Abstract
Abstract. Change detection is important to understand the patterns of transition in multi-temporal SAR acquisitions over same geographical areas. In this work, we implemented a test statistic on covariance matrices for change detection. The RADARSAT-2 data spanning the agricultural land of Central Hisar Farm in Haryana, India was used. Hypothesis testing on test-statistic was done by a pre-decided significance level. A change map was plotted and the areas with ‘change’ and ‘no change’ were determined. Analysis of changing trends of different crop lifecycles is done. This study is useful in making important agricultural crop predictions.
Highlights
1.1 General introductionChange detection in SAR images has become a crucial part of recent works in remote sensing
Various approaches ranging from the algebraic methods of image differencing and ratio [1] to the supervised methods of classification [2] and to the more recent unsupervised methods based on statistical and probabilistic approaches of test statistic [3][4] for change detection can be found in the literature
We implemented hypotheses testing on a test statistic for change detection in SAR images of an agricultural area
Summary
Change detection in SAR images has become a crucial part of recent works in remote sensing. Various approaches ranging from the algebraic methods of image differencing and ratio [1] to the supervised methods of classification [2] and to the more recent unsupervised methods based on statistical and probabilistic approaches of test statistic [3][4] for change detection can be found in the literature. The test statistic has proven to be a very simple and efficient method.
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