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Oil palm is recognized as a golden crop, as it produces the highest oil yield among oil seed crops. Malaysia is the world’s second largest producer of palm oil; 16% of its land is planted with oil palm. To cope with the ever-increasing global demand on edible oil, additional areas of oil palm are forecast to increase globally by 12 to 19 Mha by 2050. Multisensor remote sensing plays an important role in providing relevant, timely, and accurate information that can be developed into a plantation monitoring system to optimize production and sustainability. The aim of this study was to simultaneously exploit the synthetic aperture radar ALOS PALSAR 2, a form of microwave remote sensing, in combination with visible (red) data from Landsat Thematic Mapper to obtain a holistic view of a plantation. A manipulation of the horizontal–horizontal (HH) and horizontal–vertical (HV) polarizations of ALOS PALSAR data detected oil palm trees and water bodies, while the red spectra L-band from Landsat data (optical) could effectively identify built up areas and vertical–horizontal (VH) polarization from Sentinel C-band data detected bare land. These techniques produced an oil palm area classification with overall accuracies of 98.36% and 0.78 kappa coefficient for Peninsular Malaysia. The total oil palm area in Peninsular Malaysia was estimated to be about 3.48% higher than the value reported by the Malaysian Palm Oil Board. The over estimation may be due the MPOB’s statistics that do not include unregistered small holder oil palm plantations. In this study, we were able to discriminate most of the rubber areas.
Nazarin Ezzaty Mohd Najib; Kasturi Devi Kanniah; Arthur P. Cracknell; Le Yu. Synergy of Active and Passive Remote Sensing Data for Effective Mapping of Oil Palm Plantation in Malaysia. Forests 2020, 11, 858 .
AMA StyleNazarin Ezzaty Mohd Najib, Kasturi Devi Kanniah, Arthur P. Cracknell, Le Yu. Synergy of Active and Passive Remote Sensing Data for Effective Mapping of Oil Palm Plantation in Malaysia. Forests. 2020; 11 (8):858.
Chicago/Turabian StyleNazarin Ezzaty Mohd Najib; Kasturi Devi Kanniah; Arthur P. Cracknell; Le Yu. 2020. "Synergy of Active and Passive Remote Sensing Data for Effective Mapping of Oil Palm Plantation in Malaysia." Forests 11, no. 8: 858.
Anita Simic Milas; Arthur P. Cracknell; Timothy A. Warner. Drones – the third generation source of remote sensing data. International Journal of Remote Sensing 2018, 39, 7125 -7137.
AMA StyleAnita Simic Milas, Arthur P. Cracknell, Timothy A. Warner. Drones – the third generation source of remote sensing data. International Journal of Remote Sensing. 2018; 39 (21):7125-7137.
Chicago/Turabian StyleAnita Simic Milas; Arthur P. Cracknell; Timothy A. Warner. 2018. "Drones – the third generation source of remote sensing data." International Journal of Remote Sensing 39, no. 21: 7125-7137.
Philippa J. Mason; Arthur P Cracknell. The Earth as a planet. International Journal of Remote Sensing 2018, 39, 5767 -5769.
AMA StylePhilippa J. Mason, Arthur P Cracknell. The Earth as a planet. International Journal of Remote Sensing. 2018; 39 (18):5767-5769.
Chicago/Turabian StylePhilippa J. Mason; Arthur P Cracknell. 2018. "The Earth as a planet." International Journal of Remote Sensing 39, no. 18: 5767-5769.
