STUBBLE BURNING DETECTION USING MULTI-SENSOR AND MULTI-TEMPORAL SATELLITE DATA

被引:0
|
作者
Garg, Aseem [1 ]
Vescovi, Fabio Domenico [1 ]
Chhipa, Vaibhav [1 ]
Kumar, Ajay [1 ]
Prasad, Shubham [1 ]
Aravind, S. [1 ]
Guthula, Venkanna Babu [1 ]
Pankajakshan, Praveen [1 ]
机构
[1] Cropin Technol Solut Private Ltd, Bengaluru, Karnataka, India
关键词
Stubble burning; multi-sensor; multi-temporal; machine learning;
D O I
10.1109/IGARSS52108.2023.10282965
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Stubble burning is one of the major environmental hazards in almost all parts of the world. As agriculture became mechanized, combine harvesters leaves root-bound and scattered crop residues that are labor and cost intensive to remove, causing an increase in the recorded cases for burning of residues. The problem of stubble burning is more intense in the Indo-Gangetic Plain (IGP) of India due to highly mechanized farming practices, which leaves a huge amount of stubble in the field particularly after the harvest of rice. Traditionally, farmers collect crop residue to feed livestock manually. In this stubble burning study we explore the potential of the MODIS "MCD14DL-NRT" (Active Fire Data) product at a spatial resolution of 1000m available since November 2000, for the identification of fire prone areas in India. This study highlights the count of fire occurrences recorded from the MODIS Active Fire Data over a period of more than 20 years. During the months of October and November, which coincide with the paddy harvest season in the area an abrupt increase in fire activity is observed. The period of paddy harvesting, coupled with the onset of the winter season in the northern part of the country makes the region highly polluted and a breeding ground for numerous health problems for the citizens. In our study, we found that the state of Punjab records the majority of fires in India during this time period.
引用
收藏
页码:1606 / 1609
页数:4
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