattern. In contrast to pattern matching, pattern recognition algorithms generally provide a fair result for all possible inputs by considering statistical variations. Probabilistic classifiers have supported Agricultural statistical inference for decades. Potential applications of this technique in agriculture are numerous like pattern recognition from satellite imagery, identifying the type of disease from leaf image, weed detection. Agriculture resource is the most important renewable aspect and dynamic natural resource. The present research study reviews Algorithm for Detuction of Analysis in cropping pattern and crop rotation of Hisar-I and Hisar-II blocks, in the context of the developing algorithms and Digital Image Processing Models are used. The Present study deals with the Algorithm (Radiometric, Geometric correction of satellite data and DIP models for cropping pattern like Supervised, Unsupervised and Rule based Classification). Global Positioning System (GPS) used to identify the ground location of cropping pattern and Mx IRS LISS III digital data used to identify the Cropping pattern of Kharif, rabi and summer seasons of 2007-08. A rule based approach allows transparent monitoring of performed adaptation actions and gives an important advantage of easily modifiable adaptation process. NDVI of Satellite Images of each date is generated during classification. To improve accuracy, mask technique is used during classification. Season wise cropping pattern maps will be generated. The study successfully is identifying the cropping pattern & Crop Rotation of two blocks of Hisar district.