In recent decades, palm oil, which forms one of the world’s major bulk feedstock and oil crops, has been cultivated at an increasing scale to meet new demand. Oil palm expansion has driven not only socio-economic development but also serious ecological problems and environmental pollution through deforestation and fires to clear the forests. Uneconomic oil palm plantations can influence the balance of regional ecosystems and the carbon cycle. Many countries report national statistics on the area of oil palm, but few document the extent and locations of oil palm plantations. In this study, we produce and make available oil palm maps that include 15 countries with more than 10,000 ha of planted oil palms. Phased Array Type L-band Synthetic Aperture (PALSAR-2) images and high-resolution (<2.5 m) images in Google Earth were used to produce oil palm maps by supervised classification and visual interpretation. Two independent verification systems were used to evaluate map accuracy. The characteristics of oil palm plantations distribution and their environment suitability including terrain and climate conditions of the global oil palm planted regions are also discussed. The results indicate that the total area of oil palm in global in 2016 was estimated to be 29.49 million hectares (Mha) although the mapping result showed a good correlation with other records, but relatively large uncertainty in Africa. Most oil palm trees grow in warm (24–29.5°C), wet conditions (1000–4000 mm p.a. of precipitation), flat terrain (slope less than 8°), and low elevation (0–800 m); however, these growing conditions are slightly different in different continents.
Yuqi Cheng; Le Yu; Yidi Xu; Xiaoxuan Liu; Hui Lu; Arthur P. Cracknell; Kasturi Kanniah; Peng Gong. Towards global oil palm plantation mapping using remote-sensing data. International Journal of Remote Sensing 2018, 39, 5891 -5906.
AMA StyleYuqi Cheng, Le Yu, Yidi Xu, Xiaoxuan Liu, Hui Lu, Arthur P. Cracknell, Kasturi Kanniah, Peng Gong. Towards global oil palm plantation mapping using remote-sensing data. International Journal of Remote Sensing. 2018; 39 (18):5891-5906.
Chicago/Turabian StyleYuqi Cheng; Le Yu; Yidi Xu; Xiaoxuan Liu; Hui Lu; Arthur P. Cracknell; Kasturi Kanniah; Peng Gong. 2018. "Towards global oil palm plantation mapping using remote-sensing data." International Journal of Remote Sensing 39, no. 18: 5891-5906.
Satellite and ground-based observations are used to explore the composite oceanic–atmospheric link known as the El Niño/La Niña Southern Oscillation (ENSO) phenomenon, which is closely associated with extreme weather events (e.g. heat waves, tornadoes, floods, and droughts), incidence of epidemic diseases (e.g. malaria), severe coral bleaching, etc. The ENSO temporal evolution depends on the energy exchange within the coupled ocean/atmosphere system. Its cycle has an average period of about 4 years, but there is considerable modulation of it from several sources and this is not yet fully understood. In this article, we attempted to explore the intrinsic features of the Best ENSO Index (BEI) from 1870 to 2017. Studying the distribution that characterizes BEI increments, the asymptotic power-law scaling was revealed in their extreme fluctuations. Additionally, in order to study the evolution of BEI data over time, the detrended fluctuation analysis was used, which showed positive long-range correlations of power-law type and multifractal behaviour. These results aim to give a better insight into the global signature of ENSO evolution, considering both the continuous natural interactions taking place between the oceans and the atmosphere and anthropogenic effects. Furthermore, the results obtained could be employed to elucidate the development of more accurate advanced modelling of ocean–atmosphere interactions, thereby improving climate change projections.
Costas A Varotsos; Arthur P. Cracknell; Maria N. Efstathiou. The global signature of the El Niño/La Niña Southern Oscillation. International Journal of Remote Sensing 2018, 39, 5965 -5977.
AMA StyleCostas A Varotsos, Arthur P. Cracknell, Maria N. Efstathiou. The global signature of the El Niño/La Niña Southern Oscillation. International Journal of Remote Sensing. 2018; 39 (18):5965-5977.
Chicago/Turabian StyleCostas A Varotsos; Arthur P. Cracknell; Maria N. Efstathiou. 2018. "The global signature of the El Niño/La Niña Southern Oscillation." International Journal of Remote Sensing 39, no. 18: 5965-5977.
