Assessment of the responses of the urban thermal environment to climate is important, especially ... more Assessment of the responses of the urban thermal environment to climate is important, especially because of their possible influence on low- and high-temperature extreme events. This study assessed the combination of remotely sensed land surface temperature (LST) and local climate zones (LCZs) with in situ air temperature-retrieved extreme temperature indices. It aimed to assess the effect of urban growth on the three-dimensional thermal environment in the Bulawayo metropolitan area, Zimbabwe. LST and LCZ were derived from the Landsat data for 1990, 2005, and 2020, while extreme temperature indices and trends were derived from daily minimum and maximum temperature data from a local weather station. Results showed that the built LCZ expanded at the expense of vegetation-based LCZ. Average LST for each LCZ increased from 1990 to 2020, which was attributed to background warming, while the expansion of high LST areas was associated with LCZ transitions. Although average minimum temperat...
Urban growth, typified by conversion from natural to built-up impervious surfaces, is known to ca... more Urban growth, typified by conversion from natural to built-up impervious surfaces, is known to cause warming and associated adverse impacts. Local climate zones present a standardized technique for evaluating the implications of urban land use and surface changes on temperatures of the overlying atmosphere. In this study, long term changes in local climate zones of the Bulawayo metropolitan city were used to assess the influence of the city’s growth on its thermal characteristics. The zones were mapped using the World Urban Database and Access Portal Tool (WUDAPT) procedure while Landsat data were used to determine temporal changes. Data were divided into 1990 to 2005 and 2005 to 2020 temporal splits and intensity analysis used to characterize transformation patterns at each interval. Results indicated that growth of the built local climate zones (LCZ) in Bulawayo was faster in the 1990 to 2005 interval than the 2005 to 2020. Transition level intensity analysis showed that growth of...
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
This study sought to determine the impact of urban growth on future micro-climate of Harare by pr... more This study sought to determine the impact of urban growth on future micro-climate of Harare by predicting future distribution of land use and land cover (LULC), as well as land surface temperature. Landsat series data was used to map Land Use and Land Cover and land surface temperature distribution during the month of October for the year 1984, 1993, 2001 and 2015. The Cellular Automata Markov Chain analysis was used to determine long term landscape transformation at 10-year time steps from 2015 to 2045. The value of a range of vegetation and non-vegetation indices to predict land surface temperature were also tested. Results show that the Urban Index (UI), a non-vegetation index was the best predictor of surface temperature (R=0.9831). Based on 1984 and 2015 changes, results showed that high density built-up areas will increase monotonically from 470.02 in 2015 to 490.36km2 in 2045, while green spaces would decrease from 57.42 to 27.85km2 during the same period. Using UI as predictor of land surface temperature, the 18-28°C class will decrease in coverage between 2015 and 2040, while the 36-45°C category will increase in proportion covered from 42.5 to 58% of city. We concluded that continued urban growth will increase warming and result in higher future temperatures.
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Forests are at risk of extinction due to increased competition for land in urban areas due to exp... more Forests are at risk of extinction due to increased competition for land in urban areas due to expansion of cities. Forests are important as they act as heat and carbon sinks hence the need to monitor their spatial and temporal changes. We investigated the link between forest cover changes and land surface temperature dynamics in Freetown and Bo town Sierra Leone between 1998 and 2015 using Landsat data. Results showed that forests are expanding in Freetown while diminishing in Bo town. As a result, land surface temperatures warmed faster in Bo town than in Freetown where the land surface temperature moderation value of dense forest increased with time. Surface temperature increased by 4°C in Bo town while it increased by less than 2°C in Freetown due to differences in forest changes between the cities. The results showed that increasing tree density in forests is strong land surface temperature moderation measure. Future urban growth must consider impact of forest cover in order to ensure sustainability.
