Cross Validation can Cause a Difference of Misinterpretation to Valid Interpretation
Easy availability of remote sensing dataset increases its importance and use by multiple folds, especially in areas of rough and difficult terrain like snow bound mountains. But at the same chances of misinterpretations will also be increased in the same proportion, when dealing with high altitude mountains in remote sensing. Seasonal variation within single year time framework and temporal changes in long time are more important to understand separately. Verification of the imagery selection, operations and findings is the key of analysis. This paper focused upon misinterpretation often occurs in the geospatial domain by shifting the focus, when observations transforming to information. A negligible error in selection of imagery, operation or perception make it possible to misinterpret the findings. In this study we are try to withdrawing kind attention of users toward small-small negligence, that cost a lot. In this study we take area under Nanda Devi national Park as an example to highlight such errors. As we observed a clearly change in vegetation cover as well as in snow cover on direct compression of satellite images from two different time frame in first operation. While in reality the change in snow cover is just because of seasonal snow fall is only become known after second operation. Such kind of misinterpretations are often in studies using geo-spatial technologies and remote sensing. Therefore, it must be required to validates and examine observations every time whenever reporting, our findings. And also requires to understanding about concepts properly prier interpret results and observation of any findings. Article like this useful to manager’s researcher and other remote sensing users in assessment, clarification and validations of their findings.
