bluuebunny/crossref_metadata_2025 huggingface dataset:
Administrative penalties: Impact and alternatives
Authors: Aproskie Jason , Goga Sha’ista
Published: July 2019

Administrative penalties are imposed in South Africa for a specified set of prohibited practices. These are typically the most egregious anti-competitive acts, and therefore the main purpose of administrative penalties is to act as a deterrent, both to the offending firm and to other firms that may consider engaging in similar behaviour. With a spate of high-profile cases resulting in fines, there has been much discussion over fines and their ultimate impact on businesses and consumers. We discuss three arguments that have been raised. Firstly, we consider whether companies simply pass the cost of their fine through to consumers in the form of higher prices. Secondly, we look at the validity of the complaint that high fines could lead to poorer competitive outcomes due to firm exit. Thirdly, we assess suggested alternative mechanisms for disbursing the fine such as paying the fine in the form of lower prices.
Guest Editorial
Authors: Mncube Liberty , Ngepah Nicholas , Roberts Simon
Published: July 2019

No abstract available.
Retirement saving behaviour of young adults in the financial services sector
Authors: Nkoutchou Hugue , Eiselen Riëtte
Published: July 2019

In a society characterised by high levels of consumption that result in high levels of debt, saving sufficiently for retirement represents a major challenge, especially in light of the steadily increasing cost of living and the cost associated with healthcare. Questions regarding the extent to which retirees have accumulated sufficient money during their working years to support them are being raised. The purpose of this exploratory study was to investigate the behaviour of young adults in relation to retirement provision. A web-based survey was conducted in a single large organisation. The findings revealed that young adults tend to have a wide range of debt. Although they are aware that the funds accumulated in their retirement funds would not provide sufficient cover during retirement, they tend not to save over and above the minimum contribution to their employing organisation’s retirement fund. Organisations should encourage young adults to reduce their debt and voluntarily save for retirement.
Improved investment performance using the portfolio diversification index
Authors: Van Dyk Francois , Van Vuuren Gary , Styger Paul
Published: July 2019

The residual variance method is the traditional method for measuring portfolio diversification relative to a market index. Problems arise, however, when the market index itself is not appropriately diversified. A diversification measurement (Portfolio Diversification Index), free from market index influences, has been recently introduced. This article explores whether this index is a robust and ‘good’ diversification measure compared with the residual variance method. South African unit trusts are diversification-ranked using the two measures and the results compared to the ranking results of several risk performance measures. Measuring relative concentration levels allows concentration risk to be effectively managed, thereby filling a gap in the Basel accords (which omit concentration risk).
The relationship between the forward and realised spot exchange rate in South Africa
Authors: Van Heerden Chris , Heymans André
Published: July 2019

It is well known that the forward exchange rate and the realised future spot exchange rate differ. This phenomenon is better known as the exchange rate puzzle. Two approaches were followed to ascertain whether this difference is due to the weak explanatory ability of current economic fundamentals or whether the use of an ineffective econometric approach to model exchange rate theories is to blame. The first approach makes use of stationary economic time series data to model the ZAR/USD realised future spot exchange rate, while the second uses non-stationary level economic data to model the ZAR/USD realised future spot exchange rate. While the first approach reported weak results, the second approach illustrated that economic fundamentals are able to explain the ZAR/USD realised future spot exchange rate. These results also confirm that the exchange rate puzzle is a pseudoproblem.
The price puzzle and the role of South African monetary policy in Botswana and Namibia
Authors: Burger Philippe , Fillipus Helvi , Molalapata Innocent
Published: July 2019

Using SVAR analysis, this paper finds what Sims calls a ‘price puzzle’, i.e. a case where CPI increases after a positive interest rate shock. The SVAR analysis controls for various monetary transmission mechanisms, including one based on the South African dominance hypothesis that links South African monetary policy to inflation in Botswana and Namibia. The paper follows Castelnuovo and Surico and interprets the price puzzle as a symptom of an indeterminate monetary policy. Subsequently the paper explores the finding of indeterminate monetary policy further by using an unstructured VAR to estimate the monetary reaction functions of Botswana and Namibia. These results also point to the presence of an indeterminate monetary policy. Lastly, both the SVAR and the unstructured VAR estimated for the monetary reaction function indicate the importance of the exchange rate, and not the interest rate, as a determinant of inflation in both Botswana and Namibia
The effects of the National Credit Act and the global financial crisis on domestic credit extension: Empirical evidence from South Africa
Authors: Chipeta Chimwemwe , Mbululu Douglas
Published: July 2019

This paper examines the impact of the new National Credit Act (NCA) No. 34 of 2005 and the global financial crisis on credit extension provided by all monetary institutions in South Africa. The econometric approach is estimated by way of ordinary least squares while controlling for several macroeconomic factors. The findings indicate that there was a general increase in the consumer credit provision in the period subsequent to the full implementation of the Act. The promulgation of the Act increases credit card, bank overdrafts, other conventional loans and total credit to the private sector categories. The implementation of the Act fails to reverse this trend but exerts a negative influence on lease finance and the global financial crisis has significant negative effects on most of the credit provision categories. The paper seeks to investigate an under-researched area on the interrelatedness of credit provider regulation, financial crises and credit extension.
A cross-cultural comparison of organisational commitment amongst vehicle sales staff
Authors: Magano C. F. , Thomas A. , De Bruin G. P.
Published: July 2019

