中高分辨率遙感協(xié)同反演冬小麥覆蓋度
發(fā)布時(shí)間：2018-08-22 18:08
【摘要】：為了開展高精度、高時(shí)空分辨率的植被覆蓋度(fraction vegetation cover,FVC)監(jiān)測(cè),該文以華北地區(qū)冬小麥地為研究對(duì)象,采用4期高分一號(hào)衛(wèi)星多光譜(GF1-PMS)、多光譜寬幅(GF1-WFV)與環(huán)境一號(hào)衛(wèi)星多光譜(HJ1-CCD)3種傳感器同期影像數(shù)據(jù)集,基于像元二分法模型,研究多源中高分辨率遙感影像協(xié)同估算FVC方法。以基于高空間分辨率GF1-PMS影像反演的FVC作為檢驗(yàn)數(shù)據(jù),對(duì)單源直接獲取法、多源全生育期法、多源分期法3種反演模型進(jìn)行了分析比較。研究結(jié)果表明:HJ1-CCD、GF1-WFV數(shù)據(jù)與GF1-PMS數(shù)據(jù)的FVC直接反演結(jié)果具有較高的一致性,但在冬小麥的初期生長(zhǎng)階段,受衛(wèi)星觀測(cè)角度效應(yīng)的影響,GF1-WFV與HJ1-CCD的FVC結(jié)果偏高,偏差隨冬小麥的成熟封壟而逐漸減弱;多源分期法的時(shí)空反演得到的FVC精度最高,GF1-WFV的決定系數(shù)為0.984,均方根誤差為0.030;HJ1-CCD的決定系數(shù)為0.978,均方根誤差為0.034;而在缺少GF1-PMS匹配數(shù)據(jù)時(shí),可通過多源全生育期法提高GF1-WFV與HJ1-CCD數(shù)據(jù)的反演精度,GF1-WFV的決定系數(shù)為0.964,均方根誤差為0.044;HJ1-CCD的決定系數(shù)為0.950,均方根誤差為0.052。通過多傳感器的聯(lián)合反演獲取時(shí)間序列的高精度的FVC數(shù)據(jù),可為研究植被生長(zhǎng)狀況及生態(tài)環(huán)境動(dòng)態(tài)變化提供數(shù)據(jù)基礎(chǔ)。
[Abstract]:In order to monitor vegetation coverage with high precision and high spatial and temporal resolution, the winter wheat field in North China was studied in this paper. Based on pixel dichotomy model, the method of multi-source and high-resolution remote sensing image co-estimation of FVC was studied by using the simultaneous image data sets of four high-fractional-one satellite multispectral (GF1-PMS), multi-spectral wide amplitude (GF1-WFV) and environmental satellite multispectral (HJ1-CCD) sensors. Taking FVC inversion based on high spatial resolution GF1-PMS image as the test data, three kinds of inversion models, namely single source direct acquisition method, multi-source full growth period method and multi-source staging method, are analyzed and compared. The results show that there is a high consistency between the FVC direct inversion results of the GF1-PMS data and the GF1-PMS data. However, in the initial growth stage of winter wheat, the FVC results of GF1-WFV and HJ1-CCD are higher than those of HJ1-CCD due to the influence of satellite observation angle effect. The deviation decreases gradually with the mature ridging of winter wheat, the determination coefficient of FVC is 0.984, the root mean square error is 0.030 HJ1-CCD is 0.978, and the root mean square error is 0.034, but in the absence of GF1-PMS matching data, the determination coefficient of GF1-WFV is 0.978, and the root mean square error is 0.034 in the absence of GF1-PMS matching data. The inversion accuracy of GF1-WFV and HJ1-CCD data can be improved by multi-source whole growth period method. The determination coefficient of GF1-WFV is 0.964, the RMS error is 0.044 HJ1-CCD is 0.950, and the root mean square error is 0.052. The high precision FVC data of time series can be obtained by the joint inversion of multi-sensors, which can provide a data basis for the study of vegetation growth and the dynamic changes of ecological environment.
【作者單位】： 遙感科學(xué)國(guó)家重點(diǎn)實(shí)驗(yàn)室北京師范大學(xué)地理科學(xué)部;環(huán)境保護(hù)部衛(wèi)星環(huán)境應(yīng)用中心;北京林業(yè)大學(xué)精準(zhǔn)林業(yè)北京市重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家重點(diǎn)研發(fā)計(jì)劃(2016YFD0800903)
【分類號(hào)】：S127;S512.11
本文編號(hào)：2197896
[Abstract]:In order to monitor vegetation coverage with high precision and high spatial and temporal resolution, the winter wheat field in North China was studied in this paper. Based on pixel dichotomy model, the method of multi-source and high-resolution remote sensing image co-estimation of FVC was studied by using the simultaneous image data sets of four high-fractional-one satellite multispectral (GF1-PMS), multi-spectral wide amplitude (GF1-WFV) and environmental satellite multispectral (HJ1-CCD) sensors. Taking FVC inversion based on high spatial resolution GF1-PMS image as the test data, three kinds of inversion models, namely single source direct acquisition method, multi-source full growth period method and multi-source staging method, are analyzed and compared. The results show that there is a high consistency between the FVC direct inversion results of the GF1-PMS data and the GF1-PMS data. However, in the initial growth stage of winter wheat, the FVC results of GF1-WFV and HJ1-CCD are higher than those of HJ1-CCD due to the influence of satellite observation angle effect. The deviation decreases gradually with the mature ridging of winter wheat, the determination coefficient of FVC is 0.984, the root mean square error is 0.030 HJ1-CCD is 0.978, and the root mean square error is 0.034, but in the absence of GF1-PMS matching data, the determination coefficient of GF1-WFV is 0.978, and the root mean square error is 0.034 in the absence of GF1-PMS matching data. The inversion accuracy of GF1-WFV and HJ1-CCD data can be improved by multi-source whole growth period method. The determination coefficient of GF1-WFV is 0.964, the RMS error is 0.044 HJ1-CCD is 0.950, and the root mean square error is 0.052. The high precision FVC data of time series can be obtained by the joint inversion of multi-sensors, which can provide a data basis for the study of vegetation growth and the dynamic changes of ecological environment.
【作者單位】： 遙感科學(xué)國(guó)家重點(diǎn)實(shí)驗(yàn)室北京師范大學(xué)地理科學(xué)部;環(huán)境保護(hù)部衛(wèi)星環(huán)境應(yīng)用中心;北京林業(yè)大學(xué)精準(zhǔn)林業(yè)北京市重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家重點(diǎn)研發(fā)計(jì)劃(2016YFD0800903)
【分類號(hào)】：S127;S512.11
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