Climate change has resulted in increased rainfall variability over many parts of the world includ... more Climate change has resulted in increased rainfall variability over many parts of the world including Southern Africa. As such, droughts and floods have become a frequent phenomenon in Zimbabwe and have potential to intensify socio-economic stressors. This study examined possible forcing factors behind the occurrence of extreme summer events using re-analysis datasets. Composite analysis and correlation methods were used to identify circulation mechanisms and their strength in determining rainfall patterns in Zimbabwe. Predominantly northerly airflow in the lower troposphere was found to favor wet while southerly airflow favors dry seasons. Negative geopotential anomalies (minimum of −20 hPa) to the west of Zimbabwe in the middle levels characterize wet summers which swing to positive anomalies (+24 hPa) during dry summers. Positive SST anomalies (maximum of 0.4) exist to the southwest of Madagascar extending to the western shore on the Angola-Namibian border characterize wet summers which swing to negative anomalies (−0.2 oC) during dry summer seasons. SST anomalies in the South western Indian and South eastern Atlantic oceans are crucial in the determination of the strength of both the South Indian and Atlantic Ocean high pressure systems which in turn control moisture advection and convergence into Zimbabwe during the summer period. If these SST anomalies at lag times of about 3 months can be used to predict the incoming summer circulation patterns then the accuracy of summer seasonal outlook forecasts can be improved. Studying the mechanisms behind drought and flood occurrence is important to the country which is in the process of downscaling regional prediction products to improve the accuracy of seasonal forecasts. These findings are useful in crafting relevant measures to maximize the benefits and minimize the risks of extreme rainfall events.
Drought has severe impacts on human society and ecosystems. In this study, we used data acquired ... more Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a s...
The study investigates the relationship between drought and vegetation variations in three main b... more The study investigates the relationship between drought and vegetation variations in three main basins of western and southwestern of Iran, using the comprehensive approach of time-series analysis, Standardized Precipitation Index (SPI), and anomaly calculation. A total of 30 ground stations’ daily meteorological data and the MODIS 16-day composite NDVI products (2000–2017) were used in this case. The results showed that in the Great Karoun River (GKRW) and Karkheh River (KRW) sub-regions, the NDVI decreased slightly over the study period. Simultaneously, in the West Marginal (WMW) sub-region the NDVI slightly increased somewhat. Overall, the NDVI in the whole study area presented an insignificant decrease. Also the results found that there is a significant relationship ( p < 0.02) between the NDVI (0.3–0.7) with spring drought and between NDVI (0.2–0.3) with fall drought ( p < 0.01). There is a marginally significant relationship ( R = 0.43, p = 0.07) between NDVI (0.3–0.4) with fall drought and a relatively high, but insignificant relationship between NDVI (0.7–0.8) with spring drought ( R = 0.41, p = 0.09). Low temperature can play an important role in determining the relationship between SPI and NDVI, which evidenced that it can trade-off the effect of a very wet year. As well as a year with very wet condition can affect the NDVI of the coming years. Since summer is hot season in the study area and most of the vegetation consists of shrubs and grasslands, of which the NDVI ranges between 0.2 and 0.4, the vegetation cover can be significantly affected by a wet summer with abundant precipitation.
In the face of a changing climate, knowledge on the characteristics of wet and dry summers and th... more In the face of a changing climate, knowledge on the characteristics of wet and dry summers and their modes of variability becomes of great importance to Zimbabwe so that proper policies and planning can be implemented to maximise the positive impacts of climate change while minimising its negative impacts. We used time series of rainfall anomaly index, empirical orthogonal function analysis and composite analysis to determine the temporal and spatial characteristics of summer rainfall in Zimbabwe between 1980 and 2013. Results indicate that there is a possible shortening in the length of the summer season, running from November to March. There were 14 anomalous summer seasons (7 dry and 7 wet) during the 33 summer seasons in the study period. Three dominant modes of variability were identified for Zimbabwean summer rainfall for the period under study: (1) an east–west gradient accounting for about 63% of the total variability, (2) a northeast–southwest oscillation accounting for abo...
