CN103033150A - Method for quickly extracting main crop planting area through utilization of moderate resolution imaging spectroradiometer (MODIS) data - Google Patents
Method for quickly extracting main crop planting area through utilization of moderate resolution imaging spectroradiometer (MODIS) data Download PDFInfo
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- CN103033150A CN103033150A CN2011103023336A CN201110302333A CN103033150A CN 103033150 A CN103033150 A CN 103033150A CN 2011103023336 A CN2011103023336 A CN 2011103023336A CN 201110302333 A CN201110302333 A CN 201110302333A CN 103033150 A CN103033150 A CN 103033150A
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Abstract
Provided is a method for quickly extracting a main crop planting area through utilization of moderate resolution imaging spectroradiometer (MODIS) data. The method sets up a large-scale crop area automatic identification and quick extracting model based on the MODIS remote sensing images fully covering, and provides for home and abroad a technical method of large-scale crop area quick identification based on middle and low resolution remote sensing images. The method includes the following steps: firstly analyzing a planting structure of different crops, carrying out secondary crop planting regionalization study, secondly analyzing the corresponding relationship between phonological calendar of the crops and normalized difference vegetation indexes (NDVI) and phonological periods on the basis of crop planting structure and planting regionalization and through utilization of the MODIS data and combination of growth regulation of the crops, thirdly setting up quick abstracting models of different areas and different crop planting areas through utilization of MODIS vegetation indexes in key time phases, fourthly abstracting spatial distribution maps of planting areas of winter wheat, spring wheat, spring corn, summer corn, soybean, cotton, early rice, late rice and single-season rice within China, and finally comprehensively verifying results through utilization of a ground quadrat system and a high resolution remote sensing images and statistic data, and the abstracted results can be directly used in Chinese agricultural condition remote sensing monitoring.
Description
Technical field
Remote sensing technology agricultural application.
Background technology
Quick, the accurate extraction of staple crops sown area space distribution is the important foundation of the growing way monitoring in service of agricultural monitoring using remote sensing businessization, yield forecast, disaster monitoring etc.Extracting the important foundation of monitoring crop upgrowth situation that the staple crops sown area is macroscopic view, guiding agricultural production, estimation grain yield, prediction provision price, is the foundation of formulating agricultural policy and grain trade.
Correlative study both at home and abroad mainly concentrates on the land use pattern variation monitoring, and is few to the research of plough inner Different Crop space distribution and variation thereof.Simultaneously correlative study both at home and abroad utilizes high-resolution remote sensing image more, concentrate on the remote sensing recognition of monocrop space distribution or concentrate on experimental study in the small area, with in the low resolution remote sensing images obtain comparatively accurately crop and distribute and become a difficult point.The country such as the U.S., European Union is home or in the local area, mainly the mode by the high-resolution remote sensing image all standing obtains the chief crop spatial distribution map, the Chinese arable land use pattern is various, comprise in the crop growing state remote sensing monitoring of the Chinese Academy of Sciences, China Meteorological Administration and the Ministry of Agriculture, mostly for be whole arable land, do not have with in low resolution remote sensing satellite data do not extract the effective ways that crop on a large scale distributes.The shortage of dividing the crop space distribution, no matter cause is the partition model of setting up with the vegetation index method, still considered the meteorologic model of plant growth mechanism and process, all can not monitor comparatively accurately the crop growing state of minute agrotype, this is restricting the precision of crop growing state remote sensing monitoring on the one hand, can not satisfy the requirement of minute crop condition monitoring, cause on the other hand the growing way remote sensing monitoring to run into very large difficulty when setting up model subregion, a minute crop.
The present invention studies the large scale crops area of having set up based on the remote sensing image all standing and automatically identifies extraction model, provides technical method for carrying out the large scale crops area recognition based on middle low resolution remote sensing images both at home and abroad; The blank that Chinese agricultural monitoring using remote sensing businessization shortage in service divides crop to plough and distribute has been filled up in invention; Result of study can directly be Chinese agricultural monitoring using remote sensing service, improves greatly monitoring accuracy and efficient.
Summary of the invention
The present invention at first analyzes the pattern of farming of Different Crop, divide the research of crop-planting zoning, on proportion of crop planting structure and plantation zoning basis, utilize the MODIS data, growth rhythm in conjunction with crops, analyze phenological calendar and the corresponding relation in vegetation index NDVI and phenological period of crop, the MODIS vegetation index of phase when utilizing key, set up zones of different, Different Crop area rapid extraction model, extract the winter wheat in the Chinese scope, spring wheat, spring maize, summer corn, soybean, cotton, early rice, late rice and one season rice the cultivated area spatial distribution map, extract the result and can directly in Chinese agricultural monitoring using remote sensing, use.Take Spring Maize in Northeast China, spring wheat, soybean, one season rice as example, its sown area extraction model sees lists of documents for details.
Claims (2)
1. the crops planting area Remotely sensed acquisition model separately of subregion, minute crop (winter wheat, spring wheat, spring maize, summer corn, soybean, cotton, early rice, late rice and a season rice), minute crop different developmental phases, and NDVI value, the Tx value of key point in the model.
2. the spatial distribution map of the Different Crop that obtains according to extraction model.
