Your search found 3 records
1 Smaling, E.M.A.; Oenema, O.; Fresco, L.O. (Eds.) 1999. Nutrient disequilibria in agroecosystems concepts and case studies. Oxon, UK; New York, USA: CABI. xiv, 322p.; chart; 24 cm.
(Location: IWMI-SEA Call no: 577.55 G000 SMA Record No: BKK-58)
2 de Bie, C. A. J. M.; Khan, M. R.; Smakhtin, Vladimir; Venus, V.; Weir, M. J. C.; Smaling, E. M. A.. 2011. Analysis of multi-temporal SPOT NDVI images for small-scale land-use mapping. International Journal of Remote Sensing, 32(21):6673-6693. [doi: https://doi.org/10.1080/01431161.2010.512939]
Remote sensing ; GIS ; Image analysis ; Land use ; Land cover ; Mapping ; Vegetation ; Crop management / India / Andhra Pradesh / Nizamabad District
(Location: IWMI HQ Call no: e-copy only Record No: H044207)
(3.14 MB)
Land-use information is required for a number of purposes such as to address food security issues, to ensure the sustainable use of natural resources and to support decisions regarding food trade and crop insurance. Suitable land-use maps often either do not exist or are not readily available. This article presents a novel method to compile spatial and temporal land-use data sets using multi-temporal remote sensing in combination with existing data sources. Satellite Pour l’Observation de la Terre (SPOT)-Vegetation 10-day composite normalized difference vegetation index (NDVI) images (1998–2002) at 1 km2 resolution for a part of the Nizamabad district, Andhra Pradesh, India, were linked with available crop calendars and information about cropping patterns. The NDVI images were used to stratify the study area into map units represented by 11 distinct NDVI classes. These were then related to an existing land-cover map compiled from high resolution Indian Remote Sensing (IRS)-images (Liss-III on IRS-1C), reported crop areas by sub-district and practised crop calendar information. This resulted in an improved map containing baseline information on both land cover and land use. It is concluded that each defined NDVI class represents a varying but distinct mix of land-cover classes and that the existing land-cover map consists of too many detailed ‘year-specific’ features. Four groups of the NDVI classes present in agricultural areas match well with four categories of practised crop calendars. Differences within a group of NDVI classes reveal area specific variations in cropping intensities. The remaining groups of NDVI classes represent other land-cover complexes. The method illustrated in this article has the potential to be incorporated into remote sensing and Geographical Information System (GIS)-based drought monitoring systems.
3 Nguyen, T. T. H.; De Bie, C. A. J. M.; Ali, A.; Smaling, E. M. A.; Hoanh, Chu Thai. 2011. Mapping the irrigated rice cropping patterns of the Mekong delta, Vietnam, through hyper-temporal SPOT NDVI image analysis. International Journal of Remote Sensing, 33(2):415-434. [doi: https://doi.org/10.1080/01431161.2010.532826]
Irrigated rice ; Crop management ; Remote sensing ; Mapping ; Deltas ; Image analysis ; Vegetation ; Indicators ; Data / Vietnam / Mekong delta
(Location: IWMI HQ Call no: e-copy only Record No: H044487)
(3.68 MB)
Successful identification and mapping of different cropping patterns under cloudy conditions of a specific crop through remote sensing provides important baseline information for planning and monitoring. In Vietnam, this information is either missing or unavailable; several ongoing projects studying options with radar to avoid earth observation problems caused by the prevailing cloudy conditions have to date produced only partial successes. In this research, optical hyper-temporal Satellite Pour l’Observation de la Terre (SPOT) VEGETATION (SPOT VGT) data (1998–2008) were used to describe and map variability in irrigated rice cropping patterns of the Mekong delta. Divergence statistics were used to evaluate signature separabilities of normalized difference vegetation index (NDVI) classes generated from the iterative self-organizing data analysis technique algorithm (ISODATA) classification of 10-day SPOT NDVI image series. Based on this evaluation, a map with 77 classes was selected. Out of these 77 mapped classes, 26 lasses with prior knowledge that they represent rice were selected to design the sampling scheme for fieldwork and for crop calendar characterization. Using the collected information of 112 farmers’ fields belonging to the 26 selected classes, the map produced provides highly accurate information on rice cropping patterns (94% overall accuracy, 0.93 Kappa coefficient). We found that the spatial distributions of the triple and the double rice cropping systems are highly related to the flooding regime from the Hau and Tien rivers. Areas that are highly vulnerable to flooding in the upper part and those that are saline in the north-western part of the delta mostly have a double rice cropping system, whilst areas in the central and the south-eastern parts mostly have a triple rice cropping system. In turn, the duration of flooding is highly correlated with the decision by farmers to cultivate shorter or longer duration rice varieties. The overall spatial variability mostly coincides with administrative units, indicating that crop pattern choices and water controlmeasures are locally synchronized. Water supply risks, soil acidity and salinity constraints and the anticipated highly fluctuating rice market prices all strongly influence specific farmers’ choices of rice varieties. These choices vary considerably annually, and therefore grown rice varieties are difficult to map. Our study demonstrates the high potential of optical hyper-temporal images, taken on a daily basis, to differentiate and map a high variety of irrigated rice cropping patterns and crop calendars at a high level of accuracy in spite of cloudy conditions.
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