Monitoring vegetation changes over time is very important in dry areas such as Iran, given its pr... more Monitoring vegetation changes over time is very important in dry areas such as Iran, given its pronounced drought-prone agricultural system. Vegetation indices derived from remotely sensed satellite imageries are successfully used to monitor vegetation changes at various scales. Atmospheric dust as well as airborne particles, particularly gases and clouds, significantly affect the reflection of energy from the surface, especially in visible, short and infrared wavelengths. This results in imageries with missing data (gaps) and outliers while vegetation change analysis requires integrated and complete time series data. This study investigated the performance of HANTS (Harmonic ANalysis of Time Series) algorithm and (M)-SSA ((Multi-channel) Singular Spectrum Analysis) algorithm in reconstruction of wide-gap of missing data. The time series of Normalized Difference Vegetation Index (NDVI) retrieved from Landsat TM in combination with 250m MODIS NDVI time image products are used to simu...
Having updated knowledge of cropland extent is essential for crop monitoring and food security ea... more Having updated knowledge of cropland extent is essential for crop monitoring and food security early warning. Previous research has proposed different methods and adopted various datasets for mapping cropland areas at regional to global scales. However, most approaches did not consider the characteristics of farming systems and apply the same classification method in different agroecological zones (AEZs). Furthermore, the acquisition of in situ samples for classification training remains challenging. To address these knowledge gaps and challenges, this study applied a zone-specific classification by comparing four classifiers (random forest, the support vector machine (SVM), the classification and regression tree (CART) and minimum distance) for cropland mapping over four different AEZs in the Zambezi River basin (ZRB). Landsat-8 and Sentinel-2 data and derived indices were used and synthesized to generate thirty-five layers for classification on the Google Earth Engine platform. Tr...
Climate change has resulted in increased rainfall variability over many parts of the world includ... more Climate change has resulted in increased rainfall variability over many parts of the world including Southern Africa. As such, droughts and floods have become a frequent phenomenon in Zimbabwe and have potential to intensify socio-economic stressors. This study examined possible forcing factors behind the occurrence of extreme summer events using re-analysis datasets. Composite analysis and correlation methods were used to identify circulation mechanisms and their strength in determining rainfall patterns in Zimbabwe. Predominantly northerly airflow in the lower troposphere was found to favor wet while southerly airflow favors dry seasons. Negative geopotential anomalies (minimum of −20 hPa) to the west of Zimbabwe in the middle levels characterize wet summers which swing to positive anomalies (+24 hPa) during dry summers. Positive SST anomalies (maximum of 0.4) exist to the southwest of Madagascar extending to the western shore on the Angola-Namibian border characterize wet summers which swing to negative anomalies (−0.2 oC) during dry summer seasons. SST anomalies in the South western Indian and South eastern Atlantic oceans are crucial in the determination of the strength of both the South Indian and Atlantic Ocean high pressure systems which in turn control moisture advection and convergence into Zimbabwe during the summer period. If these SST anomalies at lag times of about 3 months can be used to predict the incoming summer circulation patterns then the accuracy of summer seasonal outlook forecasts can be improved. Studying the mechanisms behind drought and flood occurrence is important to the country which is in the process of downscaling regional prediction products to improve the accuracy of seasonal forecasts. These findings are useful in crafting relevant measures to maximize the benefits and minimize the risks of extreme rainfall events.