The extent of oil palm plantations has increased rapidly in Malaysia over the past few decades. To evaluate ecological effects and economic values, it is important to produce an accurate oil palm map for Malaysia. The Phased Array Type L-band Synthetic Aperture Radar (PALSAR) on the Advance Land Observing Satellite (ALOS) is useful in land-cover mapping in tropical regions under all-weather conditions. In this study, PALSAR-2 images from 2015 were used for oil palm mapping with maximum likelihood classifier (MLC)-based supervised classification. The processed PALSAR-2 data were resampled to multiple coarser resolutions (50, 100, 250, 500, and 1000 m), and then used to investigate the effect of speckle in oil palm mapping. Both independent testing samples and inventories from the Malaysia Palm Oil Board (MPOB) were used to evaluate the mapping accuracy. The oil palm mapping result indicates 50–500 m to be a good resolution for either retaining spatial details or reducing speckle noise of PALSAR-2 images. Among which, the best overall mapping accuracies and average oil palm accuracies reached 94.50% and 89.78%, respectively. Moreover, the oil palm area derived from the 100-m resolution map is 6.14 million hectares (Mha), which is the closest to the official MPOB inventories (~8.87% overestimation).
Yuqi Cheng; Le Yu; Yidi Xu; Hui Lu; Arthur P. Cracknell; Kasturi Kanniah; Peng Gong. Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data. International Journal of Remote Sensing 2017, 39, 432 -452.
AMA StyleYuqi Cheng, Le Yu, Yidi Xu, Hui Lu, Arthur P. Cracknell, Kasturi Kanniah, Peng Gong. Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data. International Journal of Remote Sensing. 2017; 39 (2):432-452.
Chicago/Turabian StyleYuqi Cheng; Le Yu; Yidi Xu; Hui Lu; Arthur P. Cracknell; Kasturi Kanniah; Peng Gong. 2017. "Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data." International Journal of Remote Sensing 39, no. 2: 432-452.
Satellite and ground-based observations are used to explore the composite oceanic - atmospheric link known as the El Ni\~no/La Ni\~na Southern Oscillation (ENSO) phenomenon, which is closely associated with extreme weather events (e.g. heat waves, tornadoes, floods and droughts), incidence of epidemic diseases (e.g. malaria), severe coral bleaching, etc. The ENSO temporal evolution depends on the energy exchange between the coupled ocean/atmosphere system. Its cycle has an average period of about four years, but there is considerable modulation of it from several sources and this is not yet fully understood. This paper aims to give a better insight to the global signature of ENSO evolution considering both the continuous natural interactions taking place between ocean and atmosphere, and anthropogenic effects. The results obtained could be employed to elucidate the development of more accurate advanced modelling of ocean - atmosphere interactions, thereby improving climate change projections.
Costas A. Varotsos; Arthur P. Cracknell. Modelling the coupling between ocean and atmosphere; the global signature of the El Niño/La Niña Southern Oscillation. 2017, 1 .
AMA StyleCostas A. Varotsos, Arthur P. Cracknell. Modelling the coupling between ocean and atmosphere; the global signature of the El Niño/La Niña Southern Oscillation. . 2017; ():1.
Chicago/Turabian StyleCostas A. Varotsos; Arthur P. Cracknell. 2017. "Modelling the coupling between ocean and atmosphere; the global signature of the El Niño/La Niña Southern Oscillation." , no. : 1.
Gridded climate products (GCPs) provide a potential source for representing weather in remote, poor quality or short-term observation regions. The accuracy of three long-term GCPs (Asian Precipitation—Highly-Resolved Observational Data Integration towards Evaluation of Water Resources: APHRODITE, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record: PERSIANN-CDR and National Centers for Environmental Prediction Climate Forecast System Reanalysis: NCEP-CFSR) was analyzed for the Kelantan River Basin (KRB) and Johor River Basin (JRB) in Malaysia from 1983 to 2007. Then, these GCPs were used as inputs into calibrated Soil and Water Assessment Tool (SWAT) models, to assess their capability in simulating streamflow. The results show that the APHRODITE data performed the best in precipitation estimation, followed by the PERSIANN-CDR and NCEP-CFSR datasets. The NCEP-CFSR daily maximum temperature data exhibited a better correlation than the minimum temperature data. For streamflow simulations, the APHRODITE data resulted in strong results for both basins, while the NCEP-CFSR data showed unsatisfactory performance. In contrast, the PERSIANN-CDR data showed acceptable representation of observed streamflow in the KRB, but failed to track the JRB observed streamflow. The combination of the APHRODITE precipitation and NCEP-CFSR temperature data resulted in accurate streamflow simulations. The APHRODITE and PERSIANN-CDR data often underestimated the extreme precipitation and streamflow, while the NCEP-CFSR data produced dramatic overestimations. Therefore, a direct application of NCEP-CFSR data should be avoided in this region. We recommend the use of APHRODITE precipitation and NCEP-CFSR temperature data in modeling of Malaysian water resources.
