Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Gene expression programming-fuzzy logic method for crop type classification

Crop type classification using remote sensing data plays a vital role in planning cultivation activities and for optimal usage of the available fertile land. Thus a reliable and precise classification of agricultural crops can help improve agricultural productivity. Hence in this paper a gene expression programming based fuzzy logic approach for multiclass crop classification using Multispectral satellite image is proposed. The purpose of this work is to utilize the optimization capabilities of GEP for tuning the fuzzy membership functions. The capabilities of GEP as a classifier is also studied. The proposed method is compared to Bayesian and Maximum likelihood classifier in terms of performance evaluation. From the results we can conclude that the proposed method is effective for classification.

Improved modeling of groundwater recharge in agricultural watersheds using a combination of crop model and remote sensing

For improved water management and efficiency of use in agriculture, studies dealing with coupled crop-surface water-groundwater models are needed. Such integrated models of crop and hydrology can provide accurate quantification of spatio-temporal variations of water balance parameters such as soil moisture store, evapotranspiration and recharge in a catchment. Performance of a coupled crop-hydrology model would depend on the availability of a calibrated crop model for various irrigated/rainfed crops and also on an accurate knowledge of soil hydraulic parameters in the catchment at relevant scale. Moreover, such a coupled model should be designed so as to enable the use/assimilation of recent satellite remote sensing products (optical and microwave) in order to model the processes at catchment scales. In this study we present a framework to couple a crop model with a groundwater model for applications to irrigated groundwater agricultural systems. We discuss the calibration of the STICS crop model and present a methodology to estimate the soil hydraulic parameters by inversion of crop model using both ground and satellite based data. Using this methodology we demonstrate the feasibility of estimation of potential recharge due to spatially varying soil/crop matrix.

GHG footprint of major cities in India

Concentration of greenhouse gases (GHG) in the atmosphere has been increasing rapidly during the last century due to ever increasing anthropogenic activities resulting in significant increases in the temperature of the Earth causing global warming. Major sources of GHG are forests (due to human induced land cover changes leading to deforestation), power generation (burning of fossil fuels), transportation (burning fossil fuel), agriculture (livestock, farming, rice cultivation and burning of crop residues), water bodies (wetlands), industry and urban activities (building, construction, transport, solid and liquid waste). Aggregation of GHG (CO2 and non-CO2 gases), in terms of Carbon dioxide equivalent (CO(2)e), indicate the GHG footprint. GHG footprint is thus a measure of the impact of human activities on the environment in terms of the amount of greenhouse gases produced. This study focuses on accounting of the amount of three important greenhouses gases namely carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and thereby developing GHG footprint of the major cities in India. National GHG inventories have been used for quantification of sector-wise greenhouse gas emissions. Country specific emission factors are used where all the emission factors are available. Default emission factors from IPCC guidelines are used when there are no country specific emission factors. Emission of each greenhouse gas is estimated by multiplying fuel consumption by the corresponding emission factor. The current study estimates GHG footprint or GHG emissions (in terms of CO2 equivalent) for Indian major cities and explores the linkages with the population and GDP. GHG footprint (Aggregation of Carbon dioxide equivalent emissions of GHG's) of Delhi, Greater Mumbai, Kolkata, Chennai, Greater Bangalore, Hyderabad and Ahmedabad are found to be 38,633.2 Gg, 22,783.08 Gg, 14,812.10 Gg, 22,090.55 Gg, 19,796.5 Gg, 13,734.59 Gg and 91,24.45 Gg CO2 eq., respectively. The major contributors sectors are transportation sector (contributing 32%, 17.4%, 13.3%, 19.5%, 43.5%, 56.86% and 25%), domestic sector (contributing 30.26%, 37.2%, 42.78%, 39%, 21.6%, 17.05% and 27.9%) and industrial sector (contributing 7.9%, 7.9%, 17.66%, 20.25%, 1231%, 11.38% and 22.41%) of the total emissions in Delhi, Greater Mumbai, Kolkata, Chennai, Greater Bangalore, Hyderabad and Ahmedabad, respectively. Chennai emits 4.79 t of CO2 equivalent emissions per capita, the highest among all the cities followed by Kolkata which emits 3.29 t of CO2 equivalent emissions per capita. Also Chennai emits the highest CO2 equivalent emissions per GDP (2.55 t CO2 eq./Lakh Rs.) followed by Greater Bangalore which emits 2.18 t CO2 eq./Lakh Rs. (C) 2015 Elsevier Ltd. All rights reserved.

Comparative evaluation of inversion approaches of the radiative transfer model for estimation of crop biophysical parameters

The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

Occurrence of sorghum midge stenodiplosis sorghicola (Coq,) during the second crop growing season on the pacific coastal plain of Nicaragua

La mosquita de la panojas del sorgo, Stenediplosls sorghicola (Coq.) es una de las plagas mas importantes que atacan al sorgo en Nicaragua. Varios estudios fueron conducidos en el pacifico de Nicaragua durante 1998 y 1999 para determinar hospederos y la actividad de esta plaga durante la segunda fecha de siembra de este cultivo (Postrera). Hembras oviposltaron en sorgo desde mediados de Septiembre hasta los últimos dfas de Diciembre. Cuando sorgo no se encontraba presente, hembras ovipositaron en sorgo escobero, Sorghum bicolor (L.) o pastoJonson, Sorghum halepense L. Pasto Jonson florea durante todo el ano y puede servir como hospedero mientras las otras especies de sorghum no se encuentran en el campo. Cuando estos tres hospederos estaban floreando al mismo tiempo, las hembras exhibieron una fuerte preferencia para ovlpositar en sorgo. Basado en estas observaciones la mosquita de la panoja del sorgo puede estar activa durante todo el ano en el pacifico de Nicaragua. Conocimiento de la ocurrencia y comportamiento de la mosquita en el area, es muy Importante para el desarrollo de estrategias de manejo de esta plaga.