In the present study, synoptic-dynamic aspects of extreme precipitation in Karoun River Basin wer... more In the present study, synoptic-dynamic aspects of extreme precipitation in Karoun River Basin were analyzed using two types of data, namely (1) grid views of Iran’s daily precipitation as registered in 1434 stations and (2) atmospheric data including sea-level pressure (SLP), geopotential height (HGT) for 1000, 850, and 500 hPa, temperature, and U&V wind components for a 54-year statistical period (1960–2013). In order to identify extreme precipitation, three criteria were used: the precipitation events should exceed 95th percentile threshold, have a minimum of 50% coverage with spatial continuity, and last for at least two consecutive days. The results showed that extreme precipitation of study area are affected by atmospheric patterns of the Caspian Sea low pressure-European migratory high pressure, Eastern Mediterranean low pressure-Central Iran low pressure, the Eastern Mediterranean low pressure-Siberian-Tibetan high pressure, and Sudanic low pressure-gigantic European high pressure. In all these patterns, the cyclonic motion is observed at all of the atmosphere levels, which indicates the effect of the atmosphere dynamic mechanisms at the time of occurrence of extreme precipitation. At 300 hPa level, the left side of the jet stream, the left exit of the subtropical jet stream, and the right entrance of the polar front jet stream were located over the study area.
Abstract Crop diseases monitoring is critical in understanding the effects of diseases on crop pr... more Abstract Crop diseases monitoring is critical in understanding the effects of diseases on crop production and associated implications on food security. The aim of this study was to assess the utility of the 10 m resolution Sentinel 2 data set, in detecting and mapping Maize Streak Virus (MSV) disease in Ofcolaco farms in Tzaneen, South Africa. Specifically, the study sought to spectrally discriminate and map maize infected with MSV from other land-cover classes. To achieve this objective two analysis approaches were used: spectral analysis (Test I: spectral bands; Test II: spectral bands + spectral vegetation indices) using random forest algorithm in a supervised classification approach. The indices combined with spectral bands were EVI, SAVI, NDVI, GNDVI, GLI and MSAVI. Results indicated that infected maize was highly separable from health maize and other land cover classes (TDSI > 1.8). The mapping accuracy was high using spectral data (Overall accuracy = 85.29% and Kappa = 0.79) and even higher when spectral bands were combined with derived vegetation indices (Overall accuracy = 89.43% and Kappa = 0.84). The results of the study show that the 10 m resolution multispectral Sentinel 2 data set can be used to detect and map maize infected by MSV. The findings are important in showing the value of combining 10 m spectral data with derived indices from Sentinel 2 in improving monitoring of maize steak virus in resource-constrained nations.
Remote Sensing Applications: Society and Environment
Abstract Owing to the proven capability of remotely sensed data in the extraction and analysis of... more Abstract Owing to the proven capability of remotely sensed data in the extraction and analysis of land use land cover (LULC) change, Landsat ETM+ and OLI imagery of 2000 and 2015 have been used in this research to carry out the LULC change comparative analysis in Bo and Freetown, two major urban areas in Sierra Leone, Africa. The supervised imagery classification with maximum likelihood algorithm method was adopted for the extraction of LULC categories. To demonstrate our idea effectively, we used the land change modeller integrated into IDRISI Selva software package to quantify and map the changes of each LULC category. Employing an error matrix table and estimator of Kappa statistics (Khat), we achieved overall accuracy and Khat greater than 80% for both cities and class level accuracies were also achieved as greater than 70%. The LULC change statistics show dynamic characteristics of LULC in the areas where maximum fluctuation was observed in dense vegetation category in Bo and agricultural land in Freetown. The built-up area shows a continuous increasing trend in both cities. Results of our analysis demonstrated that dense vegetation increased by 1024 ha (ha) in Bo whereas it reduced by 3807 ha (ha) in Freetown between 2000 and 2015 study years. Likewise, agricultural land increased by 545 ha (ha) in Bo and decreased by 9145 ha (ha) in Freetown during the same period. It is worth noting that the built-up area increased in both cities as 1326 ha (ha) and 8543 ha (ha) were recorded in Bo and Freetown, respectively. The spatial trend of LULC transition reveals that most of the transition has been occurring in the central part of Bo; whereas the transition occurs in the northern and southern parts in Freetown. However, both cities witness transition at the southern part with regards to dense vegetation category. These findings could assist in making policies for the efficient use of natural resources leading to the development of sustainable urban environments.
