Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

Radiative transfer, interception and scattering in coniferous forests : models and applications for production ecology and remote sensing

This work develops methods to account for shoot structure in models of coniferous canopy radiative transfer. Shoot structure, as it varies along the light gradient inside canopy, affects the efficiency of light interception per unit needle area, foliage biomass, or foliage nitrogen. The clumping of needles in the shoot volume also causes a notable amount of multiple scattering of light within coniferous shoots. The effect of shoot structure on light interception is treated in the context of canopy level photosynthesis and resource use models, and the phenomenon of within-shoot multiple scattering in the context of physical canopy reflectance models for remote sensing purposes. Light interception. A method for estimating the amount of PAR (Photosynthetically Active Radiation) intercepted by a conifer shoot is presented. The method combines modelling of the directional distribution of radiation above canopy, fish-eye photographs taken at shoot locations to measure canopy gap fraction, and geometrical measurements of shoot orientation and structure. Data on light availability, shoot and needle structure and nitrogen content has been collected from canopies of Pacific silver fir (Abies amabilis (Dougl.) Forbes) and Norway spruce (Picea abies (L.) Karst.). Shoot structure acclimated to light gradient inside canopy so that more shaded shoots have better light interception efficiency. Light interception efficiency of shoots varied about two-fold per needle area, about four-fold per needle dry mass, and about five-fold per nitrogen content. Comparison of fertilized and control stands of Norway spruce indicated that light interception efficiency is not greatly affected by fertilization. Light scattering. Structure of coniferous shoots gives rise to multiple scattering of light between the needles of the shoot. Using geometric models of shoots, multiple scattering was studied by photon tracing simulations. Based on simulation results, the dependence of the scattering coefficient of shoot from the scattering coefficient of needles is shown to follow a simple one-parameter model. The single parameter, termed the recollision probability, describes the level of clumping of the needles in the shoot, is wavelength independent, and can be connected to previously used clumping indices. By using the recollision probability to correct for the within-shoot multiple scattering, canopy radiative transfer models which have used leaves as basic elements can use shoots as basic elements, and thus be applied for coniferous forests. Preliminary testing of this approach seems to explain, at least partially, why coniferous forests appear darker than broadleaved forests in satellite data.

Decision fusion for reliable flood mapping using remote sensing images

Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One of the great challenges involved in the data interpretation is to separate the permanent water bodies and flooding regions, including both the fully inundated areas and the wet areas where trees and houses are partly covered with water. This paper adopts the decision fusion technique to combine the mapping results from radar data and the NDVI data derived from optical data. An improved capacity in terms of identifying the permanent or semi-permanent water bodies from flood inundated areas has been achieved. Computer software tools Multispec and Matlab were used.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Vegetation Analysis in Uttara Kannada District Using GIS and Remote Sensing Techniques

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

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.

Light Reflectance Characteristics and Remote Sensing of Waterlettuce

Waterlettuce ( Pistia stratiotes L.) is a free-floating exotic aquatic weed that often invades and clogs waterways in the southeastern United States. A study was conducted to evaluate the potential of using remote sensing technology to distinguish infestations of waterlettuce in Texas waterways. Field reflectance measurements showed that waterlettuce had higher visible green reflectance than associated plant species. Waterlettuce could be detected in both aerial color- infrared (CIR) photography and videography where it had light pink to pinkish-white image tonal responses. Computer analysis of CIR photographic and videographic images had overall accuracy assessments of 86% and 84%, respectively. (PDF contains 6 pages.)

Hazard and risk assessment from Hurricane Ivan (2004) in Grenada using Geographical Information Systems and remote sensing

Hurricanes are destructive storms with strong winds, intense storm surges, and heavy rainfall. The resulting impact from a hurricane can include structural damage to buildings and infrastructure, flooding, and ultimately loss of human life. This paper seeks to identify the impact of Hurricane Ivan on the aected population of Grenada, one of the Caribbean islands. Hurricane Ivan made landfall on 7th September 2004 and resulted in 80% of the population being adversely aected. The methods that were used to model these impacts involved performing hazard and risk assessments using GIS and remote sensing techniques. Spatial analyses were used to create a hazard and a risk map. Hazards were identied initially as those caused by storm surges, severe winds speeds, and flooding events related to Hurricane Ivan. These estimated hazards were then used to create a risk map. An innovative approach was adopted, including the use of hillshading to assess the damage caused by high wind speeds. This paper explains in detail the methodology used and the results produced.

