农业作物套装和景观的变化:使用孟加拉国农村多光谱图像的时间序列研究

T. Mollah, Md. Ashraful Habib, Munia Tahsin, Naiem Mollah, Md Masuk Mowla Aunkur, Monalisha Ferdous, Sumaya Rahman Sumaya Rahman Shefa
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引用次数: 0

摘要

孟加拉国主要是一个农业国家,因此研究适合种植作物和景观的土地是至关重要的。大量或详细的研究,特别是在景观和作物对不同季节的适应性方面,是有限的。在这篇论文中,我们试图分析和评估沿泰塔斯河,孟加拉国的农作物种植和景观的年代性变化。在这项研究中,Brahmanbaria地区被视为2012年至2022年的案例研究期。主要数据来自384份问卷调查和10份fgd,次要数据来自CEGIS和BBS。Sentinel 2图像用于土地利用和土地覆盖(LULC)的制图和时序变化。在研究期间,拉比的水稻种植从31%下降到18%,导致冬季植被最多。然而,在kharifi季节没有明显的变化。除了水田种植(在Kharif-II期间从22%下降到18%)之外,变化很少。该研究确定了12个驱动变量,表明劳动力和资本可用性更重要,而农场规模对农业和景观变化的影响较小。Rabi、Kharif-I和Kharif-II的总体准确率分别为85.98、82.13和89.52%,kappa系数分别为84.90、86.37和82.50%。生产者准确率均在83.87%以上,除城市和工业外,用户准确率均在86.00%以上。Asiat。Soc。中国科学,49(1):85-100,2023年6月
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Changes in agricultural crop suits and landscape: a time-series study using multispectral imageries from rural Bangladesh
Bangladesh is predominantly an agricultural country, so studying suitable land for crops and landscapes is essential. Substantial or detailed studies, particularly on this aspect of the landscape and crop suitability for different seasons, are limited. In this paper, an attempt has been made to analyze and evaluate the chronological changes in agricultural crop suits and landscapes along the river Titas, Bangladesh. For the study, the Brahmanbaria district was considered as a case study period from 2012 to 2022. Primary data were obtained from 384 Questionnaire surveys and 10 FGDs, whereas secondary data were collected from CEGIS and BBS. Sentinel 2 images were used for mapping and chronological changes in Land Use and Land Cover (LULC). Between the study periods, paddy cultivation declined from 31 to 18% in Rabi, leading to maximum winter vegetation. However, there were no significant changes in the Kharif-I season. Except for paddy farming, which declined from 22% to 18% in Kharif-II, changes are few. This study identified 12 driving variables demonstrating that labor and capital availability were more responsible, whereas farm size was less responsible for determining agricultural and landscape changes. Rabi, Kharif-I, and Kharif-II had an overall accuracy of 85.98, 82.13, and 89.52%, respectively, with a kappa coefficient of 84.90, 86.37, and 82.50%. All classes were over 83.87% in producer accuracy, while all classes except urban and industrial were above 86.00% in user accuracy. J. Asiat. Soc. Bangladesh, Sci. 49(1): 85-100, June 2023
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