The automotive industry is regarded as being critical to the economic growth of South Africa (Horn, 2007). As the achievement of organisational goals occurs largely through the performance of committed human resources (Nijhof, De Jong & Beukhof, 1998), the purpose of the present study was to gain a deeper understanding of the differences in organisational commitment amongst different language groups (language being a proxy of culture) of vehicle sales staff at a large South African motor retailer.The unit of analysis for the study was individual employees (n=314) and the data were collected through the administration of the TCM survey questionnaire developed by Allen and Meyer (1990) to measure affective, normative and continuance commitment. The majority of respondents (36,90%) were African language speakers, 32,30% were English language speakers and 3,60% were Afrikaans language speakers.Results indicate that African language respondents scored significantly lower on normative commitment than did either the Afrikaans or English respondents. No significant differences in normative commitment were observed between the Afrikaans and English respondents.Given the strategic importance of the automotive industry to the South African economy, this finding could alert managers to the necessity of understanding the reasons for the lower normative commitment of the African language group (compared to the Afrikaans and English speakers) and, accordingly, to devise ways of increasing normative commitment with this group.
The impact of culture-related factors on good governance in Greek family businesses in South Africa
Authors: Adendorff C. , Boshoff C.
Published: July 2019

The size of the family business component of the South African economy suggests that it is the predominant way of doing business in South Africa. A large proportion of these family businesses are Greek-owned. More importantly it is estimated that approximately 95% of all Greek businesses in South Africa can be classified as family businesses. The sustainability of Greek family businesses requires that they maintain good governance practices that are both economically and environmentally acceptable to all stakeholders. It also requires that the next generation of Greek entrepreneurs effectively balance good governance of their businesses with their family commitments.The primary objective of this study was to identify and explore the internal, culturally-related factors that influence good governance to ensure the survival, growth and sustainability of Greek family businesses in South Africa. A theoretical model of good governance factors was proposed and tested using Structural Equation Modelling.The study found that perceived good governance in a South African Greek family business context needs to be managed in terms of three factors, namely risk control, the internal regulatory environment and the protection of the stakeholders' interest. The study found that needs alignment, cultural needs alignment, vision and ethnic entrepreneurial growth all impact directly or indirectly on perceived good governance in South African Greek family businesses.
Servant leadership, trust and implications for the “Base-of-the-Pyramid” segment in South Africa
Authors: Chatbury A. , Beaty D. , Kriek H. S.
Published: July 2019

This paper examines the relationship between servant leadership and interpersonal trust in South Africa. The results of this empirical investigation, conducted among low level employees and their managers, revealed a statistically significant relationship between servant leadership and interpersonal trust using Spearman’s r-value of 0.664 (p< 0.05). These findings will be discussed in terms of their implications for establishing what kind of leadership model might work at the Base of the Pyramid (BOP) and how this approach might build trust among stakeholders in the informal economy in South Africa.
The influence of passenger satisfaction on relationship formation in the South African domestic airline industry
Authors: De Meyer C. F. , Mostert P. G.
Published: July 2019

Customers are increasingly becoming aware of alternative offerings in the market place, and are thus more demanding in terms of their expectations pertaining to service delivery. As airlines in particular are vulnerable to competitors’ offerings, they should offer passengers high levels of service and ensure that passengers are satisfied with their service offering in an effort to build long-term relationships. Building long-term relationships is important due to the financial and social benefits it holds to both the business and its customer. This study investigates whether passenger satisfaction influences whether or not passengers have formed a long-term relationship with the airline they fly with most often. Data was collected from South African domestic passengers departing from OR Tambo International Airport in Johannesburg by means of a convenience sample. Main findings from the study indicate that the majority of dissatisfied respondents have not formed a long-term relationship with the domestic airline, while satisfied respondents are more inclined to form a long-term relationship.
Gender differences in low-income non-users’ attitude towards Wireless Internet Gateway cellphone banking
Authors: Nel J. , Raleting T.
Published: July 2019

Globally the adoption of cellphone banking is proceeding more slowly than anticipated. To address this managerial dilemma, the aim of this paper is to investigate the moderating effect of gender on low-income non-users’ attitude formation towards Wireless Internet Gateway (WIG) cellphone banking. An understanding of whether and to what extent gender moderates the formation of attitude can assist marketing managers in developing more effective marketing strategies to enhance adoption. The originality of the research is that it investigates gender differences in WIG-cellphone banking adoption behaviour of low-income non-users of this type of cellphone banking application. Literature on technology adoption, self-efficacy, facilitating conditions, risk and cost is reviewed to provide theoretical support for inclusion of the constructs in the conceptual model and to develop gender difference hypotheses. To assess the moderating effect of gender, a multi-group analysis with SmartPLS is conducted. The results of the multi-group analysis indicate that for males the influences of Usefulness on Attitude, Facilitating conditions on Self-efficacy and Ease of use, and Cost on Usefulness are stronger than for females and significantly different. On the other hand, the influences of Ease of use on Attitude, Self-efficacy on Ease of use and Facilitating conditions on Perceived usefulness are stronger for females than males and significantly different. These results may also be useful to marketing managers of other text-based mobile self-services. Furthermore, more confirmation for the determinants of Usefulness and Ease of use in a private usage and mobile service context is presented.
Strategies for sustainable growth in JSE-listed companies
Authors: Eitzen C. , Sartorius K.
Published: July 2019

