Yield Forecasting of Spring Maize Using Remote Sensing and Crop Modeling in Faisalabad-Punjab Pakistan

Real time, accurate and reliable estimation of maize yield is valuable to policy makers in decision making. The current study was planned for yield estimation of spring maize using remote sensing and crop modeling. In crop modeling, the CERES-Maize model was calibrated and evaluated with the field experiment data and after calibration and evaluation, this model was used to forecast maize yield. A Field survey of 64 farm was also conducted in Faisalabad to collect data on initial field conditions and crop management data. These data were used to forecast maize yield using crop model at farmers’ field. While in remote sensing, peak season Landsat 8 images were classified for landcover classification using machine learning algorithm. After classification, time series normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surveyed 64 farms were calculated. Principle component analysis were run to correlate the indicators with maize yield. The selected LSTs and NDVIs were used to develop yield forecasting equations using least absolute shrinkage and selection operator (LASSO) regression. Calibrated and evaluated results of CERES-Maize showed the mean absolute % error (MAPE) of 0.35–6.71% for all recorded variables. In remote sensing all machine learning algorithms showed the accuracy greater the 90%, however support vector machine (SVM-radial basis) showed the higher accuracy of 97%, that was used for classification of maize area. The accuracy of area estimated through SVM-radial basis was 91%, when validated with crop reporting service. Yield forecasting results of crop model were precise with RMSE of 255 kg ha^?1, while remote sensing showed the RMSE of 397 kg ha^?1. Overall strength of relationship between estimated and actual grain yields were good with R² of 0.94 in both techniques. For regional yield forecasting remote sensing could be used due greater advantages of less input dataset and if focus is to assess specific stress, and interaction of plant genetics to soil and environmental conditions than crop model is very useful tool.     

Dimensionality Reduction and Classification of Hyperspectral Images Using Object-Based Image Analysis

Object-based image analysis (OBIA) has attained great importance for the delineation of landscape features, particularly with the accessibility to satellite images with high spatial resolution acquired by recent sensors. Statistical parametric classifiers have become ineffective mainly due to their assumption of normal distribution, vast increase in the dimensions of the data and availability of limited ground sample data. Despite pixel-based approaches, OBIA takes semantic information of extracted image objects into consideration, and thus provides more comprehensive image analysis. In this study, Indian Pines hyperspectral data set, which was recorded by the AVIRIS hyperspectral sensor, was used to analyse the effects of high dimensional data with limited ground reference data. To avoid the dimensionality curse, principal component analysis (PCA) and feature selection based on Jeffries–Matusita (JM) distance were utilized. First 19 principal components representing 98.5% of the image were selected using the PCA technique whilst 30 spectral bands of the image were determined using JM distance. Nearest neighbour (NN) and random forest (RF) classifiers were employed to test the performances of pixel- and object-based classification using conventional accuracy metrics. It was found that object-based approach outperformed the traditional pixel-based approach for all cases (up to 18% improvement). Also, the RF classifier produced significantly more accurate results (up to 10%) than the NN classifier.     

Comparative analysis of bacterial contamination in tap and groundwater: A case study on water quality of Quetta City,an arid zone in Pakistan

Water is an essential element on earth, which provides human a variety of services in domestic use, agriculture, or industries. However, some serious health risks of drinking water are associated with microbial contamination, particularly with fecal matter. Therefore, microbial quality assessment is considered to be a necessary component of water quality assessment. This study investigates microbial contamination of water distributary system around the city by comparing groundwater (GW) and tap water (TW) quality in Quetta city. 31 GW samples and 31 TW samples were collected in the study area during the months of September, October, and November. Fecal coliform test was carried out in laboratory and their average total coliform contamination was computed. Results showed that the TW sample were all contaminated by coliform except for Chiltan town, hence are not considered suitable for drinking without any treatment according to WHO drinking water quality standards. The average coliform concentrations were 12 in Quetta main city, 11.6 in Jinnah town, 5.3 in Satallite town, 10 in Shahbaz town and 5 in Brewery town (0/100 mL CFU) and the TW samples from the three towns were even more contaminated with E.coli. Whereas among the GW, average microbial concentrations were 1.8 in Quetta main city, 2 in Satallite town, 1.4 in Shahbaz town, and 0.4 in Chiltan town (0/100 mL CFU), respectively, which shows that the contamination is occurring within the water distributary pipeline system when the water flows through the pipelines. Moreover, this research will be valuable for researchers and administrative authorities to conduct elaborative studies, and develop new policies to prevent further deterioration of drinking water in the water distribution system by pathogenic microorganisms and ensure safe drinking water to the public of Quetta city.     

