Early-season mapping of crops and cultural operations using very high spatial resolution Pléiades images     

《International Journal of Applied Earth Observation and Geoinformation》2015

The aim of this study was to assess the contribution of very high spatial resolution (VHSR) Pléiades images to both early season crop identification and the mapping of bare soil surface characteristics due to cultural operations. The study region covering 21 km² is located west of the peri-urban territory of the Versailles plain and the Alluets plateau (Yvelines, France). About 100 cropped fields were observed on the ground synchronously with two Pléiades images of 3 and 24 April 2013 and one SPOT4 image of 2 April 2013. The GIS structuring of these field data along with vector information about field boundaries was used for delimitating both training and test zones for the support vector machine classifier with polynomial function kernel (pSVM). The pSVM was computed on the spectral bands and NDVI for both single-date Pléiades and the bi-temporal Pléiades pair. For the single-date classifications of crops, the overall per-pixel accuracy reached 87% for the SPOT4 image of 2 April (6 classes), 79% for the Pléiades image of 3 April (6 classes) and 82% for that of 24 April (7 classes). At the earlier date (2–3 April), the Pléiades image very well discriminated cultural operations (>77%, user’s or producer’s accuracies) as well as fallows and grasslands, while winter cereals and rapeseed were better discriminated by the SPOT4 image winter cereals (>70%, user’s or producer’s accuracies). As Pléiades images revealed within-field spatial variations of early phenological stages of winter cereals that could be critical for adjusting management of zones with delayed development during the growing season, they brought information complementary to multispectral images with high spatial resolution. For the bi-temporal Pléiades image, the overall per-pixel accuracy was about 80% (7 classes), winter crops, grasslands and fallows being very well detected while confusions occurred between spring barley at initial stages (2–3 leaves) and bare soils prepared for other spring crops. Using an additional validation field set covering ∼1/3 of the study area croplands, the crop map resulting from the bi-temporal Pléiades pair achieved correct crop prediction for about 89.7% of the validation fields when considering composite classes for winter cereals and for spring crops. Early-season Pléiades images therefore show a considerable potential for anticipating regional crop patterns and detecting soil tillage operations in spring.  相似文献   

一类ENSO事件与四川地区粮食产量的相关分析     

肖天贵  胡毅  谌芸 《成都信息工程学院学报》1992,(4)

本文对1949年以来出现的10次ENSO事件进行了分析,得出如下结果:开始於东太平洋增暖和中大平洋增暖的两类ENSO现象分别对应四川地区粮食产量的减产和增产。此结果对四川地区粮食生产政策的制定及产量的预测研究均有较重要的参考价值。  相似文献   

我国高原干旱气候区作物种植区划综合指标体系研究   总被引：5，自引：2，他引：3  

邓振镛  李栋梁  郝志毅  龚建福 《高原气象》2004,23(6):847-850

在高原地区建立以气象、地理位置、经济效益等不同指标类型和权重系数的干旱气候作物生态适生种植区划综合指标体系,并以定量标准进行5级作物生态适生种植区划等级的划分。该综合指标体系具有实践性、经验性、客观性和应用性的特点。  相似文献   

Temporal-spatial Distribution of Suitable Areas for Major Food Crops in China Over 60 Years     