Assessment of the responses of the urban thermal environment to climate is important, especially ... more Assessment of the responses of the urban thermal environment to climate is important, especially because of their possible influence on low- and high-temperature extreme events. This study assessed the combination of remotely sensed land surface temperature (LST) and local climate zones (LCZs) with in situ air temperature-retrieved extreme temperature indices. It aimed to assess the effect of urban growth on the three-dimensional thermal environment in the Bulawayo metropolitan area, Zimbabwe. LST and LCZ were derived from the Landsat data for 1990, 2005, and 2020, while extreme temperature indices and trends were derived from daily minimum and maximum temperature data from a local weather station. Results showed that the built LCZ expanded at the expense of vegetation-based LCZ. Average LST for each LCZ increased from 1990 to 2020, which was attributed to background warming, while the expansion of high LST areas was associated with LCZ transitions. Although average minimum temperat...
Urban growth, typified by conversion from natural to built-up impervious surfaces, is known to ca... more Urban growth, typified by conversion from natural to built-up impervious surfaces, is known to cause warming and associated adverse impacts. Local climate zones present a standardized technique for evaluating the implications of urban land use and surface changes on temperatures of the overlying atmosphere. In this study, long term changes in local climate zones of the Bulawayo metropolitan city were used to assess the influence of the city’s growth on its thermal characteristics. The zones were mapped using the World Urban Database and Access Portal Tool (WUDAPT) procedure while Landsat data were used to determine temporal changes. Data were divided into 1990 to 2005 and 2005 to 2020 temporal splits and intensity analysis used to characterize transformation patterns at each interval. Results indicated that growth of the built local climate zones (LCZ) in Bulawayo was faster in the 1990 to 2005 interval than the 2005 to 2020. Transition level intensity analysis showed that growth of...
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
This study sought to determine the impact of urban growth on future micro-climate of Harare by pr... more This study sought to determine the impact of urban growth on future micro-climate of Harare by predicting future distribution of land use and land cover (LULC), as well as land surface temperature. Landsat series data was used to map Land Use and Land Cover and land surface temperature distribution during the month of October for the year 1984, 1993, 2001 and 2015. The Cellular Automata Markov Chain analysis was used to determine long term landscape transformation at 10-year time steps from 2015 to 2045. The value of a range of vegetation and non-vegetation indices to predict land surface temperature were also tested. Results show that the Urban Index (UI), a non-vegetation index was the best predictor of surface temperature (R=0.9831). Based on 1984 and 2015 changes, results showed that high density built-up areas will increase monotonically from 470.02 in 2015 to 490.36km2 in 2045, while green spaces would decrease from 57.42 to 27.85km2 during the same period. Using UI as predictor of land surface temperature, the 18-28°C class will decrease in coverage between 2015 and 2040, while the 36-45°C category will increase in proportion covered from 42.5 to 58% of city. We concluded that continued urban growth will increase warming and result in higher future temperatures.
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Forests are at risk of extinction due to increased competition for land in urban areas due to exp... more Forests are at risk of extinction due to increased competition for land in urban areas due to expansion of cities. Forests are important as they act as heat and carbon sinks hence the need to monitor their spatial and temporal changes. We investigated the link between forest cover changes and land surface temperature dynamics in Freetown and Bo town Sierra Leone between 1998 and 2015 using Landsat data. Results showed that forests are expanding in Freetown while diminishing in Bo town. As a result, land surface temperatures warmed faster in Bo town than in Freetown where the land surface temperature moderation value of dense forest increased with time. Surface temperature increased by 4°C in Bo town while it increased by less than 2°C in Freetown due to differences in forest changes between the cities. The results showed that increasing tree density in forests is strong land surface temperature moderation measure. Future urban growth must consider impact of forest cover in order to ensure sustainability.