Achieving high growth that is sustainable is an elusive goal for all but a few great companies. Despite the relative importance of this topic, limited research has been performed to explain this phenomenon, especially in a South African context. This paper adopts an exploratory approach to investigate some of the variables that influence company growth, as well as their choice of strategy. A mixed method incorporating descriptive statistics, regression analysis and qualitative evaluation, was used to test the research questions. A sample of 202 JSE companies indicated 28% were high growth entities, 39% medium growth and 33% achieved growth of less than 10%. A further survey of 30 Chief Executive Officers (CEO) indicated that they believed the top five growth drivers were acquisitions, managerial talent, operational efficiency, an entrepreneurial flair (low growth companies excluded) and the development of networks and partnerships. The respondents, however, ranked the number and importance of these growth drivers very differently with high growth companies citing a broader range of growth drivers than the other respondents. Quite surprisingly, the respondents appear to have underestimated the importance of industry and economy effects. Furthermore, high growth companies appeared to develop a broader spectrum of strategies that were more likely to be linked to their choice of growth driver. Interestingly, high growth companies were the only respondents to develop formal partnership and incentive strategies. In conclusion, the results re-enforce the impression that successful organizations develop a multiplicity of strategies that are always underpinned by operational efficiency.
The repurchase by a holding company of treasury shares held by subsidiaries: A South African perspective
Authors: Wesson N. , Hamman W. D.
Published: July 2019

This study aims to establish whether the repurchasing of treasury shares by a holding company is a regular occurrence for companies listed on the Johannesburg Stock Exchange (JSE); whether these repurchasing companies have complied with the relevant legal and reporting requirements; and what their stated motivations were for these repurchases.In a sample of 251 companies listed on the JSE from 1999 till their 2009 financial year-end, 120 (47,8%) companies executed share repurchases. Thirty-six (30%) of the 120 companies repurchased treasury shares from their subsidiaries in 55 different transactions, representing 22% of the total number of shares repurchased.Companies which repurchase treasury shares do not always comply with the legal requirements (such as obligatory Security News Agency (SENS) announcements and circulars); and the accounting requirements of International Financial Reporting Standards (IFRS) (relevant to the disclosure of the reconciliation of the number of shares in issue) are applied in an inconsistent manner in annual reports. The most common reason for the repurchase of treasury shares was that the 10% limit (on treasury shares held by subsidiaries) had nearly been reached. Various business purposes were also given. Income tax implications did not seem to be a conclusive motivation for repurchasing treasury shares.The repurchase of treasury shares by the holding company is not allowed in most other countries, like the UK, and presents unique challenges to the South African share repurchase environment. More stringent application of the JSE Listing Requirements, as well as better guidance on the IFRS disclosure requirement on the reconciliation of the number of shares in issue, is needed in South Africa. This will enable stakeholders to make better-informed decisions and will also assist research on share repurchases.This material is based upon work supported financially by the National Research Foundation. However, any opinions, findings, conclusions and recommendations expressed in this article are those of the authors alone, and the NRF does not accept any liability in regard thereto.
On the Combinatorics of Gentle Algebras
Authors: Brüstle Thomas , Douville Guillaume , Mousavand Kaveh , Thomas Hugh , Yıldırım Emine
Published: July 2019

For $A$ a gentle algebra, and $X$ and $Y$ string modules, we construct a combinatorial basis for $\operatorname{Hom}(X,\unicode[STIX]{x1D70F}Y)$. We use this to describe support $\unicode[STIX]{x1D70F}$-tilting modules for $A$. We give a combinatorial realization of maps in both directions realizing the bijection between support $\unicode[STIX]{x1D70F}$-tilting modules and functorially finite torsion classes. We give an explicit basis of $\operatorname{Ext}^{1}(Y,X)$ as short exact sequences. We analyze several constructions given in a more restricted, combinatorial setting by McConville, showing that many but not all of them can be extended to general gentle algebras.
Sensitivity of GPS tropospheric estimates to mesoscale convective systems in West Africa
Authors: Nahmani Samuel , Bock Olivier , Guichard Françoise
Published: July 2019