Mou Leong Tan; Philip W. Gassman; Arthur P. Cracknell. Assessment of Three Long-Term Gridded Climate Products for Hydro-Climatic Simulations in Tropical River Basins. Water 2017, 9, 229 .
AMA StyleMou Leong Tan, Philip W. Gassman, Arthur P. Cracknell. Assessment of Three Long-Term Gridded Climate Products for Hydro-Climatic Simulations in Tropical River Basins. Water. 2017; 9 (3):229.
Chicago/Turabian StyleMou Leong Tan; Philip W. Gassman; Arthur P. Cracknell. 2017. "Assessment of Three Long-Term Gridded Climate Products for Hydro-Climatic Simulations in Tropical River Basins." Water 9, no. 3: 229.
Oil palm trees are important economic crops in Malaysia and other tropical areas. The number of oil palm trees in a plantation area is important information for predicting the yield of palm oil, monitoring the growing situation of palm trees and maximizing their productivity, etc. In this paper, we propose a deep learning based framework for oil palm tree detection and counting using high-resolution remote sensing images for Malaysia. Unlike previous palm tree detection studies, the trees in our study area are more crowded and their crowns often overlap. We use a number of manually interpreted samples to train and optimize the convolutional neural network (CNN), and predict labels for all the samples in an image dataset collected through the sliding window technique. Then, we merge the predicted palm coordinates corresponding to the same palm tree into one palm coordinate and obtain the final palm tree detection results. Based on our proposed method, more than 96% of the oil palm trees in our study area can be detected correctly when compared with the manually interpreted ground truth, and this is higher than the accuracies of the other three tree detection methods used in this study.
Weijia Li; Haohuan Fu; Le Yu; Arthur Cracknell. Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images. Remote Sensing 2016, 9, 22 .
AMA StyleWeijia Li, Haohuan Fu, Le Yu, Arthur Cracknell. Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images. Remote Sensing. 2016; 9 (1):22.
Chicago/Turabian StyleWeijia Li; Haohuan Fu; Le Yu; Arthur Cracknell. 2016. "Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images." Remote Sensing 9, no. 1: 22.
Regional spatio-temporal assessment of extreme precipitation is essential to develop better climate adaptation and mitigation strategies. This study evaluated trends in precipitation extremes from 1985 to 2014 in the Kelantan River Basin (KRB), Malaysia. Forty-one climate stations that had <10% missing data, and which passed the data quality control and homogeneity tests were selected. Trends of 14 precipitation extreme indices recommended by the Expert Team on Climate Change Detection and Indices that related to duration, threshold, absolute, relative and percentile indices were analysed using the Mann–Kendall and Sen's tests. Generally, most of the regional precipitation extremes' indices had increased trends, except the consecutive dry days and consecutive wet days, which are quite consistent with global scale trends studies. On a monthly scale, the maximum 5-day precipitation amount (Rx5d) had increasing trends in January (34.91 mm decade−1) and December (13.96 mm decade−1), by field significance at 95% confidence level. For spatial context, most of the stations with significant trends were distributed in the south-western (mountainous) and northern (near-coastal) regions. In the Tropics, the KRB's extremes indices trends had a similar pattern to the West Pacific, Indian Ocean and Caribbean regions, but were different from Western Thailand, the South China Sea and the North Inter-tropical Convergence Zone, showing that trends of precipitation extreme events are different regionally. Overall, the Pacific Decadal Oscillation, Multivariate El-Niño Southern Oscillation Index, Indian Ocean Dipole and Madden-Julian Oscillation had a significant relationship with all precipitation extremes' indices, and they are contributors to climate changes in this basin.
Mou Leong Tan; Ab Latif Ibrahim; Arthur P. Cracknell; Zulkifli Yusop. Changes in precipitation extremes over the Kelantan River Basin, Malaysia. International Journal of Climatology 2016, 37, 3780 -3797.