Xiaoju Ning  Lijun Zhang  Yaochen Qin  Kai Liu 《地球科学进展》2019,34(2):191-201

Simulating the temporal-spatial distribution of areas suitable for crops is an important part of analyzing the effects of climate change on crop growth, reducing the vulnerability of crop growth, and assessing the adaptability of crop growth to climate change. This study selected climate factors that affect the growth of wheat, maize and rice, and it combined surface soil and ground elevation factors as environment variables, as well as data from agricultural observation stations as species variables. The MaxEnt ecological model was used to identify suitable areas for these three crops during the period of 1953-2012. The areas suitable for the three crops were analyzed to determine the temporal-spatial distribution of major food crops and to estimate the difference in crop growth adaptability under climate change. The results showed the following: \mathrm{①} The response to climate change of the areas suitable for food crops could be ranked from strongest to weakest as follows: wheat, rice, and maize. \mathrm{②} On the same space-time scale, for the growth of wheat and rice, the southern agricultural regions, mountainous areas and plateaus were relatively unsuitable for a wider variety of crops than the northern agricultural regions, plains and basins. \mathrm{③} The adaptability of wheat increased in the major agricultural regions slightly. The adaptability of maize increased in the northern agricultural regions and decreased in the southern agricultural regions, respectively. The adaptability of rice was stable in the southern agricultural regions, and it decreased in the Huang-Huai-Hai region and increased in the northeastern region. \mathrm{④} Over 60 years, the ability of the major food crops to adapt to climate change increased in the northeast region, Gansu-Xinjiang region, Southwest region and Loess Plateau region, but the adaptability of major food crops decreased in the Huang-Huai-Hai region and the Mid-and-Lower Reaches of the Yangtze River. \mathrm{⑤} The suitable areas of maize and rice were significantly correlated with planting areas and yields, respectively, which provided feasibility for simulating the distribution of suitable areas on maize and rice in different climate scenarios in the future. The suitable area of wheat is not significantly related to the planting area and yield. In the future, we will take more factors to model the suitable area of wheat accurately.  相似文献   

In-season crop classification using elements of the Kennaugh matrix derived from polarimetric RADARSAT-2 SAR data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Accurate spatio-temporal classification of crops is of prime importance for in-season crop monitoring. Synthetic Aperture Radar (SAR) data provides diverse physical information about crop morphology. In the present work, we propose a day-wise and a time-series approach for crop classification using full-polarimetric SAR data. In this context, the 4 × 4 real Kennaugh matrix representation of a full-polarimetric SAR data is utilized, which can provide valuable information about various morphological and dielectric attributes of a scatterer. The elements of the Kennaugh matrix are used as the parameters for the classification of crop types using the random forest and the extreme gradient boosting classifiers.The time-series approach uses data patterns throughout the whole growth period, while the day-wise approach analyzes the PolSAR data from each acquisition into a single data stack for training and validation. The main advantage of this approach is the possibility of generating an intermediate crop map, whenever a SAR acquisition is available for any particular day. Besides, the day-wise approach has the least climatic influence as compared to the time series approach. However, as time-series data retains the crop growth signature in the entire growth cycle, the classification accuracy is usually higher than the day-wise data.Within the Joint Experiment for Crop Assessment and Monitoring (JECAM) initiative, in situ measurements collected over the Canadian and Indian test sites and C-band full-polarimetric RADARSAT-2 data are used for the training and validation of the classifiers. Besides, the sensitivity of the Kennaugh matrix elements to crop morphology is apparent in this study. The overall classification accuracies of 87.75% and 80.41% are achieved for the time-series data over the Indian and Canadian test sites, respectively. However, for the day-wise data, a ∼6% decrease in the overall accuracy is observed for both the classifiers.  相似文献   

Application of S-SEBI model for crop evapotranspiration using Landsat-8 data over parts of North India     

Abhishek Danodia  N. R. Patel  Choe Won Chol  B. R. Nikam  V. K. Sehgal 《国际地球制图》2019,34(1):114-131

Estimation and monitoring of crop evapotranspiration (ET_c) or consumptive water use over large-area holds the key to irrigation management plans and regional drought preparedness. The objective of this study was to estimate ET_c by applying the simplified-surface energy balance index (S-SEBI) model to Landsat-8 data for the 2014–2015 period in parts of North India. An average ET_c was estimated 2.72 and 2.47 in mm day^?1 with 0.22, 0.18 standard deviation and 0.11, 0.07 standard error for Kharif and Rabi crops, respectively. On validation part, a close relationship was observed between S-SEBI derived and scintillometer observed evaporative fraction with 0.85 correlation coefficient and 0.86 agreement index. The statistical analysis also endorses the results accuracy and reliability with 0.026 and 0.602, relative root-mean square errors and model efficiency for wheat crop, respectively. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of ET_c.  相似文献   

