本文選題：尺度效應　切入點：尺度轉換　出處：《中國地質大學(北京)》2017年博士論文　論文類型：學位論文

【摘要】：遙感數據與作物生長模型在農作物估產上能夠優(yōu)勢互補。然而,作物模型尺度與遙感觀測尺度不匹配是影響同化模型精度的重要因素,這將極大增加遙感反演和數據同化的不確定性。本研究以基于作物生長模型與遙感數據同化的冬小麥估產為目標,針對遙感尺度這一重要科學問題,借助統(tǒng)計模型、物理方法、數據融合等技術,剖析了同化觀測量(葉面積指數,LAI)尺度效應產生的主要原因,定量描述并校正了空間異質性與模型非線性所引起的尺度效應誤差,探討了多源遙感數據差異及其形成的內在機理,研究了Landsat與MODIS之間的尺度轉換方法,建立了空間尺度差異校正的基本框架,并面向研究區(qū)對尺度校正框架進行了適用性驗證,利用數據融合技術對同化觀測量進行了時間尺度擴展,進而耦合WOFOST模型與多時空尺度遙感數據對河北省衡水地區(qū)冬小麥產量進行估測。論文的研究工作及主要結論如下:(1)在分析尺度效應產生根源、明確多源遙感數據差異的基礎上,定量分析多空間尺度遙感反演農作物同化觀測量LAI的總體差異。結果表明,多源遙感數據引起的差異高于尺度效應帶來的誤差。(2)考慮同化觀測量LAI的空間異質性,細化尺度效應產生過程,結合小波變換和分形理論,定量分析冬小麥LAI不同反演過程對尺度效應的貢獻,并有效校正尺度效應引起的誤差。(3)從系統(tǒng)內在機理出發(fā),歸納分析Landsat和MODIS數據差異,提取可通過數理方法模擬的相關信息,基于點擴散函數及粒子群優(yōu)化算法,定量校正遙感觀測數據差異,建立尺度轉換模型,降低尺度差異導致的不確定性。(4)基于多尺度遙感數據反演同化觀測量差異的定量分析,借助各類數理模型,構建并完善空間尺度差異校正框架,將多尺度遙感定量反演同化觀測量LAI的總體不確定性降低了50%以上。(5)在空間尺度差異校正和時間尺度擴展的基礎上,通過四維變分同化算法及SCE-UA優(yōu)化算法,耦合多尺度遙感信息與WOFOST作物生長模型,對冬小麥進行區(qū)域化時空同化估產,在保證同化精度的前提下,大幅提高同化效率。
[Abstract]:The remote sensing data and crop growth model can be complementary in the estimation of crop yield. However, crop model scale and remote sensing observation scale, is an important factor affecting the assimilation model precision, which will greatly increase the retrieval and data assimilation uncertainty. Based on the yield of winter wheat crop growth model and remote sensing data assimilation based on the target in view of this, the scale of remote sensing of important scientific problems, physical methods by means of statistical model, data fusion technology, analyzes the assimilation measurements (leaf area index, LAI) mainly due to the scale effects, quantitative description of the error correction and scale effect of spatial heterogeneity and nonlinear model caused by the inherent mechanism of the difference of multi-source remote sensing data and the formation of the research on the transformation method between Landsat and MODIS scale, establish the basic framework of correction in different spatial scales, and surface To study on scale correction framework for the validation of measurements, the assimilation time scale expansion of the use of data fusion technology, and the coupling of WOFOST model and multi-scale remote sensing data on the yield of Winter Wheat in Hengshui area of Hebei province were estimated. The research work of this thesis and the main conclusions are as follows: (1) in the analysis of causes the scale effect, based on the difference of multi-source remote sensing data, the overall differences in quantitative analysis of multi spatial scale remote sensing crop assimilation measurements of LAI. The results show that the difference of multi-source remote sensing data caused by the above error scale effects. (2) considering the spatial heterogeneity of assimilation measurements of LAI, produced in the process of refining the scale effect, combined with wavelet transform and fractal theory, quantitative analysis of winter wheat LAI inversion process different contribution to the scale effect, scale effect and effective error correction caused by (3) from the Department. The system of internal mechanism, analyzed the difference between Landsat and MODIS data, the relevant information can be extracted by mathematical simulation method, point spread function and particle swarm optimization algorithm based on the difference of quantitative calibration of remote sensing observation data, a scale transformation model, reduce the scale difference leads to uncertainty. (4) quantitative analysis of differences of multi-scale remote sensing data based on the concept of retrieval and assimilation, with all kinds of mathematical model, construct and perfect the spatial scale difference correction framework of multi-scale quantitative remote sensing measurements of LAI assimilation overall uncertainty reduced by 50%. (5) based in correction in different spatial scales and time scales, the four-dimensional Variational Assimilation Algorithm and SCE-UA optimization algorithm, coupled multi-scale remote sensing information and crop growth model WOFOST, regional spatial assimilation yield of winter wheat, under the premise of ensuring the accuracy of assimilation, sharp Improve the efficiency of assimilation.

【學位授予單位】：中國地質大學(北京)
【學位級別】：博士
【學位授予年份】：2017
【分類號】：S512.11;S127

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