利用地理信息系统工具和遥感技术进行农田测绘的水稻收获技术范围

M. Hasan, M. Ali, C. Saha, M. Alam
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引用次数: 0

摘要

如今,现代农业已经受益于精准农业(PA)通过结合技术进步,如使用GIS(地理信息系统),RS(遥感),GPS(全球定位系统)和先进的信息处理。在GIS、RS和GPS的基础上,利用GIS和遥感无监督算法开发了稻田收割机适宜性分析的农田图。这项研究是在四个选定的地点进行的,分别是孟加拉国南部库尔纳、巴里沙尔、诺阿哈利-帕图阿卡利地区的杜穆里亚、瓦齐尔布尔、Subarnachar和Kalapara村的Kulbaria-Baratia、Mundopasha、Charwapda和Holdibaria村。GIS制图卫星图像采集于Boro-2018和Aman-2018植被阶段3 - 4月和10 - 11月。利用收割机和联合收割机的技术性能,根据GIS地图估算的耕地面积,确定所需收割机数量。计算所需数量的死神,b)迷你组合和c)介质结合来填补估计水稻面积是)17日和16日1和5,38 - 127,6 - 21日35 b)和32岁的3和10,76年和254年,13,42和c) 10日和9日,1和3,21日和72年4和12在米德尔斯堡和阿曼Kulbaria-Baratia季节,Mundopasha, Charwabda Holdibaria Dumuria, Wazirpur, Subarnachar和Kalapara upazilas,分别。估计结果表明,地理信息系统工具和遥感正在通过整合数据集帮助简化和可视化,这些数据集可以支持实施水稻收获技术的决策,以确保适当的农业机械化。在精度评估的基础上,发现GIS工具对机械收获面积与特定类型和数量的评估是非常有用的。可通过其他领域的进一步研究,为制定机械化采收政策提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scope of paddy harvesting technologies through cropland mapping using GIS tools and remote sensing
Nowadays, modern agriculture has benefited from Precision Agriculture (PA) through incorporation of technological advances like the use of GIS (Geographic Information Systems), RS (Remote Sensing), GPS (Global Positioning System) and advanced information processing. Based on the GIS, RS and GPS, a study was conducted to develop a cropland map using GIS and remotely sensed unsupervised algorithm for suitability analysis of paddy harvester. The research was carried out at four selected locations such as Kulbaria-Baratia, Mundopasha, Charwapda, and Holdibaria villages of Dumuria, Wazirpur, Subarnachar and Kalapara upazilas of Khulna, Barishal, Noakhali Patuakhali districts, respectively in the southern Bangladesh. The satellite images for GIS mapping were captured at vegetation stage of Boro-2018 and Aman-2018 during March-April and October-November. Technical performances of reaper and combine harvester were used to determine the required number harvester based on the estimated cultivated area found through GIS maps. The calculated required number of a) reaper, b) mini combine and c) medium combine to cover the estimated paddy area are a) 17 and 16, 1 and 5, 38 and 127, 6 and 21, b) 35 and 32, 3 and 10, 76 and 254, 13 and, 42 and c) 10 and 9, 1 and 3, 21 and 72, 4, and 12 during Boro and Aman seasons at Kulbaria-Baratia, Mundopasha, Charwabda and Holdibaria of Dumuria, Wazirpur, Subarnachar and Kalapara upazilas, respectively. The estimated results revealed that GIS tools and remote sensing are helping in simplification and visualization by incorporating data sets which can supports decision making for the implementation of paddy harvesting technologies in order to ensure the proper agricultural mechanization. Based on the accuracy assessment, GIS tool is found very useful to assess area to be harvested mechanically with specific type and number of harvester. It can be considered for formulating mechanized harvesting policy through further research in other areas.
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