AMA StyleMou Leong Tan, Ab Latif Ibrahim, Arthur P. Cracknell, Zulkifli Yusop. Changes in precipitation extremes over the Kelantan River Basin, Malaysia. International Journal of Climatology. 2016; 37 (10):3780-3797.
Chicago/Turabian StyleMou Leong Tan; Ab Latif Ibrahim; Arthur P. Cracknell; Zulkifli Yusop. 2016. "Changes in precipitation extremes over the Kelantan River Basin, Malaysia." International Journal of Climatology 37, no. 10: 3780-3797.
Effective monitoring is necessary to conserve mangroves from further loss in Malaysia. In this context, remote sensing is capable of providing information on mangrove status and changes over a large spatial extent and in a continuous manner. In this study we used Landsat satellite images to analyze the changes over a period of 25 years of mangrove areas in Iskandar Malaysia (IM), the fastest growing national special economic region located in southern Johor, Malaysia. We tested the use of two widely used digital classification techniques to classify mangrove areas. The Maximum Likelihood Classification (MLC) technique provided significantly higher user, producer and overall accuracies and less “salt and pepper effects” compared to the Support Vector Machine (SVM) technique. The classified satellite images using the MLC technique showed that IM lost 6740 ha of mangrove areas from 1989 to 2014. Nevertheless, a gain of 710 ha of mangroves was observed in this region, resulting in a net loss of 6030 ha or 33%. The loss of about 241 ha per year of mangroves was associated with a steady increase in urban land use (1225 ha per year) from 1989 until 2014. Action is necessary to protect the existing mangrove cover from further loss. Gazetting of the remaining mangrove sites as protected areas or forest reserves and introducing tourism activities in mangrove areas can ensure the continued survival of mangroves in IM.
Kasturi Devi Kanniah; Afsaneh Sheikhi; Arthur P. Cracknell; Hong Ching Goh; Kian Pang Tan; Chin Siong Ho; Fateen Nabilla Rasli. Satellite Images for Monitoring Mangrove Cover Changes in a Fast Growing Economic Region in Southern Peninsular Malaysia. Remote Sensing 2015, 7, 14360 -14385.
AMA StyleKasturi Devi Kanniah, Afsaneh Sheikhi, Arthur P. Cracknell, Hong Ching Goh, Kian Pang Tan, Chin Siong Ho, Fateen Nabilla Rasli. Satellite Images for Monitoring Mangrove Cover Changes in a Fast Growing Economic Region in Southern Peninsular Malaysia. Remote Sensing. 2015; 7 (11):14360-14385.
Chicago/Turabian StyleKasturi Devi Kanniah; Afsaneh Sheikhi; Arthur P. Cracknell; Hong Ching Goh; Kian Pang Tan; Chin Siong Ho; Fateen Nabilla Rasli. 2015. "Satellite Images for Monitoring Mangrove Cover Changes in a Fast Growing Economic Region in Southern Peninsular Malaysia." Remote Sensing 7, no. 11: 14360-14385.
Satellite precipitation products (SPPs) potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation. However, applications of these products are still limited due to the lack of robust quality assessment. This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH) and a ground-based precipitation product (APHRODITE). The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R2, ME, MAE, and RB) and categorical (ACC, POD, FAR, CSI, and HSS) statistical approaches. Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD. 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 4.7%, and 2.1%, respectively. By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 19.7% and 13.2%, respectively, whereas GPCP-1DD only slightly underestimated by 2.8%. All six precipitation products performed better in the northeast monsoon than in the southwest monsoon. The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia. All precipitation products underestimated the no/tiny (<1 mm/day) and extreme (≥20 mm/day) rainfall events, while they overestimated low (1–20 mm/day) rainfall events. 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (0.36). Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R2 value ranging from 0.49 to 0.88 and 0.52 to 0.86, respectively. These results on SPPs’ uncertainties and their potential controls might allow sensor and algorithm developers to deliver better products for improved rainfall estimation and thus improved water management.