Effects of preceding crop and weed control method on weeds and common bean (Phaseoulus vulgaris L.) yield in a no-tillage cropping system

En 1994, se inició un trabajo de investigación el cual se continuo durante tres años, con el objetivo de evaluar el efecto de cultivos antecesores y métodos de control de malezas sobre el rendimiento frijol común ( P h a s e o l u s vulgaris L.) y la dinámica de las malezas. El frijol y los cultivos antecesores fueron sembrados en sistema de cero labranza. Las secuencias de cultivos estudiadas fueron: maíz (Zea mays L), seguido de frijol y frijol seguido de frijol. Se analizaron tres ciclos de los cultivos (1994, 1995 y 1996). La secuencia de cultivo que produjo el máximo rendimiento fue maíz seguido de frijol en 1994, así como también el promedio de rendimiento a través de los años. Por otro lado, los mayores valores de vainas por planta y semillas por vaina se obtuvieron cuando el frijol antecedió al frijol en 1994. Parcelas con controles de malezas mecánico y químico obtuvieron menores densidades y peso seco de malezas y mejores rendimientos que aquellas parcelas en las cuales se controlo la maleza a través de cobertura muerta.

A quantitative analysis of the phytoplankton of the Gulf of Panama II. On the relationship between C14 assimilation and the diatom standing crop

ENGLISH: The Inter-American Tropical Tuna Commission has maintained a hydro-biological station in the Gulf of Panama located at 8°45'N, 79°23'W in connection with their ecological investigation of the anchoveta (Cetengraulis mysticetus), a tuna baitfish (see Peterson, 1961, for references) . The depth is approximately 42 meters at mean low water at this station. Routine hydrographic and biological observations have been made (Schaefer, Bishop and Howard, 1958; Schaefer and Bishop, 1958; Forsbergh, 1963), including the collection of quantitative phytoplankton samples from November 1954 through May 1957 (Smayda, 1959; unpublished). The seasonal and regional variations in phytoplankton growth in the Gulf of Panama have also been investigated (Smayda, 1963). The relationships existing between C1 4 assimilation as determined by 24 hour in situ experiments and diatom standing crop at 10 meters when expressed as cell numbers, cell volume, cell surface area and cell plasma volume have been assessed for 30 observations made between November 1954 and May 1957 at 8°45'N, 79°23'W. The average cell volume and cell surface area characteristics for 110 diatom species and varieties are presented. SPANISH: Las relaciones existentes entre la asimilación del C14 , determinadas después de 24 horas de experimentos in situ, y la cosecha estable de las diatomeas a 10 metros, expresando el número de células, volumen celular, área de la superficie celular y volumen del plasma celular, han sido determinadas por medio de 30 observaciones hechas entre noviembre de 1954 y mayo de 1957, a los 8°45'N, 79°23'W. Se presenta, para 110 especies y variedades de diatomeas, el promedio de las características del volumen celular y del área de la superficie celular. (PDF contains 67 pages.)

A proposed integrated livestock-rice-poultry-cum-fish culture in enclosure system

Integrated agriculture-cum-fish farming has been practised profitably for ages in the Chinese small-scale farming system. There is a great potential for this system by utilizing the vast Nigerian flood plains (approx. 515,000 ha). Dogongari Bay in Lake Kainji Basin was identified as a suitable site for this system after some extensive fish culture trials. Polyculture of Clarias spp., Heterotis niloticus and Tilapia was proposed for integration with layers in the poultry house, 2-ha upland rain-fed rice farming and indirect cattle rearing in the 5-ha enclosure site. Cost benefit analysis showed that the system will consistently record profit as from the second year of operation. Various complex factors were identified to affect profitability of this mixed farming system. Concerted research approach is needed to fully understand the interrelationships of the various components of this integrated system. Generous funding of research activities is very crucial in this situation

Effects of international trade of food and feed and human diet shifts on food security and environmental safety: integrating scales

4 p.

Modelling the Effect of Climate Change on Environmental Pollution Losses from Dairy Systems in the UK

21 p.

Aquaculture, fisheries, poverty and food security

Fisheries and aquaculture play important roles in providing food and income in many developing countries, either as a stand-alone activity or in association with crop agriculture and livestock rearing. The aim of this paper is to identify how these contributions of fisheries and aquaculture to poverty reduction and food security can be enhanced while also addressing the need for a sustainability transition in over-exploited and over-capitalized capture fisheries, and for improved environmental performance and distributive justice in a rapidly growing aquaculture sector. The focus of the paper is on the poverty and food security concerns of developing countries, with an emphasis on the least developed. The emphasis is on food security rather than poverty reduction policies and strategies, although the two are of course related. The food security agenda is very much to the fore at present; fish prices rose along with other food prices in 2007-8 and as fish provide important nutritional benefits to the poor, food security has become a primary concern for sector policy.

Uganda and Malawi field pilots of proposed LSMS fisheries module: summary report

While an overwhelming majority of sub-Saharan African countries exhibit serious weaknesses in statistics pertaining to crop and livestock sectors, the deficiencies in terms of nationally representative data on the fishery sector are even more acute. The very little data available on the sector are essentially derived from case studies of selected fisheries, and the limited nationally representative data available are generally derived from a few questions included in the livestock section of household surveys. These do not permit the detailed characterization of the fishery production systems. As a consequence in many countries the decision-makers and planners lack the most basic information about the role and importance of the fisheries sector to their national economy. As part of an initiative called the Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) project, a collaboration was developed between the World Bank and the WorldFish Center to address this situation. This report provides detail on pilot testing of a fisheries module for living standards measurement surveys.