Spatial big data analytics for sustainable intensification of pulse crops in South Asia
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Chandrashekhar Biradar, Rajkumar Singh, Mukunda Behera, Ashutosh Sarker, Shiv Kumar Agrawal, Xiangming Xiao, Geli Zhang, Khaled El-Shamaa, Girish Pujar, Layal Atassi, Sat Kumar Tomar, Prasenjit Acharya, Rabi Sahoo, Nigamananda Swain, Jalal Omary, Praveen Prajapati, Rajib Nath, Parvesh Chandna, Murali Krishna Gumma, Abhineet Jain. (7/5/2018). Spatial big data analytics for sustainable intensification of pulse crops in South Asia.
Abstract
Sustainable intensification has become a foremost goal of agricultural research and development in the
recent years. The mono-crop based production systems in South Asia retains nearly 30 percent of
cultivated area left as fallows, while demand for the nutritional food grains continues to rise. Several
initiatives are underway towards bridging the gaps and achieving sustainable food as well as nutritional
security. One of the opportunities lies in the potential use of the crop-fallows for growing pulses. The
lentil, grasspea and chickpea are most preferred food legume crops for fallow intensification. However
often lack of the adequate and updated information on the crop follow areas, its dynamics, soil
moisture, suitability range, etc. lead to poor intervention on the ground level. The recent advances in
harnessing the power of big-data analytics, artificial intelligence and machine learning with access to
near real-time remote sensing, in-situ observations including drones, soil moisture, water harvesting
provided a unique capability for quantifying suitable matrix for intensification of pulses such as lentil,
grasspea and chickpea in the rice-fallows. The dynamics of the rice fallows has been mapped using
multi-source satellite data (MODIS, Landsat, Sentinel, Worldview, SMOS, AMSR-E and UAVs/drones) and
in-situ observations. The hotspots (priority areas) were delineated with respect to multi-year maps
(2000-2016) of fallow dynamics such a start and end dates, length of the fallows, biophysical parameters
for specific pulse crops and varieties. The high-resolution farm typology was built along with soil
moisture regimes and suitable area for rain water harvesting for providing supplemental irrigation
during dry season. Resultant big data analytics envisage empowering decision makers, researchers,
extension systems and farmers by providing a holistic perspective to fine tune decisions and actions
from on-ground implementation to resource management, sustainable intensification and values chains.
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Author(s) ORCID(s)
Biradar, Chandrashekhar https://orcid.org/0000-0002-9532-9452
Singh, Rajkumar https://orcid.org/0000-0002-3576-8971
Sarker, Ashutosh https://orcid.org/0000-0002-9074-4876
Agrawal, Shiv Kumar https://orcid.org/0000-0001-8407-3562
El-Shamaa, Khaled https://orcid.org/0000-0002-7668-3798
Atassi, Layal https://orcid.org/0000-0002-7271-7591
Swain, Nigamananda https://orcid.org/0000-0001-9593-4911
Singh, Rajkumar https://orcid.org/0000-0002-3576-8971
Sarker, Ashutosh https://orcid.org/0000-0002-9074-4876
Agrawal, Shiv Kumar https://orcid.org/0000-0001-8407-3562
El-Shamaa, Khaled https://orcid.org/0000-0002-7668-3798
Atassi, Layal https://orcid.org/0000-0002-7271-7591
Swain, Nigamananda https://orcid.org/0000-0001-9593-4911