Mou Leong Tan; Ab Latif Ibrahim; Zheng Duan; Arthur P Cracknell; Vincent Chaplot. Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia. Remote Sensing 2015, 7, 1504 -1528.
AMA StyleMou Leong Tan, Ab Latif Ibrahim, Zheng Duan, Arthur P Cracknell, Vincent Chaplot. Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia. Remote Sensing. 2015; 7 (2):1504-1528.
Chicago/Turabian StyleMou Leong Tan; Ab Latif Ibrahim; Zheng Duan; Arthur P Cracknell; Vincent Chaplot. 2015. "Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia." Remote Sensing 7, no. 2: 1504-1528.
Conducting quantitative studies on the carbon balance or productivity of oil palm is important for understanding the role of this ecosystem in global climate change. The MOD17 algorithm is used for processing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to generate the values of gross primary productivity (GPP) and net primary productivity for input to global carbon cycle modelling. In view of the increasing importance of data on carbon sequestration at regional and national levels, we have studied one important factor affecting the accuracy of the implementation of MOD17 at the sub-global level, namely the database of MODIS land cover (MOD12Q1) used by MOD17. By using a study area of approximately 7 km × 7 km (49 MODIS pixels) in semi-rural Johor in Peninsular Malaysia and using Google Earth 0.75 m resolution images as ground data, we found that the land-cover type for only 16 of these 49 MODIS pixels was correctly identified by MOD12Q1 using its 1 km resolution land-cover database. This leads to errors of 24% to 50% in the maximum light use efficiency, leading to corresponding errors of 24% to 50% in the GPP. We show that by using the Finer Resolution Observation and Monitoring – Global Land Cover (FROM-GLC) land-cover database developed by Gong et al., this particular error can be essentially eliminated, but at the cost of using extra computing resources.
Arthur Philip Cracknell; Kasturi Devi Kanniah; Kian Pang Tan; Lei Wang. Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees. International Journal of Remote Sensing 2015, 36, 262 -289.
AMA StyleArthur Philip Cracknell, Kasturi Devi Kanniah, Kian Pang Tan, Lei Wang. Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees. International Journal of Remote Sensing. 2015; 36 (1):262-289.
Chicago/Turabian StyleArthur Philip Cracknell; Kasturi Devi Kanniah; Kian Pang Tan; Lei Wang. 2015. "Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees." International Journal of Remote Sensing 36, no. 1: 262-289.
Kasturi Devi Kanniah; Hui Qi Lim; Dimitris G. Kaskaoutis; Arthur P. Cracknell. Investigating aerosol properties in Peninsular Malaysia via the synergy of satellite remote sensing and ground-based measurements. Atmospheric Research 2014, 138, 223 -239.
AMA StyleKasturi Devi Kanniah, Hui Qi Lim, Dimitris G. Kaskaoutis, Arthur P. Cracknell. Investigating aerosol properties in Peninsular Malaysia via the synergy of satellite remote sensing and ground-based measurements. Atmospheric Research. 2014; 138 ():223-239.
Chicago/Turabian StyleKasturi Devi Kanniah; Hui Qi Lim; Dimitris G. Kaskaoutis; Arthur P. Cracknell. 2014. "Investigating aerosol properties in Peninsular Malaysia via the synergy of satellite remote sensing and ground-based measurements." Atmospheric Research 138, no. : 223-239.
Conducting quantitative studies on the carbon balance or productivity of oil palm is important in understanding the role of this ecosystem in global climate change. In this study, we evaluated the accuracy of MODIS (Moderate Resolution Imaging Spectroradiometer) annual gross primary productivity (GPP) (the product termed MOD-17) and its upstream products, especially the MODIS land cover product (the product termed MOD-12). We used high-resolution Google Earth images to classify the land cover classes and their percentage cover within each 1 km spatial resolution MODIS pixel. We used field-based annual GPP for 2006 to estimate GPP for each pixel based on percentage cover. Both land cover and GPP were then compared to MODIS land cover and GPP products. The results show that for pure pixels that are 100% covered by mature oil palm trees, the RMSE (root mean square error) between MODIS and field-based annual GPP is 18%, and that this is increased to 27% for pixels containing mostly oil palm. Overall, for an area of about 42 km2 the RMSE is 26%. We conclude that land cover classification (at 1 km resolution) is one of the main factors for the discrepancy between MODIS and field-based GPP. We also conclude that the accuracy of the MODIS GPP product could be improved significantly by using higher-resolution land cover maps.
