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Accueil du site → Doctorat → Allemagne → 2014 → Understanding land use and land cover change in Inner Mongolia using remote sensing time series

Humboldt-Universität zu Berlin (2014)

Understanding land use and land cover change in Inner Mongolia using remote sensing time series

Yin, He

Titre : Understanding land use and land cover change in Inner Mongolia using remote sensing time series

Auteur : Yin, He

Université de soutenance : Humboldt-Universität zu Berlin

Grade : Doctor rerum naturalium (Dr. rer. nat.) 2014

Résumé
Monitoring land use and land cover change (LULCC) support better interpretation about how land surfaces are impacted by human decisions. The overall aim of this thesis is to gain a better understanding about LULCC in Inner Mongolia using remote sensing under consideration of China’s land use policies. With the largest scale land restoration programs in the world, China aims to reduce human pressure on lands and promote sustainable land use. As a hot-spot of environmental change, Inner Mongolia received the heaviest investment from the central government for land restoration. Yet the effectiveness and consequences of China’s land use policies in Inner Mongolia remain unclear. Remote sensing is an effective tool for monitoring land use and land cover change across broad scales, yet data limitations and a lack of available change detection methods hampers the capacity of researchers to apply remote sensing techniques for LULCC monitoring. To reliably map LULCC in Inner Mongolia, the opportunities and limitations of using coarse resolution imagery time series for monitoring long-term land changes was first examined. Second, an approach detecting annual changes between multiple land categories was developed and applied in Inner Mongolia. Results indicate that China’s land use policies effectively preserved and recovered forest ecosystems in Inner Mongolia after the year 2000. The decreasing trends of deforestation and forest gain are obvious in the regions that implement China’s land use policies, which reflect the positive influence of the policy. Cropland retirement was mostly found in ecologically fragile areas where climate and topographic conditions are unsuitable for cultivation. This thesis reveals how political factors and other underlying social-economic drivers impact a country’’s land surface, and highlights the values of using coarse resolution imagery and time series analysis for LULCC monitoring across large areas.

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