Climate change has resulted in increased rainfall variability over many parts of the world includ... more Climate change has resulted in increased rainfall variability over many parts of the world including Southern Africa. As such, droughts and floods have become a frequent phenomenon in Zimbabwe and have potential to intensify socio-economic stressors. This study examined possible forcing factors behind the occurrence of extreme summer events using re-analysis datasets. Composite analysis and correlation methods were used to identify circulation mechanisms and their strength in determining rainfall patterns in Zimbabwe. Predominantly northerly airflow in the lower troposphere was found to favor wet while southerly airflow favors dry seasons. Negative geopotential anomalies (minimum of −20 hPa) to the west of Zimbabwe in the middle levels characterize wet summers which swing to positive anomalies (+24 hPa) during dry summers. Positive SST anomalies (maximum of 0.4) exist to the southwest of Madagascar extending to the western shore on the Angola-Namibian border characterize wet summers which swing to negative anomalies (−0.2 oC) during dry summer seasons. SST anomalies in the South western Indian and South eastern Atlantic oceans are crucial in the determination of the strength of both the South Indian and Atlantic Ocean high pressure systems which in turn control moisture advection and convergence into Zimbabwe during the summer period. If these SST anomalies at lag times of about 3 months can be used to predict the incoming summer circulation patterns then the accuracy of summer seasonal outlook forecasts can be improved. Studying the mechanisms behind drought and flood occurrence is important to the country which is in the process of downscaling regional prediction products to improve the accuracy of seasonal forecasts. These findings are useful in crafting relevant measures to maximize the benefits and minimize the risks of extreme rainfall events.
Drought has severe impacts on human society and ecosystems. In this study, we used data acquired ... more Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a s...
The study investigates the relationship between drought and vegetation variations in three main b... more The study investigates the relationship between drought and vegetation variations in three main basins of western and southwestern of Iran, using the comprehensive approach of time-series analysis, Standardized Precipitation Index (SPI), and anomaly calculation. A total of 30 ground stations’ daily meteorological data and the MODIS 16-day composite NDVI products (2000–2017) were used in this case. The results showed that in the Great Karoun River (GKRW) and Karkheh River (KRW) sub-regions, the NDVI decreased slightly over the study period. Simultaneously, in the West Marginal (WMW) sub-region the NDVI slightly increased somewhat. Overall, the NDVI in the whole study area presented an insignificant decrease. Also the results found that there is a significant relationship ( p < 0.02) between the NDVI (0.3–0.7) with spring drought and between NDVI (0.2–0.3) with fall drought ( p < 0.01). There is a marginally significant relationship ( R = 0.43, p = 0.07) between NDVI (0.3–0.4) with fall drought and a relatively high, but insignificant relationship between NDVI (0.7–0.8) with spring drought ( R = 0.41, p = 0.09). Low temperature can play an important role in determining the relationship between SPI and NDVI, which evidenced that it can trade-off the effect of a very wet year. As well as a year with very wet condition can affect the NDVI of the coming years. Since summer is hot season in the study area and most of the vegetation consists of shrubs and grasslands, of which the NDVI ranges between 0.2 and 0.4, the vegetation cover can be significantly affected by a wet summer with abundant precipitation.
In the face of a changing climate, knowledge on the characteristics of wet and dry summers and th... more In the face of a changing climate, knowledge on the characteristics of wet and dry summers and their modes of variability becomes of great importance to Zimbabwe so that proper policies and planning can be implemented to maximise the positive impacts of climate change while minimising its negative impacts. We used time series of rainfall anomaly index, empirical orthogonal function analysis and composite analysis to determine the temporal and spatial characteristics of summer rainfall in Zimbabwe between 1980 and 2013. Results indicate that there is a possible shortening in the length of the summer season, running from November to March. There were 14 anomalous summer seasons (7 dry and 7 wet) during the 33 summer seasons in the study period. Three dominant modes of variability were identified for Zimbabwean summer rainfall for the period under study: (1) an east–west gradient accounting for about 63% of the total variability, (2) a northeast–southwest oscillation accounting for abo...
