Abstract
Abstract. Agricultural intensification is defined in terms as cropping intensity, which is the numbers of crops (single, double and triple) per year in a unit cropland area. Information about crop calendar (i.e. number of crops in a parcel of land and their planting & harvesting dates and date of peak vegetative stage) is essential for proper management of agriculture. Remote sensing sensors provide a regular, consistent and reliable measurement of vegetation response at various growth stages of crop. Therefore it is ideally suited for monitoring purpose. The spectral response of vegetation, as measured by the Normalized Difference Vegetation Index (NDVI) and its profiles, can provide a new dimension for describing vegetation growth cycle. The analysis based on values of NDVI at regular time interval provides useful information about various crop growth stages and performance of crop in a season. However, the NDVI data series has considerable amount of local fluctuation in time domain and needs to be smoothed so that dominant seasonal behavior is enhanced. Based on temporal analysis of smoothed NDVI series, it is possible to extract number of crop cycles per year and their crop calendar. In the present study, a methodology is developed to extract key elements of crop growth cycle (i.e. number of crops per year and their planting – peak - harvesting dates). This is illustrated by analysing MODIS-NDVI data series of one agricultural year (from June 2012 to May 2013) over Gujarat. Such an analysis is very useful for analysing dynamics of kharif and rabi crops.
Highlights
Agriculture is one of the most important sectors for India
The present study demonstrates the use of temporal Normalized Difference Vegetation Index (NDVI) data in extracting key phenological information calendar by interpreting temporal variations in spatial domain to generate crop calendar
For further refinement land use land cover (LULC) mask for Gujarat state provide by NRDB database was used. These LULC was made by IRS AWiFS data source and 1:250,000 scale agricultural layer were created for making agriculture mask for India
Summary
It is necessary for our country to arrange enough food for the people of our country. Proper planning for this sector requires relevant and reliable information in timely manner. Planning commission of India recognizes the crucial role of remote sensing (RS) technology in generating quality crop statistics (Gupta and Rajan, 2009). India is one of the few select countries which have a reliable system of generating forecast of crop production using RS and other collateral sets of data. Since crop is a very sensitive biological system which is affected by many biotic and abiotic factors, it is essential to have dynamic assessment crop condition so that crop growth cycle can be simulated and reliable forecasts of crop production can be generated and/or modulated
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