Monitoring and evaluation of effective climate parameters on the cultivation and zoning of corn agricultural crop in Iran (case study: Ardabil province)

Ghanbari, R.; Sobhani, Behrouz; Aghaee, Mahshid; nooshabadi, Amir oshnooei; Safarianzengir, Vahid

doi:10.1007/s12517-021-06807-y

Cited by 9 publications

(4 citation statements)

References 28 publications

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“…When attempting to use spectral differences (multi-band indices) for residue characterization, the influence of moisture on this process becomes more intricate. Under dry conditions, it is possible to distinguish the adsorption characteristics of crop residue from soil 80 . Well-calibrated broadband spectral indexes like Normalized Difference Tillage Index (NDTI) can accurately map CRC during such conditions.…”

Section: Discussionmentioning

confidence: 99%

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

Kazemi Garajeh,

Hassangholizadeh,

Bakhshi Lomer

et al. 2023

Sci Rep

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To the best of our knowledge, the impacts of crop residue cover (CRC) on agricultural productivity and soil fertility have not been studied by previous researchers. In this regard, this study aims to apply an integrated approach of remote sensing and geospatial analysis to detect CRC and monitor the effects of CRC on agricultural productivity, as well as soil chemical and physical characteristics. To achieve this, a series of Landsat images and 275 ground control points (GCPs) collected from the study areas for the years 2013, 2015, and 2021 were used. A convolutional neural network (CNN), a class of artificial neural network has commonly applied to analyze visual imagery, was employed in this study for CRC detection in two classes (Not-CRC and CRC) for the years 2013, 2015, and 2021. To assess the effects of CRC, the Normalized Difference Vegetation Index (NDVI) was applied to Landsat image series for the years 2015 (22 images), 2019 (20 images), and 2022 (23 images). Furthermore, this study evaluates the impacts of CRC on soil fertility based on collected field observation data. The results show a high performance (Accuracy of > 0.95) of the CNN for CRC detection and mapping. The findings also reveal positive effects of CRC on agricultural productivity, indicating an increase in vegetation density by about 0.1909 and 0.1377 for study areas 1 and 2, respectively, from 2015 to 2022. The results also indicate an increase in soil chemical and physical characteristics, including EC, PH, Na, Mg, HCO3, K, silt, sand, and clay from 2015 to 2022, based on physical examination. In general, the findings underscore that the value of an integrated approach of remote sensing and geospatial analysis for detecting CRC and monitoring its impacts on agricultural productivity and soil fertility. This research can offer valuable insight to researchers and decision-makers in the field of soil science, land management and agriculture.

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Section: Discussionmentioning

confidence: 99%

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

Kazemi Garajeh,

Hassangholizadeh,

Bakhshi Lomer

et al. 2023

Sci Rep

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“…They took Jiujiang sightseeing agricultural tourism resources as an example and used the analytic hierarchy process to evaluate Jiujiang agricultural tourism resources from the three levels of resource conditions, development conditions, and management conditions, trying to provide assistance for the development of Jiujiang sightseeing agricultural tourism [13]. Relevant scholars adopted multidisciplinary theories, an innovative and improved analytic hierarchy process, divided three project layers at the same time, and constructed a more complete ecological agricultural tourism resource evaluation system [14]. Relevant scholars take the value of Fujian ecoagricultural tourism as the research object and use 2…”

Section: Related Workmentioning

confidence: 99%

Intelligent Rural Tourism Environmental Suitability Evaluation System Based on a Wireless Sensor Network

Feng

2021

Journal of Sensors

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After years of vigorous development, the scale of rural tourism industry has gradually expanded throughout the country, and it has become an important means of coordinating urban and rural areas to drive farmers’ incomes and get rich. Nowadays, the level of informatization is constantly improving, the construction of smart cities is constantly advancing, the personalized demand of tourists is increasingly strong, especially the rural tourist spots scattered in the vast countryside which have a great spatial breadth, and the traditional management method can no longer meet the needs of the source objects whose main travel mode is self-driving. Therefore, only when rural tourism develops in the direction of intelligence can it successfully realize the transformation and upgrading of rural tourism industry. This paper takes a rural tourism resort in a certain area as the research object and builds an intelligent rural tourism environmental suitability evaluation system with three criterion levels: natural geographic conditions, traffic environmental conditions, and tourism spatial conditions. The weight of each indicator layer is obtained through the analytic hierarchy process, and the reclassified raster data of indicators is weighted and superimposed on the ArcGIS operating platform to obtain the evaluation result of the environmental suitability of smart rural tourism. According to the results of suitability evaluation, the most suitable area is selected as the potential area of the intelligent rural tourism environment in a certain area. According to the natural and cultural tourism resource conditions in the block, the potential block is divided into functions. A comprehensive comparison of the suitability spatial differentiation map of the smart rural tourism environment in a certain area with the suitability spatial differentiation map of each subsystem can more clearly find that the suitability score of the economic development subsystem and the basic support subsystem is a county-level village in a certain area. Among them, the suitability of the rural economic development subsystem is similar to the distribution of the suitability of the smart rural tourism environment in a certain area; that is, it is positively correlated with the suitability of the smart rural tourism environment. Therefore, improving the level of rural economic development and increasing investment in the construction of a smart rural tourism environment play an important role in improving the level of public services and infrastructure coverage.

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“…Population growth, climate change, and globalization are the main factors affecting water resources 1 . Among the main controlling factors, climate changes play a serious role when researchers evaluate both the quality and quantity of water resources 2 , 3 . Climate change is already affecting water access for people around the world, causing more severe droughts and floods.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal monitoring of climate change impacts on water resources using an integrated approach of remote sensing and Google Earth Engine

Kazemi Garajeh,

Haji,

Tohidfar

et al. 2024

Sci Rep

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In this study, a data-driven approach employed by utilizing the product called JRC-Global surface water mapping layers V1.4 on the Google Earth Engine (GEE) to map and monitor the effects of climate change on surface water resources. Key climatic variables affecting water bodies, including air temperature (AT), actual evapotranspiration (ETa), and total precipitation, were analyzed from 2000 to 2021 using the temperature-vegetation index (TVX) and Moderate Resolution Imaging Spectroradiometer (MODIS) products. The findings demonstrate a clear association between global warming and the shrinking of surface water resources in the LUB. According to the results, an increase in AT corresponded to a decrease in water surface area, highlighting the significant influence of AT and ETa on controlling the water surface in the LUB (partial rho of − 0.65 and − 0.68, respectively). Conversely, no significant relationship was found with precipitation and water surface area (partial rho of + 0.25). Notably, the results of the study indicate that over the past four decades, approximately 40% of the water bodies in the LUB remained permanent. This suggests a loss of around 30% of the permanent water resources, which have transitioned into seasonal water bodies, accounting for nearly 13% of the total. This research provides a comprehensive framework for monitoring surface water resource variations and assessing the impact of climate change on water resources. It aids in the development of sustainable water management strategies and plans, supporting the preservation and effective use of water resources.

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Monitoring and evaluation of effective climate parameters on the cultivation and zoning of corn agricultural crop in Iran (case study: Ardabil province)

Cited by 9 publications

References 28 publications

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

Intelligent Rural Tourism Environmental Suitability Evaluation System Based on a Wireless Sensor Network

Spatiotemporal monitoring of climate change impacts on water resources using an integrated approach of remote sensing and Google Earth Engine

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