Mapping and assessing crop diversity in the irrigated Fergana Valley,Uzbekistan     

《Applied geography (Sevenoaks, England)》2017

Crop diversity (e.g. the number of agricultural crop types and the level of evenness in area distribution) in the agricultural systems of arid Central Asia has recently been increased mainly to achieve food security of the rural population, however, not throughout the irrigation system. Site-specific factors that promote or hamper crop diversification after the dissolvent of the Soviet Union have hardly been assessed yet. While tapping the potential of remote sensing, the objective was to map and explain spatial patterns of current crop diversity by the example of the irrigated agricultural landscapes of the Fergana Valley, Uzbekistan. Multi-temporal Landsat and RapidEye satellite data formed the basis for creating annual and multi-annual crop maps for 2010–2012 while using supervised classifications. Applying the Simpson index of diversity (SID) to circular buffers with radii of 1.5 and 5 km elucidated the spatial distribution of crop diversity at both the local and landscape spatial scales. A variable importance analysis, rooted in the conditional forest algorithm, investigated potential environmental and socio-economic drivers of the spatial patterns of crop diversity. Overall accuracy of the annual crop maps ranged from 0.84 to 0.86 whilst the SID varied between 0.1 and 0.85. The findings confirmed the existence of areas under monocultures as well as of crop diverse patches. Higher crop diversity occurred in the more distal parts of the irrigation system and sparsely settled areas, especially due to orchards. In contrast, in water-secure and densely settled areas, cotton-wheat rotations dominated due to the state interventions in crop cultivation. Distances to irrigation infrastructure, settlements and the road network influenced crop diversity the most. Spatial explicit information on crop diversity per se has the potential to support policymaking and spatial planning towards crop diversification. Driver analysis as exemplified at the study region in Uzbekistan can help reaching the declared policy to increase crop diversity throughout the country and even beyond.  相似文献   

基于冠层温度的作物缺水研究进展   总被引：35，自引：2，他引：35  

袁国富  唐登银  罗毅  于强 《地球科学进展》2001,16(1):49-54

冠导温度信息可以很好地反映作物的水分状况。自20世纪70年代以来，基于冠层温度的作物缺水指标的研究经历了三个阶段，即单纯研究冠层温度本身变化特征的第一阶段、以冠层能量平衡原理为基础的作物水分胁迫指数的第二阶段和考虑冠层和土壤的复合温度的水分亏缺指数的第三阶段。指标的局长也由使用手持式红外辐射仪信息扩大到使用航空和卫星遥感信息。这一类指标在点和区域尺度上均可应用。加强这一类指标的研究对于我国北方地区农作物的有效灌溉和区域水资源的管理都有重要意义。  相似文献   

遥感信息与作物生长模型的耦合应用研究进展   总被引：6，自引：0，他引：6  

邢雅娟  刘东升  王鹏新 《地球科学进展》2009,24(4):444-451

卫星遥感技术具有快速、宏观、准确、客观、及时、动态等特点,在大范围作物长势监测和产量预测等方面具有得天独厚的优势。但遥感监测常常受卫星遥感数据空间分辨率、时间分辨率等因素的影响,且遥感信息大多反映的是瞬间物理状况。作物生长模型是对作物生长、发育、产量形成过程中的一系列生理生化过程进行数学描述,是一种面向过程、机理性的动态模型。但是,当作物模拟从单点研究发展到区域应用时,由于随空间尺度的增大导致模型中一些宏观资料的获取和参数的区域化方面存在很多困难。
遥感信息与作物生长模型的耦合应用可以解决作物长势监测和产量预测等一系列农业问题,越来越受到相关研究人员的关注,已经逐渐成为一个重要的研究领域。因此,随着作物模型和遥感技术的迅速发展,如何将两者结合,进行互补性的研究是很有意义的。在查阅了相关资料的基础上,综述了遥感信息与作物生长模型的耦合应用以及发展历程,分别阐述了两种遥感数据与作物生长模型的结合方法——强迫法和同化法,总结了两类方法的应用情况。最后提出了该领域存在的问题,以及进一步解决的研究方向。  相似文献   

Efficacy of Rhizobia for Improving Photosynthesis,Productivity, and Mineral Nutrition of Maize          下载免费PDF全文

Muhammad Baqir Hussain  Zahir Ahmad Zahir  Hafiz Naeem Asghar  Rafia Mubaraka  Muhammad Naveed 《洁净——土壤、空气、水》2016,44(11):1564-1571

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