Abstract. This study analyzes the characteristics of GPS
tropospheric estimates (zenith wet delays – ZWDs, gradients, and post-fit phase
residuals) during the passage of mesoscale convective systems (MCSs) and
evaluates their sensitivity to the research-level GPS data processing
strategy implemented. Here, we focus on MCS events observed during the
monsoon season of West Africa. This region is particularly well suited for the study of these events due to the high frequency of MCS occurrences in the contrasting climatic
environments between the Guinean coast and the Sahel. This contrast is well
sampled with data generated by six African Monsoon Multidisciplinary Analysis (AMMA) GPS stations. Tropospheric estimates for a
3-year period (2006–2008), processed with both the GAMIT and GIPSY-OASIS
software packages, were analyzed and intercompared. First, the case of a
MCS that passed over Niamey, Niger, on 11 August 2006 demonstrates a
strong impact of the MCS on GPS estimates and post-fit residuals when the
GPS signals propagate through the convective cells as detected on reflectivity maps from the MIT C-band Doppler radar. The estimates are also capable of
detecting changes in the structure and dynamics of the MCS. However, the sensitivity
is different depending on the tropospheric modeling approach adopted
in the software. With GIPSY-OASIS, the high temporal sampling (5 min) of
ZWDs and gradients is well suited for detecting the
small-scale, short-lived, convective cells, while the post-fit residuals
remain quite small. With GAMIT, the lower temporal sampling of the estimated
parameters (hourly for ZWDs and daily for gradients) is not
sufficient to capture the rapid delay variations associated with the passage
of the MCS, but the post-fit phase residuals clearly reflect the presence of
a strong refractivity anomaly. The results are generalized with a composite
analysis of 414 MCS events observed over the 3-year period at the six GPS
stations with the GIPSY-OASIS estimates. A systematic peak is found in the
ZWDs coincident with the cold pool crossing time associated with the MCSs. The tropospheric gradients reflect the path of the MCS
propagation (generally from east to west). This study concludes that ZWDs, gradients, and post-fit phase residuals provide relevant and
complementary information on MCSs passing over or in the vicinity of a GPS
station.
EARTH OBSERVATIONS FOR AGRICULTURAL MONITORING: EDITORIAL
Authors: Ray S. S. , Navalgund R. , Justice C.
Published: July 2019

Abstract. Earth observation data obtained from spaceborne, aerial and other platforms at different spectral regions and time intervals and spatial detail has immensely helped in inventorying, monitoring and condition assessment of agricultural resources. EO data available from a host of international space missions in both optical and microwave regions are being operationally used in many counties to make preharvest production forecasts and in assessing the impact of drought. Thus, EO techniques are proving to be important tools contributing to improve food security and meet the needs of UN Sustainable Development Goals. However, there are many scientific challenges in the application of EO data in the assessment of minor, short duration crops grown in fragmented land holdings, non-paddy crops grown during kharif season (cloud covered periods), in more precise productivity estimation, in estimating the impact of extreme weather on production, in early detection of disease affected crops etc. Newer techniques of data fusion, use of hyperspectral data and machine learning tools are advancing the use of EO data. In this context, the Group on Earth Observations, an international forum has initiated a programme on Global Agricultural Monitoring (GEOGLAM), in which many coordinated efforts are successfully being undertaken for the use of EO data. In order to review the progress made, challenges faced and to advance this initiative, a joint international workshop was organised by the International Society for Photogrammetery and Remote Sensing (ISPRS) Working Group III/10 (Agriculture and Natural Ecosystems Modelling and Monitoring), the Indian Society of Remote Sensing and GEOGLAM at the Indian Agricultural Research Institute in New Delhi, India during February 18–20, 2019. More than one hundred research articles were received for oral and poster presentations at this workshop. The manuscripts deal with the application of EO data for production forecasts of different crops grown under irrigated and dryland conditions, the impact of likely climate change on crop yield, extreme weather and agriculture, use of EO data in crop intensification, retrieval of biophysical parameters from EO data for further use in process models, use of microwave SAR and scatterometer data in estimating crop parameters, detection of wheat blast, water use efficiency, and so on. There were several presentations dealing with development of advanced techniques for data analysis etc. The current volume is a collection of all the manuscripts presented at the workshop. All the papers have gone through a preliminary review and editing. We do hope, this volume will provide material for all those professionals and decision/policy makers interested in the applications of EO data for agricultural monitoring.
SOYBEAN CROPLAND MAPPING USING MULTI-TEMPORAL SENTINEL-1 DATA
Authors: Kumari M. , Murthy C. S. , Pandey V. , Bairagi G. D.
Published: July 2019

