Predicting the spatiotemporal changes of an agriculturally vulnerable region of Bangladesh

IF 2.3 Q2 REMOTE SENSING
Sayeda Laizu Aktar, Moon Islam, Afsana Haque
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Abstract

Agricultural land, the primary factor of food production, is essential for ensuring food security. Land constraints have led policymakers to promote agricultural intensification to achieve higher production, which is no longer sustainable. In Bangladesh, the consistent decline of agricultural land at a regional scale is a rising concern for food security. This study intends to assess the spatiotemporal changes in agricultural lands concerning food security, including temporary cropland, permanent cropland, and fallow land. LANDSAT satellite imagery for 1995, 2010, and 2022 were categorized using a hybrid image classification method. However, the study limits to produce higher accuracy as compromised due to the spatial resolution of LANDSAT imagery. MLP-CA Markov chain model was used to predict the agricultural land for 2041 by employing driver variables. The study finds around 15% loss in agricultural land from 1995–2022 with significant losses (12%) between 2010–2022. The built-up area is doubled after each of the time periods. Temporary crop-producing lands are declining quickly and converted rapidly (around 30%) to built-up areas between 2010–2022. Notably, agricultural land near riverine zones rapidly converts to built-up areas, hinting at potential environmental consequences. The model predicts around 10% loss in agricultural land with a likely conversion around cities and riverine areas, driven by infrastructure development. Contradictory sectoral policies have driven such conversion without effective land use policy. Hence, the study implies formulating a physical plan and urbanization policy for growth control and management, as well as land zoning and master plan for protecting valuable agricultural land.

预测孟加拉国农业脆弱地区的时空变化
农业用地是粮食生产的首要因素,对确保粮食安全至关重要。土地制约因素导致决策者推动农业集约化,以实现更高的产量,但这已不再具有可持续性。在孟加拉国,区域范围内农业用地的持续减少日益引起人们对粮食安全的关注。本研究旨在评估与粮食安全有关的农业用地的时空变化,包括临时耕地、永久耕地和休耕地。采用混合图像分类法对 1995 年、2010 年和 2022 年的 LANDSAT 卫星图像进行了分类。然而,由于 LANDSAT 图像的空间分辨率有限,这项研究的准确性受到影响。研究采用 MLP-CA 马尔科夫链模型,通过驱动变量预测 2041 年的农业用地。研究发现,1995 年至 2022 年期间,农用地减少了约 15%,其中 2010 年至 2022 年期间农用地大幅减少(12%)。在每个时期之后,建成区面积都翻了一番。临时作物生产用地迅速减少,并在 2010-2022 年间迅速(约 30%)转化为建筑密集区。值得注意的是,靠近河流地带的农业用地迅速转化为建筑密集区,暗示着潜在的环境后果。根据模型预测,在基础设施建设的推动下,城市和沿河地区附近的农业用地可能会减少约 10%。相互矛盾的部门政策在没有有效土地利用政策的情况下推动了这种转化。因此,这项研究意味着要制定实体规划和城市化政策,以控制和管理增长,并制定土地分区和总体规划,以保护宝贵的农业用地。
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来源期刊
Applied Geomatics
Applied Geomatics REMOTE SENSING-
CiteScore
5.40
自引率
3.70%
发文量
61
期刊介绍: Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences. The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology. Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements
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