Per-Field Irrigated Crop Classification in Arid Central Asia Using SPOT and ASTER Data

Remote Sensing

Christopher Conrad¹  Sebastian Fritsch¹  Julian Zeidler¹  Gerd R࿌ker² 

[1] Remote Sensing Unit, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany; E-Mails:;German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, 82234 Wessling, Germany; E-Mails:

关键词: object-based classification;    segmentation;    tasselled cap;    Uzbekistan;    irrigated agriculture;    multi-sensor;   

DOI  :  10.3390/rs2041035

来源: mdpi

【 摘 要 】

The overarching goal of this research was to explore accurate methods of mapping irrigated crops, where digital cadastre information is unavailable: (a) Boundary separation by object-oriented image segmentation using very high spatial resolution (2.5–5 m) data was followed by (b) identification of crops and crop rotations by means of phenology, tasselled cap, and rule-based classification using high resolution (15–30 m) bi-temporal data. The extensive irrigated cotton production system of the Khorezm province in Uzbekistan, Central Asia, was selected as a study region. Image segmentation was carried out on pan-sharpened SPOT data. Varying combinations of segmentation parameters (shape, compactness, and color) were tested for optimized boundary separation. The resulting geometry was validated against polygons digitized from the data and cadastre maps, analysing similarity (size, shape) and congruence. The parameters shape and compactness were decisive for segmentation accuracy. Differences between crop phenologies were analyzed at field level using bi-temporal ASTER data. A rule set based on the tasselled cap indices greenness and brightness allowed for classifying crop rotations of cotton, winter-wheat and rice, resulting in an overall accuracy of 80 %. The proposed field-based crop classification method can be an important tool for use in water demand estimations, crop yield simulations, or economic models in agricultural systems similar to Khorezm.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.