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La rapide urbanisation de la Chine conduit à mettre au point des méthodes d'analyse et de suivi de la taille des villes. Devant l'hétérogénéité des divisions administratives et des dénombrements des populations, nous en proposons ici une estimation par les surfaces bâties, obtenues sur des images satellites Landsat. On mesure ainsi l'extension en superficie d'une cinquantaine d'agglomérations urbaines de 1980 à 2000, que l'on compare ensuite aux chiffres de population indiqués pour les villes éponymes dans diverses bases de données internationales. Les relations non linéaires établies entre populations et surfaces attestent de la cohérence des résultats obtenus par cette méthode. Cependant, lorsqu'il s'agit de mesurer l'évolution des surfaces comme des populations, les nombreuses fluctuations rendent la méthode moins fiable et celle-ci doit être complétée par d'autres types d'observations.

[ScienceDirect, via Biblio-SHS] Auteur : XiaoFang Sun, TianXiangYue, ZeMeng Fan Paru dans : Procedia Environmental Sciences, Volume 13, 2012, Pages 590-597 18th Biennial ISEM Conference on Ecological Modelling for Global Change and Coupled Human and Natural System Abstract Land use changes affect many aspects of Earth System functioning, for example in impacting global carbon cycle, contributing to climate change, or increasing soil erosion. The simulation of land use change is important in environmental impact assessment and land use planning. We assessed the land use scenarios of China in the next 100 years based on the SMLC (surface modelling of land cover change) model and Dyna-CLUE (dynamic conversion of land use and its effects) model. Three SRES scenarios were evaluated: Global Economy (A1FI): lean government, strong globalization; Continental Markets (A2a): lean government, regional culture and economic development; Regional communities (B2a): much government intervention, regional cultural and economic development. Ten land cover types were simulated, which are cultivated land, woodland, grassland, built-up land, water area, wetland, nival area, desert, bare rock and desertification land. The SMLC model was used to calculate changes in area for each land use types in the future at country level while the spatially explicit land use model Dyna-CLUE was used to simulate land use pattern at 2 km2 resolution based on the country level areas demands for each land cover type. The results show that the cultivated land would decrease in all of the three scenarios, while in the A2a scenario, the cultivated land would decrease with the lowest rate because of the high population growth, high level of market protection and low agricultural efficiency; in the B2a scenario, it would decrease with the highest rate caused by the decreased population numbers and increased crop productivity. The nival area would decrease with the highest rate in the A1FI