【摘要】：在省域尺度上,冬小麥遙感識別中存在冬小麥物候不一致、地表環(huán)境復(fù)雜、數(shù)據(jù)處理復(fù)雜、遙感數(shù)據(jù)冗余、選擇適當(dāng)?shù)姆诸悩颖纠щy、分類精度低等問題,而遙感數(shù)據(jù)云平臺為解決這些問題提供了良好的數(shù)據(jù)基礎(chǔ)和數(shù)據(jù)處理能力。以河南省為研究區(qū),以谷歌地球引擎(Google Earth Engine)云平臺為支撐,基于2015年和2002年前后年份河南省冬小麥識別關(guān)鍵期內(nèi)的2296景Landsat遙感影像,采用NDVI重構(gòu)增幅算法建立冬小麥大區(qū)域遙感快速制圖模型,實現(xiàn)了2015年和2002年的河南省冬小麥分布制圖。結(jié)果表明:2015年和2002年冬小麥種植面積分別為56 055.79 km~2和47 296.11 km~2,與統(tǒng)計數(shù)據(jù)比,精度達(dá)到97%;2002-2015年,河南省冬小麥種植分布存在明顯變化,總體播種面積呈增加趨勢,2015年比2002年增加8759.69 km~2,增幅為18.52%。與傳統(tǒng)計算機冬小麥制圖方法相比,基于Google Earth Engine云平臺的數(shù)據(jù)處理和制圖效率均獲得千倍以上的提升。
[Abstract]:On the provincial scale, winter wheat remote sensing recognition has many problems such as inconsistent phenology, complex surface environment, complex data processing, redundancy of remote sensing data, difficulty in selecting suitable classification samples and low classification accuracy. The remote sensing data cloud platform provides a good data base and data processing ability for solving these problems. Based on the (Google Earth Engine) cloud platform of Google Earth engine, the 2296 Landsat remote sensing images of winter wheat in Henan Province during the critical period of winter wheat recognition in 2015 and 2002 were used as the research area. The fast remote sensing mapping model of winter wheat in large area was established by using NDVI reconstruction increment algorithm, and the distribution mapping of winter wheat in Henan Province in 2015 and 2002 was realized. The results showed that the planting area of winter wheat in 2015 and 2002 was 56 055.79 km~2 and 47 296.11 km~2, respectively, and the precision was 97% compared with the statistical data. The planting distribution of winter wheat in Henan Province changed obviously from 2002 to 2015, and the total sowing area showed an increasing trend, and the increase of 8759.69 km~2, was 18.52% in 2015 than in 2002. Compared with the traditional computer mapping method of winter wheat, the efficiency of data processing and mapping based on Google Earth Engine cloud platform has been improved more than 1000 times.
【作者單位】： 北京林業(yè)大學(xué);中國科學(xué)院遙感與數(shù)字地球研究所;中國科學(xué)院大學(xué);
【基金】：國家自然科學(xué)基金項目(4130139、41371358) 河北省自然科學(xué)基金項目(D2015207008)
【分類號】：S127;S512.11

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