Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE

Estimation of soil parameters by inverse modeling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise when heterogeneous layered soils are considered. The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables - leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS. This was performed using GLUE method on a synthetic data set on varying soil types and on a data set from a field experiment carried out in two maize plots in South India. The main results were (i) combination of surface soil moisture and above-ground biomass provided consistently good estimates with small uncertainity of soil properties for the two soil layers, for a wide range of soil paramater values, both in the synthetic and the field experiment, (ii) above-ground biomass was found to give relatively better estimates and lower uncertainty than LAI when combined with surface soil moisture, especially for estimation of soil depth, (iii) surface soil moisture data, either alone or combined with crop variables, provided a very good estimate of the water holding capacity of the upper soil layer with very small uncertainty whereas using the surface soil moisture alone gave very poor estimates of the soil properties of the deeper layer, and (iv) using crop variables alone (else above-ground biomass or LAI) provided reasonable estimates of the deeper layer properties depending on the soil type but provided poor estimates of the first layer properties. The robustness of combining observations of the surface soil moisture and the above-ground biomass for estimating two layer soil properties, which was demonstrated using both synthetic and field experiments in this study, needs now to be tested for a broader range of climatic conditions and crop types, to assess its potential for spatial applications. (C) 2012 Elsevier B.V. All rights reserved.

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.

Lamb wave based detection of damage in a stiffener bonded to a plate

Stiffener is one of the major components of aircraft structures to increase the load carrying capacity. Damage in the stiffener, mostly in the form of crack is an unavoidable problem in aerospace structures. Stiffener is bonded to the inner side of the aircraft panel which is not accessible for immediate inspection. A sensor-actuator network can be placed on the outer side of the panel that is accessible. Ultrasonic lamb waves are transmitted through stiffener using the sensoractuator network for detecting the presence of damages. The sensor-actuator network is placed on both halves of the stiffened section on the accessible surface of the plate. Detecting damage in stiffener by using this technique has significant potential for SHM technology. One of the major objectives of the present work is to determine the smallest detectable crack on the stiffener using the proposed technique. Wavelet based damage parameter correlation studies are carried out. In the proposed scheme, with increase in the damage size along the stiffener, it is found that the amplitude of the received signal decreases monotonically. The advantage of this technique is that the stiffened panels need not be disassembled in a realistic deployment of SHM system.

Lamb Wave Propagation in Laminated Composite Structures

Damage detection using guided Lamb waves is an important tool in Structural health Monitoring. In this paper, we outline a method of obtaining Lamb wave modes in composite structures using two dimensional Spectral Finite Elements. Using this approach, Lamb wave dispersion curves are obtained for laminated composite structures with different fibre orientation. These propagating Lamb wave modes are pictorially captured using tone burst signal.

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.)