A comparative analysis of pre- and post-industrial spatiotemporal drought trends and patterns of Tibet Plateau using Sen slope estimator and steady-state probabilities of Markov Chain

Natural Hazards - The increase of frequency and severity of extreme weather events due to climate change gives evidence of severe challenges faced by infrastructure systems. Among them, the...     

Remote sensing and geophysical survey applications for delineating near-surface palaeochannels and shallow aquifer in the United Arab Emirates

This study integrates remote sensing data and geoelectrical dipole–dipole resistivity to delineate near-surface palaeochannels and shallow aquifer in the northern part of Abu Dhabi Emirate, United Arab Emirates. The shuttle imaging radar images and shuttle radar topographic mission DEM were used to delineate near-surface palaeochannels visually based on the contrast between bright and dark tone and automatically using the eight-direction flow model. The delineated palaeochannels were validated by comparing the textural features evident from advanced land observing satellite-phased array type L-band synthetic aperture radar images and determining whether these patterns were different. Field observation and geoelectrical dipole–dipole resistivity method was used to define the depth of palaeochannels and lithology of the shallow aquifer. The remote sensing and geophysical investigations in the UAE, including the study area, indicate the presence of buried palaeochannels with south-west and north-west flow directions from Oman Mountain. The study area can be of economic importance to the local population.     

Hydrogeological aspects of groundwater drainage of the urban areas in Kuwait City

Residential areas in Kuwait City have witnessed a dramatic rise in subsurface water tables over the last three decades. This water rise phenomenon is attributed mainly to over irrigation practices of private gardens along with leakage from domestic and sewage networks. This paper presents a comprehensive study for urban drainage in two selected areas representing the two hydrogeological settings encountered in Kuwait City. In the first area, a vertical drainage scheme was applied successfully over an area of 1 km². The system has been under continuous operation and monitoring for more than 4 years without problems, providing a permanent solution for the water rise problem in this area. The hydrogeological system has approached steady state conditions and the water levels have dropped to about 3·5 m below the ground surface. In the second area a dual drainage scheme, composing of horizontal and vertical elements, is proposed. Horizontal elements are suggested in the areas where the deep groundwater contains hazardous gases that may pose environmental problems. The proposed drainage scheme in the second area has not yet been implemented. Field tests were conducted to assess the aquifer parameters in both areas and a numerical model has been developed to predict the long‐term response of the hydrogeological system in the two areas under consideration. Copyright © 2001 John Wiley & Sons, Ltd.     

New insights into the origin of perylene in geological samples

The origin of the polycyclic aromatic hydrocarbon (PAH) perylene in sediments and petroleum has been a matter of continued debate. Reported to occur in Phanerozoic organic matter (OM), fossil crinoids and tropical termite mounds, its mechanism of formation remains unclear. While a combustion source can be excluded, structural similarities to perylene quinone-like components present in e.g. fungi, plants, crinoids and insects, potentially suggest a product-precursor relationship. Here, we report perylene concentrations, ¹³C/¹²C, and D/H ratios from a Holocene sediment profile from the Qingpu trench, Yangtze Delta region, China. Perylene concentrations differ from those of pyrogenic PAHs, and rise to prominence in a stratigraphic interval that was dominated by woody vegetation as determined by palynology including fungal spores. In this zone, perylene concentrations exhibit an inverse relationship to the lignin marker guaiacol, D/H ratios between −284‰ and −317‰, similar to the methoxy groups in lignin, as well as co-variation with spores from wood-degrading fungi. ¹³C/¹²C of perylene differs from that of land plant wax alkanes and falls in the fractionation range expected for saprophytic fungi that utilise lignin, which is isotopically lighter than cellulose and whole wood. During progressive lignin degradation, the relative carbon isotopic ratio of the perylene decreases. We therefore hypothesise a relationship of perylene to the activity of wood-degrading fungi. To support our hypothesis, we analysed a wide range of Phanerozoic sediments and oils, and found perylene to generally be present in subordinate amounts before the evolutionary rise of vascular plants, and to be generally absent from marine-sourced oils, few exceptions being attributed perhaps to a contribution of marine and/or terrestrial-derived fungi, anoxia (especially under marine conditions) and/or contamination of core material by fungi. A series of low-molecular-weight aromatic quinones bearing the perylene-backbone were detected in Devonian and Cretaceous sediments, potentially representing precursor components to perylene.