The GF-1 satellite has advantages such as short revisit period and the combination of various spatial resolutions and large swath, while the Landsat-8 satellite has the advantages of multi-channels and high radiometric resolution. This article presents a case study focused on land cover classification in Zhongxiang City, Hubei Province. Considering the characteristics of different sensor parameters, the Support Vector Machine classifier (SVM) was applied to the two datasets of the same region on 6 August 2013 and a comparison was made on the classification results. The result shows that the coefficient of determination of the corresponding channels between these two sensors are over 0.92. Good consistencies are found in typical samples’ spectrum. However, compared to GF-1, Landsat-8 has better separability between farmland and woodland, and between impervious surface and bare soil. The overall classification accuracy of GF-1 and Landsat-8 reaches 90.38% and 90.07% respectively, whereas there are differences in classification accuracies of different surface types. The differences in spectral response functions may account for the advantage of Landsat-8 on woodland identification accuracy as compared to GF-1. In addition, compared to Landsat-8, GF-1 outperforms in classification accuracy on surface types with fragmented distribution because GF-1 has higher spatial resolution.

Intensity analysis is a popular method as a top-down hierarchical accounting framework to analyze land use maps by considering cross-tabulation matrices and calculating change area and intensity of each land use category in every time interval with the use of remote sensing, geographic information system, and statistical methods. It was applied to analyze land use changes at three levels: temporal (time interval), categorical (land use types), and direction of conversion. At each level, we compared the observed change intensity to a uniform change intensity in order to reveal the characteristics of change. At the temporal level, we identify in which time intervals changes were relatively fast in terms of overall annual change. At the categorical level, we identify which categories were stable as opposed to active relative to the size of the categories. At the direction of conversion level, when a given category gains or loses, we can identify intensive targeting or avoidance of the other categories. In this article, we took land use change in Kunming City as an example to explore area and intensity changes at different levels and analyze stationarity. The results show that temporally land use intensity in Kunming City has gradually increased since 2000 (in the last time interval). With regard to land use categories, built-up areas’ change intensity was most active, while the change intensity of forests was most stable. With regard to the direction of conversion, the increased built-up areas were mainly from previous cropland, while the reduced forest areas were mainly changed into grassland. Intensity analysis theory has great advantages in analyzing land use change processes, which facilitates the mining of change information and understanding of land use change processes and is very useful for scientists.

Multi-functionality of land use is the result of the process of land utilization according to the socioeconomic goals, which is the key to ensuring the coordinated development of the socioeconomic and ecological environments. By constructing a social-economic-ecological multi-functional land use evaluation indicator system, this article comprehensively examines the multi-functionality of land use from 1990 to 2013 in Northeast China, which aims to explain the spatiotemporal patterns of multi-functionality of land use in the area. The results show that functional values of land use showed an upward trend during 1990-2013 in Northeast China, but the growth rates differed. The development levels of land use functions in Heilongjiang, Jilin, and Liaoning Provinces were in an ascending order, and the average annual growth rates were 2.976%, 2.725%, and 2.261%, respectively. The social function values of Heilongjiang and Jilin Provinces increased with some fluctuations, but Liaoning Province showed a periodical change. The economic function values of Heilongjiang Province increased, but that of Jilin and Liaoning Provinces showed an overall upward trend yet fluctuated in 2000 to 2005. The ecological function values of Heilongjiang and Jilin Provinces were stable at the beginning of the period then showed an increasing trend with some fluctuations, whereas in Liaoning Province it always showed greater volatility. Land production and transportation, which are important parts of the economic function, had a great impact on the land use functionality of the three provinces in Northeast China. Economic and social factors had a greater impact on the multi-functionality of land use in Heilongjiang and Jilin Provinces, while ecological factors played a smaller role. But in Liaoning Province, economic, social, and ecological factors all had important impacts on the multi-functionality of land use.