Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link



Sibanda, M; Murwira, A (2012). The use of multi-temporal MODIS images with ground data to distinguish cotton from maize and sorghum fields in smallholder agricultural landscapes of Southern Africa. INTERNATIONAL JOURNAL OF REMOTE SENSING, 33(16), 4841-4855.

In this study, we test whether we can significantly (p < 0.05) distinguish cotton (Gossypium hirsutum L.) fields from maize (Zea mays L.) and sorghum (Sorghum bicolor) fields in smallholder agricultural landscapes of the Mid-Zambezi Valley, Zimbabwe, using a temporal series of 16-day Moderate Resolution Imaging Spectroradiometer - normalized difference vegetation index (MODIS NDVI) data. We test this hypothesis at different phenological stages over the growing season, that is, early green-up onset, late green-up onset, green-peak, early senescence and late senescence. We also statistically compare the rate of change in the greenness of the three crops at the three phenological stages. Results show that we can significantly (p < 0.05) distinguish cotton fields from maize and sorghum fields using 16-day MODIS NDVI data during the late green-up onset as well as during the green-peak stage of the three crops. Our results indicate that cotton can successfully be distinguished from maize and sorghum in spatially heterogeneous smallholder agricultural landscapes using temporal MODIS NDVI.



NASA Home Page Goddard Space Flight Center Home Page