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| CN2011103023336A CN103033150A (en) | 2011-10-09 | 2011-10-09 | Method for quickly extracting main crop planting area through utilization of moderate resolution imaging spectroradiometer (MODIS) data |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103310197A (en) * | 2013-06-13 | 2013-09-18 | 山东省农业可持续发展研究所 | Method for extracting garlic cultivated areas of Huang-Huai-Hai plane terrain by aid of moderate resolution imaging spectroradiometer data |
| CN104615977A (en) * | 2015-01-26 | 2015-05-13 | 河南大学 | Winter wheat remote sensing recognition method capable of synthesizing key seasonal aspect characters and fuzzy classification technology |
| CN104766135A (en) * | 2015-03-25 | 2015-07-08 | 中国农业科学院农业信息研究所 | Method, device and system for predicting crop yield |
| CN104850694A (en) * | 2015-05-13 | 2015-08-19 | 福州大学 | Winter wheat remote sensing monitoring method based on vegetation index increment in growing period |
| CN113392759A (en) * | 2021-06-11 | 2021-09-14 | 河南大学 | Overwintering crop planting area identification method based on multi-source full-time-phase satellite image under cloud computing platform |
| CN114067158A (en) * | 2021-11-17 | 2022-02-18 | 江苏天汇空间信息研究院有限公司 | Farmland use state monitoring system and method applying multi-source remote sensing data |
| CN116524225A (en) * | 2022-12-23 | 2023-08-01 | 山东大学 | Crop classification method and system based on multi-source remote sensing data |
| CN116664663A (en) * | 2023-07-21 | 2023-08-29 | 湖北泰跃卫星技术发展股份有限公司 | Method, device, computer equipment and storage medium for calculating crop area |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070003107A1 (en) * | 2005-07-01 | 2007-01-04 | Deere & Company, A Delaware Corporation | Method and system for vehicular guidance using a crop image |
| CN101595812A (en) * | 2009-06-26 | 2009-12-09 | 中国农业科学院农业资源与农业区划研究所 | A kind of method for acquiring crop harvest index |
| JP2010166851A (en) * | 2009-01-22 | 2010-08-05 | Chiharu Hongo | Method and device for predicting crop yield |
-
2011
- 2011-10-09 CN CN2011103023336A patent/CN103033150A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070003107A1 (en) * | 2005-07-01 | 2007-01-04 | Deere & Company, A Delaware Corporation | Method and system for vehicular guidance using a crop image |
| JP2010166851A (en) * | 2009-01-22 | 2010-08-05 | Chiharu Hongo | Method and device for predicting crop yield |
| CN101595812A (en) * | 2009-06-26 | 2009-12-09 | 中国农业科学院农业资源与农业区划研究所 | A kind of method for acquiring crop harvest index |
Non-Patent Citations (2)
| Title |
|---|
| 张明伟: "基于MODIS数据的作物物候期监测及作物类型识别模式研究", 《中国博士学位论文全文数据库（农业科技辑）》 * |
| 邹金秋等: "利用Terra_MODIS数据提取冬小麦面积及精度分析", 《农业工程学报》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103310197A (en) * | 2013-06-13 | 2013-09-18 | 山东省农业可持续发展研究所 | Method for extracting garlic cultivated areas of Huang-Huai-Hai plane terrain by aid of moderate resolution imaging spectroradiometer data |
| CN104615977A (en) * | 2015-01-26 | 2015-05-13 | 河南大学 | Winter wheat remote sensing recognition method capable of synthesizing key seasonal aspect characters and fuzzy classification technology |
| CN104615977B (en) * | 2015-01-26 | 2018-02-06 | 河南大学 | The winter wheat remote sensing recognition method of comprehensive crucial Aspection character and fuzzy classification technology |
| CN104766135A (en) * | 2015-03-25 | 2015-07-08 | 中国农业科学院农业信息研究所 | Method, device and system for predicting crop yield |
| CN104850694A (en) * | 2015-05-13 | 2015-08-19 | 福州大学 | Winter wheat remote sensing monitoring method based on vegetation index increment in growing period |
| CN104850694B (en) * | 2015-05-13 | 2018-05-04 | 福州大学 | Winter wheat remote-sensing monitoring method based on growth period vegetation index increment |
| CN113392759A (en) * | 2021-06-11 | 2021-09-14 | 河南大学 | Overwintering crop planting area identification method based on multi-source full-time-phase satellite image under cloud computing platform |
| CN114067158A (en) * | 2021-11-17 | 2022-02-18 | 江苏天汇空间信息研究院有限公司 | Farmland use state monitoring system and method applying multi-source remote sensing data |
| CN116524225A (en) * | 2022-12-23 | 2023-08-01 | 山东大学 | Crop classification method and system based on multi-source remote sensing data |
| CN116664663A (en) * | 2023-07-21 | 2023-08-29 | 湖北泰跃卫星技术发展股份有限公司 | Method, device, computer equipment and storage medium for calculating crop area |
| CN116664663B (en) * | 2023-07-21 | 2023-10-20 | 湖北泰跃卫星技术发展股份有限公司 | Method, device, computer equipment and storage medium for calculating crop area |
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Application publication date: 20130410 |