Abstract. Soybean, a high value oilseed crop, is predominantly grown in the rainfed agro-ecosystem of central and peninsular India. Accurate and up-to-date assessment of the spatial distribution of soybean cultivated area is a key information requirement of all stakeholders including policy makers, soybean farmers and consumers. A methodology for timely assessment with high precision of soybean crop using satellite data is yet not operational in India. In this scenario, synthetic aperture radar (SAR) has been shown to be a reliable form of gathering crop information, especially during monsoon season. In this work, repeat coverage from the C-band Sentinel-1 satellite over Ujjain district, Madhya Pradesh is used for in-season soybean crop mapping along with other agricultural land-cover types. The data were processed through four steps: (a) data preprocessing, (b) constructing smooth time series backscatter data, (c) soybean crop classification using knowledge-based decision rule classifier and support vector machines (SVM) and (d) accuracy assessment. The results indicated that the smooth VH backscatter profiles reflected the temporal characteristics of soybean crop growing in the study region. Phenological characteristics were also derived from the smoothed S-1 VH backscatter time series to segregate early and late sown soybean. This information was used as an input to a decision-rule classifier and SVM in order to classify the input data into soybean and other crops. An overall accuracy of more than 80% using SVM and 75% using rule based classifier, in Ujjain district was achieved. These results demonstrate the scope for using time-series S-1 VH data to develop an operational soybean crop-monitoring framework.
JUTE CROP PRODUCTION ESTIMATION IN MAJOR STATES OF INDIA: A COMPARATIVE STUDY OF LAST 6 YEARS’ FASAL AND DES ESTIMATES
Authors: Rajpoot S. , Saxena S. , Sehgal S. , Dubey S. K. , Choudhary K. , Gavli A. S. , Verma A. ,   Neetu, Ray S. S.
Published: July 2019

Abstract. In the last few years, remote sensing technique has emerged as a viable technology for crop acreage estimation. Under the FASAL project, the jute acreage estimation was carried out in the last 6 years by using both microwave SAR data (2012–13 to 2016–17) and high resolution optical multi-spectral data (2017–18). In the assessment using SAR data, hierarchical decision rule classification technique and for optical data hybrid classification approach was used. Yield was estimated using, agro-meteorological parameter based statistical models. In the present study, different statistical parameters such as correlation coefficient (r) and RMSE were used for evaluating and comparing the results of the last 6 years (2012–13 to 2017–18) with DES (government) estimates. The RMSE values over the years were found to be 7–20% and 5–13% for area and production, respectively. The correlation coefficient (r) over the years between DES and FASAL estimates ranging between 0.995 to 1.00 and 0.996 to 1.00 in acreage and production estimates respectively. At district level, the correlation coefficient (r) values for the area and production were 0.967 and 0.962 respectively. On the basis of statistical criteria used in this study, FASAL estimates were close to DES estimates and improved over the years. The FASAL jute production estimates could be called better than DES ones in terms of good accuracy, timely reporting and low labour intensive. Thus, the FASAL estimates can be continued for policy purposes as far as jute production forecasts are concerned in India.
SEN2-AGRI – CROP TYPE MAPPING PILOT STUDY USING SENTINEL-2 SATELLITE IMAGERY IN INDIA
Authors: Vijayasekaran D.
Published: July 2019

Abstract. Large-scale mapping and monitoring of agriculture land use are very important. It helps in forecast crop yields, assesses the factors influencing the crop stress and estimate the damage due to natural hazards. Also, more essentially, aids in calculating the irrigation water demand at the farm level and better water resource management. Recent developments in remote sensing satellite sensors spatial and temporal resolutions, global coverage and open access such as Sentinel-2, created new possibilities in mapping and monitoring land use/land cover features. The present study investigated the performance and applicability of Sen2-Agri system in the heterogeneous cropping system for operational crop type mapping at parcel resolution using time series Sentinel-2 multispectral satellite imagery. The parcel level crop type information was collected in the field by systematic sampling and used to train and validate the random forest (RF) classification in the system. The classification accuracy varied from 57% to 86% for different major crops. The overall classification accuracy was 70% with KAPPA index of 61%. The very small agriculture field size and persistent cloud cover are the major constraint to the improvement of classification accuracy. Combination of the time series imagery from multiple earth observation satellites for the monsoon cropping season and development of a robust system for in-situ data collection will further increase the mapping accuracy. Sen2-Agri system has the potential to handle a large amount of earth observation data and can be scaled up to the entire country, which will help in the efficient monitoring of crops.
MONITORING AND FORECASTING OF SEASONAL RICE CROP PRODUCTIVITY FOR PADDY DOMINATED REGIONS OF INDIA
Authors: Das N. N. , Andreadis K. , Ines A.
Published: July 2019

Abstract. The relevance of this study is immense for India. The Indian economy largely depends on agriculture, which is impacted by weather extremes and variability in monsoon. India is more vulnerable to disruption from drought than countries like the United States. While agriculture accounts for just 16 percent of India’s economy, half of its 1.3 billion people work on farms, thus, making agriculture the backbone of the Indian economy. However, in agriculture, rice is India’s most important food crop with nearly 1 billion Indian people reliant on it as their major food source. Most important constraint to rice production is water stress which affects nearly ~40 million ha of rainfed system from the total ~45 million ha area under rice cultivation. Future climate change effects on rainfall timing and amount, and projected increases in temperature are expected to exacerbate existing water stresses and will have a direct impact on agriculture in India, especially rice cultivation. We have developed an integrated system that is successfully implemented in many countries. The integrated system RHEAS (Regional Hydrological Extreme and Assessment System) coupled with M-DSSAT (modified DSSAT crop model) ingests various NASA Earth science data to produce a set of relevant hydrologic products (e.g., drought indices, water excess/stress information) and rice yields nowcasts (current conditions), forecasts, and seasonal projections, and then feed them into the operational agency. The overarching goal of this study is to provide this integrated system to stakeholder to improve decision-making process and mitigate the plights of rice farmers and prepare the country to deal with ground realities based on the forecast of rice production.
ASSESSING THE IMPACT OF CLIMATE CHANGE IN PONNANIYAR BASIN OF TAMIL NADU BASED ON REGCM 4.4 SIMULATIONS
Authors: Guhan V. , Geethalakshmi V. , Jagannathan R. , Panneerselvam S. , Bhuvaneswari K.
Published: July 2019

