Tillage direction analysis in agricultural fields from Digital Orthophotos and Sentinel-2 imagery

IF 3.8 Q2 ENVIRONMENTAL SCIENCES
Sebastian Goihl
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引用次数: 0

Abstract

For questions of soil and water protection, knowledge about agricultural management is relevant, especially in hilly and mountainous areas. In sloping areas, an area-wide knowledge of whether farming is done with or across the contour line would be very valuable for use in regional soil conservation management. In order to ascertain the prevalence of farming practices conducted with or against the slope in a given region, it is necessary to obtain data on the direction in which fields are cultivated. This information can be derived from remote sensing data through the application of geographic information system (GIS) methods. While previous studies have attempted to provide knowledge primarily through the use of small-scale but high-resolution Unmanned Aerial Vehicle (UAV) imagery, this study used medium-resolution imagery from satellite imagery (Sentinel-2 at 10 m × 10 m) and high resolution imagery (0.2 m × 0.2 m) Digital Orthophotos (DOP) from aircraft flights.
The use of medium-resolution satellite images (such as Sentinel-2) has yet to be explored in the context of addressing this research question, and this study represents their preliminary application in this domain. For this purpose, two GIS-based methods of analysis were proposed, which mainly made use of high-pass filtering, reclassification, vectorization, and compass orientation calculation. The results are promising, as in the best cases the correlation, between processing and ground truth orientation of the field tillage direction, for the DOP is R2 of 0.867 for 170 fields and 2.687 ha. For the Sentinel-2 evaluation, an R2 of 0.833 was obtained for 141 fields with 2.611 ha. Despite the different spatial resolution of both systems, the results are very comparable in terms of spatial coverage and accuracy of validation. However, for these two cases, this also meant that less than 50% of the total agricultural area and less than 20% of all fields in the study area could be covered. The data obtained from the DOP and Sentinel-2 sensors were collected at different times, resulting in the identification of distinct preferences for specific crop types. These preferences were observed to yield both accurate and less accurate evaluations, respectively. For instance, wheat exhibited favorable outcomes. Overall, the proposed approach demonstrated the capacity to derive area-wide information on farming direction with satisfactory results. Especially the temporarily high data availability of Sentinel-2 should be used to generate an overall picture using crop rotation and different phenological stages of arable crops in the long term.
利用数字正射影像和哨兵-2 图像分析农田耕作方向
对于水土保护问题,农业管理知识是相关的,特别是在丘陵和山区。在坡地,了解整个地区的耕作是沿着等高线进行还是越过等高线进行,对于区域土壤保持管理非常有价值。为了确定在某一地区沿坡或逆坡进行耕作的普遍情况,有必要获得有关田地耕作方向的数据。这些信息可以通过应用地理信息系统(GIS)方法从遥感数据中获得。虽然以前的研究主要是通过使用小型但高分辨率的无人机(UAV)图像来提供知识,但本研究使用了来自卫星图像的中分辨率图像(Sentinel-2在10米× 10米)和来自飞机飞行的高分辨率图像(0.2米× 0.2米)数字正射影像(DOP)。在解决这一研究问题的背景下,中分辨率卫星图像(如Sentinel-2)的使用还有待探索,本研究代表了它们在这一领域的初步应用。为此,提出了两种基于gis的分析方法,主要利用高通滤波、重分类、矢量化和罗盘方位计算。结果表明,在最好的情况下,处理与田间耕作方向的地面真值方向之间的相关性为,170块地和2.687公顷的DOP为R2 = 0.867。Sentinel-2评价结果表明,141块地、2.611 ha的R2为0.833。尽管两种系统的空间分辨率不同,但在空间覆盖和验证精度方面,结果非常相似。然而,对于这两种情况,这也意味着不到50%的农业总面积和不到20%的研究区域的所有领域可以被覆盖。从DOP和Sentinel-2传感器获得的数据是在不同时间收集的,从而确定了对特定作物类型的不同偏好。观察到这些偏好分别产生准确和不太准确的评估。例如,小麦表现出有利的结果。总体而言,所提出的方法证明了获得有关耕作方向的全区域信息的能力,并取得了令人满意的结果。特别是Sentinel-2的数据暂时高可用性,应长期利用作物轮作和不同物候阶段的可耕地作物来生成整体图像。
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来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
期刊介绍: The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
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