Monitoring vegetation changes over time is very important in dry areas such as Iran, given its pr... more Monitoring vegetation changes over time is very important in dry areas such as Iran, given its pronounced drought-prone agricultural system. Vegetation indices derived from remotely sensed satellite imageries are successfully used to monitor vegetation changes at various scales. Atmospheric dust as well as airborne particles, particularly gases and clouds, significantly affect the reflection of energy from the surface, especially in visible, short and infrared wavelengths. This results in imageries with missing data (gaps) and outliers while vegetation change analysis requires integrated and complete time series data. This study investigated the performance of HANTS (Harmonic ANalysis of Time Series) algorithm and (M)-SSA ((Multi-channel) Singular Spectrum Analysis) algorithm in reconstruction of wide-gap of missing data. The time series of Normalized Difference Vegetation Index (NDVI) retrieved from Landsat TM in combination with 250m MODIS NDVI time image products are used to simu...
Having updated knowledge of cropland extent is essential for crop monitoring and food security ea... more Having updated knowledge of cropland extent is essential for crop monitoring and food security early warning. Previous research has proposed different methods and adopted various datasets for mapping cropland areas at regional to global scales. However, most approaches did not consider the characteristics of farming systems and apply the same classification method in different agroecological zones (AEZs). Furthermore, the acquisition of in situ samples for classification training remains challenging. To address these knowledge gaps and challenges, this study applied a zone-specific classification by comparing four classifiers (random forest, the support vector machine (SVM), the classification and regression tree (CART) and minimum distance) for cropland mapping over four different AEZs in the Zambezi River basin (ZRB). Landsat-8 and Sentinel-2 data and derived indices were used and synthesized to generate thirty-five layers for classification on the Google Earth Engine platform. Tr...
Climate change has resulted in increased rainfall variability over many parts of the world includ... more Climate change has resulted in increased rainfall variability over many parts of the world including Southern Africa. As such, droughts and floods have become a frequent phenomenon in Zimbabwe and have potential to intensify socio-economic stressors. This study examined possible forcing factors behind the occurrence of extreme summer events using re-analysis datasets. Composite analysis and correlation methods were used to identify circulation mechanisms and their strength in determining rainfall patterns in Zimbabwe. Predominantly northerly airflow in the lower troposphere was found to favor wet while southerly airflow favors dry seasons. Negative geopotential anomalies (minimum of −20 hPa) to the west of Zimbabwe in the middle levels characterize wet summers which swing to positive anomalies (+24 hPa) during dry summers. Positive SST anomalies (maximum of 0.4) exist to the southwest of Madagascar extending to the western shore on the Angola-Namibian border characterize wet summers which swing to negative anomalies (−0.2 oC) during dry summer seasons. SST anomalies in the South western Indian and South eastern Atlantic oceans are crucial in the determination of the strength of both the South Indian and Atlantic Ocean high pressure systems which in turn control moisture advection and convergence into Zimbabwe during the summer period. If these SST anomalies at lag times of about 3 months can be used to predict the incoming summer circulation patterns then the accuracy of summer seasonal outlook forecasts can be improved. Studying the mechanisms behind drought and flood occurrence is important to the country which is in the process of downscaling regional prediction products to improve the accuracy of seasonal forecasts. These findings are useful in crafting relevant measures to maximize the benefits and minimize the risks of extreme rainfall events.