Arthur Philip Cracknell; Kasturi Devi Kanniah; Kian Pang Tan; Lei Wang. Evaluation of MODIS gross primary productivity and land cover products for the humid tropics using oil palm trees in Peninsular Malaysia and Google Earth imagery. International Journal of Remote Sensing 2013, 34, 7400 -7423.
AMA StyleArthur Philip Cracknell, Kasturi Devi Kanniah, Kian Pang Tan, Lei Wang. Evaluation of MODIS gross primary productivity and land cover products for the humid tropics using oil palm trees in Peninsular Malaysia and Google Earth imagery. International Journal of Remote Sensing. 2013; 34 (20):7400-7423.
Chicago/Turabian StyleArthur Philip Cracknell; Kasturi Devi Kanniah; Kian Pang Tan; Lei Wang. 2013. "Evaluation of MODIS gross primary productivity and land cover products for the humid tropics using oil palm trees in Peninsular Malaysia and Google Earth imagery." International Journal of Remote Sensing 34, no. 20: 7400-7423.
The largest ozone losses ever recorded over the Arctic have been measured by an international network of over 30 ground-based stations and satellite-borne sensors during January–March 2011. We study whether this was an exceptional event or whether it is part of the evolution of an ozone hole in the Arctic. The main finding is that the 2010–2011 winter's record-breaking ozone loss was instigated by the extremely low stratospheric temperatures that are linked to climate change, that is, the coldest winters at the Arctic region have been getting colder leading to larger ozone losses there, which are progressively reaching the levels of the Antarctic ozone hole.
Costas A. Varotsos; Arthur P. Cracknell; Chris Tzanis. The exceptional ozone depletion over the Arctic in January–March 2011. Remote Sensing Letters 2012, 3, 343 -352.
AMA StyleCostas A. Varotsos, Arthur P. Cracknell, Chris Tzanis. The exceptional ozone depletion over the Arctic in January–March 2011. Remote Sensing Letters. 2012; 3 (4):343-352.
Chicago/Turabian StyleCostas A. Varotsos; Arthur P. Cracknell; Chris Tzanis. 2012. "The exceptional ozone depletion over the Arctic in January–March 2011." Remote Sensing Letters 3, no. 4: 343-352.
Numerous interactive processes are responsible for climate formation and change (Brasseur, 1997; Houghton et al., 1996; Kondratyev, 1989, 1998b; Zillman, 1997). It is therefore difficult to single out the impact of an individual cause of climate change. Nevertheless, many attempts have been undertaken to assess climatic the impacts of various processes and phenomena, including processes in the stratosphere with special emphasis on the role of stratospheric ozone variability (Kondratyev, 1998b, 1999b). In this context, climate change affects the variability of the ozone layer through changes in atmospheric circulation, chemical composition, and temperature. However, changes to the ozone layer affect climate through radiative processes (e.g., changes in temperature gradients) which consequently modify atmospheric dynamics. Therefore, there is a strong link between climate change and ozone layer variability. The problem becomes more complex when assuming that the processes involved in this coupling often exhibit non-linear behavior (Fleming et al., 2009; WMO, 2007).
Arthur P. Cracknell; Costas A. Varotsos. Atmospheric ozone and climate. Remote Sensing and Atmospheric Ozone 2012, 485 -557.
AMA StyleArthur P. Cracknell, Costas A. Varotsos. Atmospheric ozone and climate. Remote Sensing and Atmospheric Ozone. 2012; ():485-557.
Chicago/Turabian StyleArthur P. Cracknell; Costas A. Varotsos. 2012. "Atmospheric ozone and climate." Remote Sensing and Atmospheric Ozone , no. : 485-557.