Abstract. Climate change induced extreme weather events such as drought and flood condition are likely to become more common and associated impacts on crop production will be more without proper irrigation planning. The present investigation was undertaken for assessing the impact of Climate change on tomato yield and water use efficiency (WUE) using AquaCrop model and RegCM 4.4 simulations. The water driven AquaCrop model was validated based on observation of field experiment conducted with four different dates of sowing (1st November, 15th November, 1st December, 15th December) at Ponnaniyar basin, Tiruchirappalli. Validation of AquaCrop model indicated the capability of AquaCrop in predicting tomato yield, biomass and WUE close to the observed data. Seasonal maximum and minimum temperatures over Tiruchirappalli are projected to increase in the mid-century under both RCP4.5 and RCP8.5 scenarios. Maximum temperature is expected to increase up to 1.7 °C/2.5 °C in SWM and 1.9 °C/2.9 °C in NEM by the mid of century as projected through stabilization (RCP 4.5) and overshoot emission (RCP 8.5) pathways. Minimum temperature is expected to increase up to 1.6 °C/2.2 °C in SWM and 1.6 °C/2.1 °C in NEM by the mid of century as projected through stabilization (RCP 4.5) and overshoot emission (RCP 8.5) pathways. Seasonal rainfall over Tiruchirappalli is expected to decrease with RCP4.5 and RCP8.5scenarios with different magnitude. Rainfall is expected to change to the tune of −1/−11 per cent in SWM and −2/−14 per cent in NEM by the mid of century as projected through stabilization (RCP 4.5) and overshoot emission (RCP 8.5) pathways.
DISCRIMINATION OF SUGARCANE CROP AND CANE YIELD ESTIMATION USING LANDSAT AND IRS RESOURCESAT SATELLITE DATA
Authors: Pandey S. , Patel N. R. , Danodia A. , Singh R.
Published: July 2019

Abstract. The objective of this research work aims at crop acreage estimation at mill catchment level, derivation of sugarcane phenology and yield estimation at field level. The study was carried out in Kisan Sahkari Chini Mill catchment, Nanauta, Saharanpur, Uttar Pradesh. Extensive and systematic field sampling was carried out for ground-truth observations, biophysical measurements (LAI and above/below canopy PAR) and mill-able cane yield through crop cutting experiments. Major emphasis were laid on sugarcane crop discrimination, biophysical parameter estimation, generation of phenological metrics and yield model development for sugarcane crop at mill catchment level. Sugarcane crop discrimination and its acreage estimation was done using multi-sensor satellite data. The sugarcane classification accuracies were > 92% for LISS-IV, > 86% for Landsat-8 and > 83% for LISS-III classified image. The sugarcane phenological matrices at field level derived using time-series of NDVI for a period of 2015–2016 through TIMESAT software. To retrieve the biophysical parameters particularly leaf area index, best predictive function developed with vegetation indices (EVI, NDVI, SAVI) through correlation and regression analysis along this cane yield estimation attempted with multi-date (eight-day) NDVI from Landsat OLI. Yield models developed for ratoon cane and planted cane explained variance in yield significantly with coefficient of determination (R2) values equal to 0.83 and 0.69, respectively. Similar predictive functions were also established with monthly composite dataset for village-level yield estimates with step wise regression (R2 = 0.83) (P = 0.00001), Multi linear regression (MLR) (R2 = 0.792) (P = 0.00081) and Random forest regression (R2 = 0.466) (P = 0.038).
CLIMATE CHANGE IMPACT AND RESPONSE OF RICE YIELD
Authors: Rana M. , Singh K. K. , Kumari N. , Sanjay J. , Gohain G. P. , Kalra N.
Published: July 2019

Abstract. Rice is an important cereal crop and part of daily diet not only in India but also throughout Asia. Agriculture is highly dependent on the variations in temperature, precipitation and solar radiation and long-term climate patterns. The pattern of changing climate in last 30 years indicate that predictable and possible changes in rainfall and temperature can reduce agriculture outputs and yields particularly for rice and wheat significantly. The main aim of this research paper is to study the Kharif Rice Productivity in Hisar, Haryana under changing climate. The study focuses on the impacts of climate change namely intensity, timings and spatial distribution of rainfall. Kharif rice is more vulnerable to meteorological drought due to growing uncertainties in monsoon rains under the changing climate patterns. The study of seasonal changes in precipitation at decadal scale for observed and CORDEX projected precipitation for the selected region was done to understand the impacts of climate change. Along with this, DSSAT Crop Simulation Model was run to quantify the water stress in the years with more negative rainfall departure and to identify the reasons for variability in yield. DSSAT model was able to simulate phenological events and final grain yield at maturity stage with reasonable accuracy under varied weather conditions. The analysis of the simulated results indicates the association between yield and rainfall amount and its distribution during the season and different phenological growth stages of rice. The results further indicate that water stress at important stages such as Booting, Heading and Flowering majorly impact the final yield.
MULTI STAGE WHEAT YIELD ESTIMATION USING DIFFERENT MODEL UNDER SEMI ARID REGION OF INDIA
Authors: Vashisth A. , Krishanan P. , Joshi D. K.
Published: July 2019

