Paper
26 October 2011 Development of a satellite-based multi-scale land use classification system for land and water management in Uzbekistan and Kazakhstan
Fabian Löw, Ulrich Michel, Stefan Dech, Christopher Conrad
Author Affiliations +
Abstract
Satellite remote sensing is an invaluable tool to assess the status and changes of irrigated agricultural systems. Agricultural sites are among the most heterogeneous sites at the landscape level: spatial pattern of agricultural fields, within-field heterogeneity, crop phenology and crop management practices vary significantly. Highly dynamic objects (crops and crop rotations) result in large temporal variability of surface spatial heterogeneity. Technological advances have opened the possibility to monitor agricultural sites combining satellite images with both high spatial resolution and high revisit frequency, which could overcome these constraints. Yet depending on the field sizes and crop phenology of the agricultural system observed, requisites in terms of the instrument´s spatial resolution and optimal timing of crop observation will be different. The overall goal is to quantitatively define region specific satellite observation support requirements in order to perform land use classification at the field basis. The main aspect studied here is the influence of spatial resolution on the accuracy of land use classification over a variety of different irrigated agricultural landscapes. This will guide in identifying an appropriate spatial resolution and input parameters for classification. The study will be performed over distinct locations in irrigated agro-ecosystems in Central Asia, where reliable information on agricultural crops and crop rotations is needed for sustainable land and water management.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fabian Löw, Ulrich Michel, Stefan Dech, and Christopher Conrad "Development of a satellite-based multi-scale land use classification system for land and water management in Uzbekistan and Kazakhstan", Proc. SPIE 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II, 81811K (26 October 2011); https://doi.org/10.1117/12.898038
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Cited by 2 scholarly publications.
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KEYWORDS
Agriculture

Spatial resolution

Remote sensing

Satellites

Classification systems

Image classification

Earth observing sensors

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