Comparison of Drought Recognition of Spring Maize in Northeast China Based on 3 Remote Sensing Indices

Chen Yuye; Wang Peijuan; Zhang Yuanda; Yang Jianying

doi:10.11898/1001-7313.20220407

Vol.33, NO.4, 2022

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Chen Yuye, Wang Peijuan, Zhang Yuanda, et al. Comparison of drought recognition of spring maize in Northeast China based on 3 remote sensing indices. J Appl Meteor Sci, 2022, 33(4): 466-476. DOI: 10.11898/1001-7313.20220407.

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Chen Yuye, Wang Peijuan, Zhang Yuanda, et al. Comparison of drought recognition of spring maize in Northeast China based on 3 remote sensing indices. J Appl Meteor Sci, 2022, 33(4): 466-476. DOI: 10.11898/1001-7313.20220407.

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Comparison of Drought Recognition of Spring Maize in Northeast China Based on 3 Remote Sensing Indices

DOI: 10.11898/1001-7313.20220407

Chinese Academy of Meteorological Sciences, Beijing 100081

Received Date: 2022-04-19
Rev Recd Date: 2022-05-30
Publish Date: 2022-07-13

Abstract

Abstract

Drought is a complex and widespread natural disaster, which has brought serious environmental and social problems and caused huge economic losses to China. For nearly half a century, the trend of aridification in Northeast China has been very significant, the area of influence has increased, and the degree of drought has also intensified significantly. Drought index is the basis of judging the occurrence of drought events, evaluating the degree of drought, clarifying the spatiotemporal characteristics of drought, and formulating measures for drought prevention and mitigation. Numerous studies indicate that solar-induced chlorophyll fluorescence(SIF), normalized difference vegetation index(NDVI), enhanced vegetation index(EVI), and normalized difference water index(NDWI) can be used to identify agricultural drought, but the research on comparing the ability of SIF index, NDWI and NDVI for identifying agricultural drought has not been reported publicly. Taking spring maize in Northeast China as the research object, NDWI and NDVI are calculated using the surface reflectance data MOD09A1. Combined with SIF index, NDWI and NDVI, the time series dataset of remote sensing drought index is constructed, respectively, and the accuracy and sensitivity of these three indices for identifying the drought is further explored. It shows that the accuracy of three indices in indentifying maize drought are all higher than 80%, and the accuracy of SIF index is the highest, reaching 89.27%. The accuracy for identifying severe drought is higher than mild and moderate drought for three indices, all reaching more than 94%, and the accuracy of SIF index exceeds 95%. From the perspective of different developmental stages of spring maize, the monitoring accuracy is the highest at seedling stage, reaching more than 90%, and is the lowest at jointing-booting stage and grain filling-maturity stage. The drought identifying accuracies of SIF index during four developmental periods of spring maize are all better than those of NDWI and NDVI. The sensitivities of SIF index, NDWI and NDVI to the identification of maize drought are different, and the SIF index has the highest sensitivity to drought identification, followed by NDWI, and NDVI is slightly lower. In terms of drought grades, the identifying sensitivities of three indices to severe drought are all higher than those of mild and moderate drought. Above all, compared with NDWI and NDVI, SIF index has better accuracy and sensitivity in identifying the drought of spring maize in Northeast China, and can make timely and accurate response to maize drought in Northeast China. The results have important practical significance for accurately identifying and predicting drought of spring maize in Northeast China, and taking effective drought-resistant measures in a timely and objective manner to minimize the damage to crops.
- SIF index;
- NDWI;
- NDVI;
- spring maize;
- drought sensitivity

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References(39)

Figures and Tables

Fig. 1 Study area and typical stations

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Fig. 2 Distribution of drought sample sites and drought frequency for spring maize in Northeast China from May to Sep during 2000-2013

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Fig. 3 Accuracy of SIF index, NDWI and NDVI in identifying different drought grades for spring maize

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Fig. 4 Sensitivity of SIF index, NDWI and NDVI in identifying different drought grades for spring maize

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图 5 SIF指数、NDWI和NDVI识别春玉米干旱敏感度对比

(a)判定干旱发生与灾害记录日数差, (b)判定干旱发生与灾害记录日数差频次和累计频次

Fig. 5 Sensitivity in identifying drought for spring maize by SIF index, NDWI and NDVI

(a)difference between drought occurrence date and determined disaster record date, (b)the difference frequency and cumulative frequency between drought occurrence date and determined disaster record date

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Fig. 6 Drought sensitivity identified by SIF index, NDWI and NDVI at typical stations

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Table 1 Accuracy of SIF index, NDWI and NDVI in identifying different drought grades at different developmental stages of spring maize

遥感指数	发育阶段	准确度/%
遥感指数	发育阶段	轻度干旱	中度干旱	重度干旱	总体
SIF指数	苗期	100.00	94.44	94.45	95.77
	拔节-孕穗期	78.95	81.82	100.00	81.82
	抽穗-开花期	100.00	92.31	100.00	96.77
	灌浆-成熟期	78.57	76.47	100.00	80.56
NDWI	苗期	88.24	88.89	100.00	91.55
	拔节-孕穗期	73.68	72.73	100.00	75.76
	抽穗-开花期	85.71	76.92	90.91	83.87
	灌浆-成熟期	64.29	82.35	100.00	77.78
NDVI	苗期	100.00	94.44	94.45	95.77
	拔节-孕穗期	73.68	45.45	100.00	66.67
	抽穗-开花期	85.71	76.92	90.91	83.00
	灌浆-成熟期	64.29	82.35	100.00	77.00

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