Abstract. Crop yield estimation before harvest is required for marketing, pricing, storage, import, export etc. Productivity of cropping systems under various weather, management and policy scenarios can be predicted successfully by simulation models. Due to increase in input cost of agricultural operation, agriculture produces become costly. Therefore, crop yield estimation in the agriculture becomes essential. Weather variability causes the losses in the yield. Therefore, model based on weather parameters, soil parameter and crop parameters can provide reliable crop yield estimation in advance. For estimating the multi stage wheat crop yield, experiments were conducted at research farm of IARI, New Delhi during Rabi 2016–17 and Rabi 2017–18. Crop yield were estimated by weather based and crop simulation model. Percentage deviation of estimated yield by observed yield at flowering and grain filling stage was −5.1 and 2.0 by weather based model, 4.3 and 2.1 by InfoCrop model, 10.2 and 9.0 by DSSAT model during Rabi 2016–17 and 5.3 and 5.9 by weather based model, 2.3 and 2.2 by InfoCrop model, −10.8 and −9.6 by DSSAT model during Rabi 2017–18 respectively. Among the three models opted for estimating the yield at flowering and grain filling stage, InfoCrop model gave better results followed by weather based and DSSAT model. Therefore, this model can be used for multi stage wheat crop yield estimation at district as well as regional level.
CROP INVENTORY OF ORCHARD CROPS IN INDIA USING REMOTELY SENSED DATA
Authors: Chaudhari K. , Nishant N. , Upadhyay G. , More R. , Singh N. , Vyas S. P. , Bhattacharya B. K.
Published: July 2019

Abstract. The use of satellite remote sensing (RS) technologies for purpose of crop discrimination, mapping, area estimation, condition and yield assessment has been proved to be effective and efficient in terms of time and cost, having better consistency implemented with scientific approaches. However, application of satellite RS technology for horticultural crops in India has certain challenges due to scattered and small field sizes, comparatively short duration such as vegetable crops and mixed cropping. Hence the study was taken for developing research methodology for area assessment of three major fruit crops such as Banana, Mango and Citrus over 20 districts in four states viz. Gujarat, Madhya Pradesh, Uttar Pradesh and Bihar. Appropriate bio-window for analysing different crop types was selected and mapping of crops were done using pixel based hybrid classification i.e. un-supervised ISODATA clustering plus supervised MXL classification as well as object based classification of high resolution remote sensing data (Resourcesat LISS III and/or LISS IV, Cartosat – 1 PAN) followed by their accuracy assessment and their comparison with departmental reported statistics. Overall, the classification accuracy was more than 80% for all the crops. Deviation from statistics were in the range of 3 to 38%. Higher deviations from statistics were mostly due to use of lower resolution satellite data or mixing of crops having similar spectral signatures e.g. mango and sapota in Navsari and Valsad districts of Gujarat. It was very difficult to discriminate the young orchards of 2–3 years from other field crops due to mixed / inter cropping practices. The maps were checked and certified by respective State Horticulture Departments and were archived in VEADS, SAC and BHUVAN, NRSC geoportals of ISRO. RISAT – 1 (microwave) data were explored for the estimation of banana orchards in order to detect banana plantation at early stage and under cloudy sky conditions. There is huge potential of application in this sector using advanced observations from hyperspectral, thermal infrared sensors and advanced radars or LIDAR’s on-board upcoming satellites.
COMPARISON OF DIFFERENT CLASSIFICATION TECHNIQUES TO IDENTIFY COCONUT GROWING AREAS IN KOZIKHODE DISTRICT, KERALA
Authors: Singh N. , Roy S. , Kumar P. , Kimothi M. M. , Mamatha S.
Published: July 2019

Abstract. This study was envisaged to map the coconut growing areas in Kerala state of India, using multidate NDVI obtained from sentinel 2A MSI data, having spatial resolution as 10 m. 95% Cloud free satellite images were taken for classification and date of pass considered for the study were 16th February, 2017 and 18th December, 2017 for Kozhikode district of Kerala. In this study bio-window of coconut plantation was identified using NDVI images of two dates. It was observed that interclass variations were more prominent in February image. Forest, dense and moderately dense coconut plantations have significantly different NDVI values in February image whereas in December image all three features have similar values. Hence, February image was classified using three classification methods i.e. ISODATA, maximum likelihood and random forest classification to assess which method is better to distinguish coconut plantation from other classes. Random Forest classification technique was found to be more accurate in identifying coconut plantation. Area was also estimated for Kozhikode district and compared with the government statistics. Google Earth was taken as reference to identify coconut plantation as it has a unique star shaped canopy, which is clearly visible in high-resolution imagery.
SITE SUITABILITY FOR DEVELOPING NEW COLD CHAIN USING MULTI-CRITERIA DECISION ANALYSIS AND GEOSPATIAL TECHNIQUES
Authors: Upadhyay G. , Bhattacharya B. K.
Published: July 2019

