What is it about?
Our study is a first of its kind in using Fractal method in time-series MODIS data. It reveals interesting results which can be potentially used to extract agriculture information over vast area especially over Mountainous terrain, automatically. The challenge is how can we know whether agriculture is there inside a 250x250 sq.m coarse pixel or not? Generally we do not find big patches of agriculture in Mountain terrain. It is generally get mixed with plantation and forests. Hence out study opens up a new domain of fractal based time-series analysis.
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Why is it important?
Living in the Mountain area for a life time is a tremendous challenge. Recently, a huge migration pattern is seen among the young people from Mountain area moving to cities in the Plain area because of job opportunity and enhanced living condition. This has put a tremendous pressure on the future sustainability and food security of families and elders residing in the Mountain regions because of reduction in the young agriculture manpower. What will happen if every youngster move from Mountain?. Can we capture the agriculture pattern using Satellite data. Yes of course we can map but there are problems in the mountain area in accurately extracting agriculture area. Time-Series data provides an opportunity but again it is coarse. So there is a real challenge in deriving this important information about Mountain Agriculture Dynamics.
Perspectives
MODIS time-series data has been used for various activities. But no major study is done over mountain agriculture. Considering the issues of Mountain area we decided to first address the important problem of food security in mountain region. In order to address this issue we need to have a proper data about agriculture spread. Most of the studies using remote sensing data did not pay much attention to this issue. Hence we decided to take up this challenge of extracting agriculture area from time-series data. The limitations and challenges in doing this are explained in our Published paper. Our work gives an interesting approach utilising FRACTAL INFORMATION about growth characteristics of various land cover features using time-series NDVI measure which is an indirect indicator of vegetation vigour. Our study is a first of its kind in using Fractal method in time-series MODIS data. It reveals interesting results which can be potentially used to extract agriculture information over vast area, automatically.
Dr. Jeganathan Chockalingam
Birla Institute of Technology
Read the Original
This page is a summary of: Mountain agriculture extraction from time-series MODIS NDVI using dynamic time warping technique, International Journal of Remote Sensing, March 2018, Taylor & Francis,
DOI: 10.1080/01431161.2018.1444289.
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