基于MODIS影像的土地覆被分类研究——以京津冀地区为例

doi:10.11820/dlkxjz.2014.09.012

Abstract

Abstract:

With intensifying human activities global ecological and environmental problems have become increasingly pressing. Therefore the study of global change has become more prominent. Obtaining accurate land cover information in a timely fashion is critically important for such research. With the development of remote sensing science and technology and application, numerous studies have the issue of land cover classification using remote sensing image. In this study, the Beijing-Tianjin-Hebei region was selected as a study area for land cover classification using MODIS data. The 16-day MOD13Q1/EVI data in 2013, MOD09Q1 (Band1, 2) and MOD09A1(Band3-7) products in May 2013 were used as the basic data. Harmonic analysis method was employed to remove clouds and noises of the whole year's EVI, so that it can better reflect plant phenology. Then, the processed MOD13Q1/EVI data, surface albedo of MODIS/Ref1-7, modified normalized difference water index (MNDWI), normalized difference soil brightness index (NDSI), and normalized difference water index (NDWI) were integrated to construct three schemes of CART decision tree to investigate the land cover classification of the Beijing-Tianjin-Hebei region. The three band combinations are scheme1: 23 phases of EVI of 2013; scheme2: 23 phases of EVI of 2013 plus B1-B7 of MOD09; and scheme3: scheme2+MNDWI+NDSI+NDWI. The results show that the overall classification accuracy of the three schemes reaches 86.70%, 89.98%, and 89.98% respectively. Their Kappa coefficients are 84.94%, 88.66%, and 90.20% respectively. Therefore, MODIS images with various classification characteristics, combined with the decision trees can achieve higher precision land cover classification. This proves the feasibility of the proposed method for land cover classification at the regional scale.

Key words: land cover, classification, MODIS images, harmonics analysis, CART decision tree, classification feature combination, Beijing-Tianjin-Hebei region

CLC Number:

TP79

Yushan ZUO, Wei WANG, Yanli HAO, Hong LIU. Land cover classification based on MODIS images: taking the Beijing-Tianjin-Hebei region as an example[J].PROGRESS IN GEOGRAPHY, 2014, 33(11): 1556-1565.

Figures/Tables 10

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References 35

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土地覆被类型	含义	样区数	样本数
一年一熟旱地	指一年收获一季,种植旱生农作物的耕地	26	1522
一年两熟旱地	指一年收获二季,种植旱生农作物的耕地	22	1269
一年一熟水田	指一年收获一季,用于种植水稻等水生农作物的耕地	28	1116
园地	人工种植的经济林地	25	1011
林地	指生长乔木、灌丛为主的土地	23	1558
草地	指生长草本植物为主的土地	20	1379
建筑用地	指居民点、交通、工矿用地	20	1550
水体	指陆地水域、海涂（含盐田）等用地	35	1433
其他土地	指上述地类以外的其他类型土地,主要包括裸地和休耕地	26	1289
合计			12127

类对	分类特征组合
	方案一		方案二		方案三

一年一熟旱地_一年一熟水田	1.2935	1.4901	1.9907	1.9999	1.9997	2.0000
一年一熟旱地_园地	1.8468	1.9921	1.9921	2.0000	1.9998	2.0000
一年一熟旱地_草地	1.7404	1.9577	1.9588	1.9996	1.9947	2.0000
一年一熟旱地_其他	1.8405	1.9401	1.9704	1.9989	1.9978	2.0000
一年一熟水田_草地	1.8810	1.9811	1.9980	1.9999	1.9999	2.0000
园地_其他	1.8783	1.9734	1.9748	1.9989	1.9921	2.0000
林地_草地	1.7494	1.9390	1.9953	1.9999	1.9994	2.0000
草地_其他	1.8119	1.9941	1.9658	1.9999	1.9880	2.0000
建筑用地_水体(含盐田)	1.8176	1.9993	1.9979	1.9999	1.9999	2.0000
水体(含盐田)_其他	1.8593	1.9999	1.9999	2.0000	2.0000	2.0000

类别	不同分类特征组合方案下的分类精度/%
	方案一			方案二			方案三
	制图精度		用户精度		制图精度	用户精度	制图精度	用户精度
一年一熟旱地	87.22	87.76		94.23	94.81		93.81	90.10
一年两熟旱地	85.06	92.82		87.34	96.37		94.94	96.65
一年一熟水田	90.33	73.28		96.98	76.61		91.24	75.88
园地	98.08	88.99		92.01	93.51		95.53	85.43
林地	77.60	94.27		95.68	92.06		94.89	95.45
草地	77.13	76.97		76.30	90.62		81.70	97.28
建筑用地	87.24	95.64		86.82	93.47		88.28	96.57
水体（含盐田）	87.79	96.86		88.74	98.49		88.33	99.69
其他土地	93.82	75.79		94.01	76.76		96.25	82.64
Kappa系数	84.94		88.66			90.20
总体分类精度	86.70		89.98			91.34

Land cover classification based on MODIS images: taking the Beijing-Tianjin-Hebei region as an example

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