Abstract. Growth and performance of various sectors of a country largely depends on the infrastructure developed by the country. It is true about the agricultural sector also. Along with the numbers, the location of these infrastructure play a vital role in reducing cost to the farmers while utilizing the existing resources like land, water, electricity and road network to their optimum level. India is the second largest producer of fruits, vegetable and tea. Against the total production of more than 500 MMT of horticultural & non-horticultural produces, the total cold storage capacity is estimated at approximately 31 MMT, which is not even 10% of the total production. In view of this, a site suitability study was conducted to develop an optimum plan to locate cold storages in the state of Uttar Pradesh, a leading potato growing state. Factors considered for evolving the plan includes the site of production, i.e. region where potato is grown, road network, existing cold storage, electricity and land use. When there are various factors behind any decision-making process, it becomes a complex process. It becomes difficult to decide which factor is to be given more importance and how other factors can be compounded with each other to arrive at a decision. Analytical Hierarchy process (AHP), helps us in determining the relative importance of various factors to arrive at a decision. In view of infrastructure planning, an illustrative map indicating spatial features is vital. As is widely established, remote sensing and GIS helps to obtain such a spatial map. Remote sensing and GIS was used to generate maps of the factors involved. AHP was used to develop weights of the factors in relation to each other to generate a map showing site suitability of places for developing cold storage facilities.
GEOSPATIAL PERSPECTIVE FOR POST-HARVEST INFRASTRUCTURE MANAGEMENT: POSITIONING OF NEW COLD STORAGE
Authors: Vijjapu P. , Kimothi M. M. , Roy S. , Mamatha S. , Ray S. S.
Published: July 2019

Abstract. The deficiency in post-harvest infrastructure leads to loss of agricultural produce which in turn affects farmer’s income and food security. So, there is a need to improve post-harvest infrastructure in the country. Potato is a major horticultural crop requiring cold storage facility. This study was carried out for Bihar state of India, which has the least ratio of storage capacity to potato production in comparison to other states. An approach has been developed to identify the suitable locations for cold storages using geospatial technology to increase accessibility to cold storage facilities. Temporal variations in vegetation profiles were used to generate crop maps and from this crop area proportions were calculated at village level. These proportions were used to identify significant village clusters contributing to horticulture production. From this priority villages were identified. These priority villages were assigned to nearest major settlement which will be the sites for positioning new cold storage facility. The approach developed in this study has identified 63 locations in 17 districts for developing new cold storage facility. The proposed new locations for cold storages will reduce the distance to nearest cold storage for 14244 villages and this reduction in distance will be more than 8 kms for 9774 villages. Thus, the study validated the role of Remote Sensing and GIS for post-harvest infrastructure planning.
SURFACE MOISTURE AND IRRIGATION MAPPING AT AGRICULTURAL FIELD SCALE USING THE SYNERGY SENTINEL-1/SENTINEL-2 DATA
Authors: Zribi M. , Baghdadi N. , Bousbih S. , El-Hajj M. , Gao Q.
Published: July 2019

Abstract. Soil moisture plays a key role in various processes at the soil-vegetation-atmosphere interface, such as evapotranspiration, infiltration and runoff. In this study, we firstly propose a global analysis of Sentinel-1 (S1) & Sentinel-2 (S2) data potential to retrieve soil moisture. Two approaches are tested. The first one is based on neural network approach; it uses Integral Equation Model (IEM) coupled to Water Cloud Model for vegetation cover backscattering simulation (El Hajj et al., 2017). The second approach considers change detection methodology. It estimates change of soil moisture with the driest and highest moisture levels, and also change of moisture between successive radar acquisitions (Gao et al., 2017). The proposed approaches are validated over three agricultural regions, south of France, Urgell (Spain) and Merguellil (Tunisia). In these different sites, important ground campaigns have been realized over reference fields with different types of measurements (soil moisture and roughness, Leaf area Index of vegetation cover). The retrieved accuracy of estimated volumetric soil moisture is about 5 vol.%. Based on estimated moisture products, two methodologies are considered to map irrigated areas (Gao et al., 2018, Bousbih et al., 2018). An analysis of different metrics (mean, variance, correlation length, etc.) of radar signal time series and surface parameters (moisture and NDVI) are tested. The proposed classification of irrigated areas is based on a combination of Support Vector Machine (SVM) and decision tree methodologies. For Urgell and Merguellil sites, a mapping of irrigated fields is proposed. The accuracy of mapping is higher than 75% for the two studied sites.