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Remote sensing is useful for water quality assessments but current remote sensing applications favour parameters that are easy to detect such as chlorophyll-a. An assessment of the utility of Landsat 8 for detecting nutrients was conducted in Mazvikadei reservoir in Zimbabwe. The main objective was to determine whether nutrients often overlooked by remote sensing and yet are the main determinants of water quality can be remotely sensed. Sampling targeted ammonia, nitrates and reactive phosphorus from May to October 2015. In situ nutrient concentrations were regressed against reflectance derived from Landsat 8 imagery. Strong negative relationships were found between ammonia and the near-infrared band in July (R2 = 0.80, p < 0.05) as well as between nitrates and the blue band (R2 = 0.67, p < 0.05) in June. Overall, the results suggest that the cool dry season is the optimum time to use Landsat 8 for monitoring nutrients in tropical lakes. 相似文献
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Isaiah Gwitira Amon Murwira Mhosisi Masocha Fadzai M. Zengeya Munyaradzi Davis Shekede Joconiah Chirenda 《国际地球制图》2013,28(11):1163-1176
AbstractMalaria burden has considerably declined in the last 15 years mainly due to large-scale vector control. The continued decline can be sustained through malaria risk stratification. Malaria stratification is the classification of geographical areas according to malaria risk. In this study, ecological niche modelling using the maximum entropy algorithm was applied to predict malaria vector habitat suitability in terms of bioclimatic and topographic variables. The output vector suitability map was integrated with malaria prevalence data in a GIS to stratify Zimbabwe into different malaria risk zones. Five improved and validated malaria risk zones were successfully delimited for Zimbabwe based on the World Health Organization classification scheme. These results suggest that the probability of occurrence of major vectors of malaria is a key determinant of malaria prevalence. The delimited malaria risk zones could be used by National Malaria Control programmes to plan and implement targeted malaria interventions based on vector control. 相似文献
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Mhosisi Masocha Andrew K. Skidmore 《International Journal of Applied Earth Observation and Geoinformation》2011
Mapping the cover of invasive species using remotely sensed data alone is challenging, because many invaders occur as mid-level canopy species or as subtle understorey species and therefore contribute little to the spectral signatures captured by passive remote sensing devices. In this study, two common non-parametric classifiers namely, the neural network and support vector machine were used to map four cover classes of the invasive shrub Lantana camara in a protected game reserve and the adjacent area under communal land management in Zimbabwe. These classifiers were each combined with a geographic information system (GIS) expert system, in order to test whether the new hybrid classifiers yielded significantly more accurate invasive species cover maps than the single classifiers. The neural network, when used on its own, mapped the cover of L. camara with an overall accuracy of 71% and a Kappa index of agreement of 0.61. When the neural network was combined with an expert system, the overall accuracy and Kappa index of agreement significantly increased to 83% and 0.77, respectively. Similarly, the support vector machine achieved an overall accuracy of 64% with a Kappa index of agreement of 0.52, whereas the hybrid support vector machine and expert system classifier achieved a significantly higher overall accuracy of 76% and a Kappa index of agreement of 0.67. These results suggest that integrating conventional image classifiers with an expert system increases the accuracy of invasive species mapping. 相似文献
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Rain-fed agriculture is threatened by an increased frequency of droughts worldwide thereby putting millions of livelihoods at risk especially in sub-Saharan Africa. This makes drought preparedness critical. In this study, we sought to establish whether maize yield can be predicted using the number of dry dekads that occur at specific maize growth stages for purposes of yield early warning. The dry dekads were derived from remotely sensed Vegetation Condition Index calculated from the SPOT NDVI time series ranging from 1998 to 2013. Regression between dry dekads and maize yield show a negative linear relationship for four growing seasons (2010–2013) and indicates that dry dekads at both the vegetative and reproductive stages are important for predicting maize yield. Results suggest that early warning alert could be given using dry dekads that occur at the vegetative stage, while those at the reproductive stage can be used to give better yield estimate later on. 相似文献
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Tropical deforestation through logging activities poses a direct threat to biodiversity. However, the detection of logging has remained a challenge. Based on study sites in Zimbabwe and Zambia, we tested whether the Normalized Difference Vegetation Index (NDVI) and the Coefficient of Variation in NDVI (CVNDVI) derived from high and medium spatial resolution satellite data could be used to detect logging in dry and wet miombo woodlands. Separately, we integrated NDVI and CVNDVI in logistic regression to test whether each can be used to successfully predict logging in the study sites. We tested whether the spatial resolution of satellite data has an effect in detection of logging using NDVI and CVNDVI derived from Landsat 8 and Worldview-2. Based on the ROC curves, we concluded that remotely sensed data could provide an effective predictive tool for detecting logging. However, in wet miombo woodlands the predictive power of remotely sensed data is weak. 相似文献
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Water quality problems continue on a global scale and this creates the need for regular monitoring using cheaper technologies to inform management. The objective of this study was to test for significant relationships between the field-measured and Landsat 8 OLI sensor-retrieved water quality parameters. The study was carried out in two reservoirs with contrasting trophic states in Zimbabwe. Results show that the Blue/Red ratio had strong predictive relationships with Secchi disc transparency (R2 > 0.70) and turbidity (R2 ≥ 0.65). The Near-infrared/Red ratio was a strong predictor of chlorophyll-a in Mazvikadei (R2 > 0.84) whereas in Lake Chivero, which is more polluted, the red band was the most useful predictor (R2 = 0.69). Overall, our work demonstrates the utility of using Landsat 8 band ratios for remote assessment of water quality in African reservoirs as a value-addition to the traditional field-based methods, which are expensive resulting in data scarcity. 相似文献
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