In the present study, synoptic-dynamic aspects of extreme precipitation in Karoun River Basin wer... more In the present study, synoptic-dynamic aspects of extreme precipitation in Karoun River Basin were analyzed using two types of data, namely (1) grid views of Iran’s daily precipitation as registered in 1434 stations and (2) atmospheric data including sea-level pressure (SLP), geopotential height (HGT) for 1000, 850, and 500 hPa, temperature, and U&V wind components for a 54-year statistical period (1960–2013). In order to identify extreme precipitation, three criteria were used: the precipitation events should exceed 95th percentile threshold, have a minimum of 50% coverage with spatial continuity, and last for at least two consecutive days. The results showed that extreme precipitation of study area are affected by atmospheric patterns of the Caspian Sea low pressure-European migratory high pressure, Eastern Mediterranean low pressure-Central Iran low pressure, the Eastern Mediterranean low pressure-Siberian-Tibetan high pressure, and Sudanic low pressure-gigantic European high pressure. In all these patterns, the cyclonic motion is observed at all of the atmosphere levels, which indicates the effect of the atmosphere dynamic mechanisms at the time of occurrence of extreme precipitation. At 300 hPa level, the left side of the jet stream, the left exit of the subtropical jet stream, and the right entrance of the polar front jet stream were located over the study area.
Abstract Crop diseases monitoring is critical in understanding the effects of diseases on crop pr... more Abstract Crop diseases monitoring is critical in understanding the effects of diseases on crop production and associated implications on food security. The aim of this study was to assess the utility of the 10 m resolution Sentinel 2 data set, in detecting and mapping Maize Streak Virus (MSV) disease in Ofcolaco farms in Tzaneen, South Africa. Specifically, the study sought to spectrally discriminate and map maize infected with MSV from other land-cover classes. To achieve this objective two analysis approaches were used: spectral analysis (Test I: spectral bands; Test II: spectral bands + spectral vegetation indices) using random forest algorithm in a supervised classification approach. The indices combined with spectral bands were EVI, SAVI, NDVI, GNDVI, GLI and MSAVI. Results indicated that infected maize was highly separable from health maize and other land cover classes (TDSI > 1.8). The mapping accuracy was high using spectral data (Overall accuracy = 85.29% and Kappa = 0.79) and even higher when spectral bands were combined with derived vegetation indices (Overall accuracy = 89.43% and Kappa = 0.84). The results of the study show that the 10 m resolution multispectral Sentinel 2 data set can be used to detect and map maize infected by MSV. The findings are important in showing the value of combining 10 m spectral data with derived indices from Sentinel 2 in improving monitoring of maize steak virus in resource-constrained nations.
Remote Sensing Applications: Society and Environment
Abstract Owing to the proven capability of remotely sensed data in the extraction and analysis of... more Abstract Owing to the proven capability of remotely sensed data in the extraction and analysis of land use land cover (LULC) change, Landsat ETM+ and OLI imagery of 2000 and 2015 have been used in this research to carry out the LULC change comparative analysis in Bo and Freetown, two major urban areas in Sierra Leone, Africa. The supervised imagery classification with maximum likelihood algorithm method was adopted for the extraction of LULC categories. To demonstrate our idea effectively, we used the land change modeller integrated into IDRISI Selva software package to quantify and map the changes of each LULC category. Employing an error matrix table and estimator of Kappa statistics (Khat), we achieved overall accuracy and Khat greater than 80% for both cities and class level accuracies were also achieved as greater than 70%. The LULC change statistics show dynamic characteristics of LULC in the areas where maximum fluctuation was observed in dense vegetation category in Bo and agricultural land in Freetown. The built-up area shows a continuous increasing trend in both cities. Results of our analysis demonstrated that dense vegetation increased by 1024 ha (ha) in Bo whereas it reduced by 3807 ha (ha) in Freetown between 2000 and 2015 study years. Likewise, agricultural land increased by 545 ha (ha) in Bo and decreased by 9145 ha (ha) in Freetown during the same period. It is worth noting that the built-up area increased in both cities as 1326 ha (ha) and 8543 ha (ha) were recorded in Bo and Freetown, respectively. The spatial trend of LULC transition reveals that most of the transition has been occurring in the central part of Bo; whereas the transition occurs in the northern and southern parts in Freetown. However, both cities witness transition at the southern part with regards to dense vegetation category. These findings could assist in making policies for the efficient use of natural resources leading to the development of sustainable urban environments.
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