Following the agreement of the Montreal Protocol in 1987 a great deal of research work has been done on atmospheric ozone and a considerable amount of that research was directed towards monitoring the effectiveness of the Montreal Protocol. As we said at the end of Chapter 5, there are various stages involved: (a) monitoring the production and use of ozone-depleting substances; (b) monitoring the concentration of these substances in the atmosphere, both in the troposphere and in the stratosphere; (c) monitoring the trends in ozone concentration in the troposphere; and (d) monitoring the ozone concentration in the stratosphere both in equatorial areas and mid-latitudes and also in the polar regions. The main datasets of TOC and ozone profiles are listed and described briefly in Appendix 3A of WMO (2007). Apart from monitoring the success of the Montreal Protocol so far, the data collected are also important in contributing to models that can be used to make predictions about the rate of recovery of the ozone layer in the future. This work has been reported, in the usual way, in scientific journals and at the Quadrennial Ozone Symposia.
Professor Arthur P. Cracknell; Costas Varotsos. The study of atmospheric ozone since 1987. Remote Sensing and Atmospheric Ozone 2012, 379 -483.
AMA StyleProfessor Arthur P. Cracknell, Costas Varotsos. The study of atmospheric ozone since 1987. Remote Sensing and Atmospheric Ozone. 2012; ():379-483.
Chicago/Turabian StyleProfessor Arthur P. Cracknell; Costas Varotsos. 2012. "The study of atmospheric ozone since 1987." Remote Sensing and Atmospheric Ozone , no. : 379-483.
In this chapter we discuss the effects of human activities on atmospheric ozone and, in particular, ozone depletion. We divide ozone depletion into two distinct parts; one is the steady depletion that occurs to a lesser or greater extent over the whole of the globe and is an underlying trend beneath all the various large daily, seasonal, and regional fluctuations; and the other is the dramatic reduction of stratospheric ozone in the Antarctic spring, usually referred to as the (Antarctic) ozone hole. A similar, but smaller effect, to the Antarctic ozone hole has also been observed more recently in the Arctic. We shall describe the discoveries and events that led to the adoption of the Montreal Protocol which was drawn up in 1987 and which came into effect in 1989. However, when the Montreal Protocol was drawn up the relevant scientific evidence was far from complete. Very readable accounts of the steps involved in this process are given in the book by Sharon Roan (1989), albeit in a slightly journalistic format and with a U.S. bias, and in the book by Richard Benedick (1991) which concentrates on the diplomatic aspects of the negotiations leading to the Montreal Protocol, rather than on the science. The contribution of remote sensing in the scientific work leading up to the establishment of the Montreal Protocol and the monitoring of its success is discussed by Cracknell and Varotsos (2009), part of a special issue of the International Journal of Remote Sensing (Volume 30, Nos. 15–16, August 2009); this chapter draws substantially on that article.
Arthur P. Cracknell; Costas A. Varotsos. The Montreal Protocol. Remote Sensing and Atmospheric Ozone 2012, 339 -378.
AMA StyleArthur P. Cracknell, Costas A. Varotsos. The Montreal Protocol. Remote Sensing and Atmospheric Ozone. 2012; ():339-378.
Chicago/Turabian StyleArthur P. Cracknell; Costas A. Varotsos. 2012. "The Montreal Protocol." Remote Sensing and Atmospheric Ozone , no. : 339-378.
As mentioned in Chapter 1, the most characteristic feature of global total ozone dynamics is the presence of strong spatiotemporal variability, which has been documented and analyzed in detail in recent years. The development of various kinds of ozone observations constitutes a great step forward. However, a number of problems still remain unresolved. This is why there is a need for long-term continuity of ozone measurements (Kaye and Readings, 1998).
Arthur P. Cracknell; Costas A. Varotsos. The dynamics of atmospheric ozone. Remote Sensing and Atmospheric Ozone 2012, 255 -337.
AMA StyleArthur P. Cracknell, Costas A. Varotsos. The dynamics of atmospheric ozone. Remote Sensing and Atmospheric Ozone. 2012; ():255-337.
Chicago/Turabian StyleArthur P. Cracknell; Costas A. Varotsos. 2012. "The dynamics of atmospheric ozone." Remote Sensing and Atmospheric Ozone , no. : 255-337.