Ocean structure and climate (Eastern North Atlantic): in situ measurement and remote sensing

Structure and climate of the east North Atlantic are appraised within a framework of in situ measurement and altimeter remote sensing from 0 degree - 60 degree N. Long zonal expendable bathythermograph /conductivity-temperature-depth probe sections show repeating internal structure in the North Atlantic Ocean. Drogued buoys and subsurface floats give westward speeds for eddies and wavelike structure. Records from longterm current meter deployments give the periodicity of the repeating structure. Eddy and wave characteristics of period, size or wavelength, westward propagation speed, and mean currents are derived at 20 degree N, 26 degree N, 32.5 degree N, 36 degree N and 48 degree N from in situ measurements in the Atlantic Ocean. It is shown that ocean wave and eddy-like features measured in situ correlate with altimeter structure. Interior ocean wave crests or cold dome-like temperature structures are cyclonic and have negative surface altimeter anomalies; mesoscale internal wave troughs or warm structures are anticyclonic and have positive surface height anomalies. Along the Eastern Boundary, flows and temperature climate are examined in terms of sla and North Atlantic Oscillation (NAO) Index. Longterm changes in ocean climate and circulation are derived from sla data. It is shown that longterm changes from 1992 to 2002 in the North Atlantic Current and the Subtropical Gyre transport determined from sla data correlate with winter NAO Index such that maximum flow conditions occurred in 1995 and 2000. Minimum circulation conditions occurred between 1996-1998. Years of extreme negative winter NAO Index result in enhanced poleward flow along the Eastern Boundary and anomalous winter warming along the West European Continental Slope as was measured in 1990, 1996, 1998 and 2001.

Position and structure of the subtropical/Azores front region from combined Lagrangian and remote sensing (IR/altimeter/SeaWIFS) measurements

The position and structure of the North Atlantic Subtropical Front is studied using Lagrangian flow tracks and remote sensing (AVHRR imagery: TOPEX/POSEIDON altimetry: SeaWiFS) in a broad region ( similar to 31 degree to similar to 36 degree N) of marked gradient of dynamic height (Azores Current) that extends from the Mid-Atlantic Ridge (MAR), near similar to 40 degree W, to the Eastern Boundary ( similar to 10 degree W). Drogued Argos buoy and ALACE tracks are superposed on infrared satellite images in the Subtropical Front region. Cold (cyclonic) structures, called storms, and warm (anticyclonic) structures of 100-300 km in size can be found on the south side of the Subtropical Front outcrop, which has a temperature contrast of about 1 degree C that can be followed for similar to 2500 km near 35 degree N. Warmer water adjacent to the outcrop is flowing eastward (Azores Current) but some warm water is returned westward about 300 km to the south (southern Counterflow). Estimates of horizontal diffusion in a Storm (D=2.2t10 super(2) m super(2) s super(-1)) and in the Subtropical Front region near 200 m depth (D sub(x)=1.3t10 super(4) m super(2) s super(-1), D sub(y)=2.6t10 super(3) m super(2) s super(-1)) are made from the Lagrangian tracks. Altimeter and in situ measurements show that Storms track westwards. Storms are separated by about 510 km and move westward at 2.7 km d super(-1). Remote sensing reveals that some initial structures start evolving as far east as 23 degree W but are more organized near 29 degree W and therefore Storms are about 1 year old when they reach the MAR (having travelled a distance of 1000 km). Structure and seasonality in SeaWiFS data in the region is examined.

UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Geochemical, Sedimentological And Remote Sensing Studies Of Kayamkulam Estuary, South West Coast Of India- A Gis Approach

In this study, an attempt has been made to find the textural, geochemical, sedimentological characteristics of sediments and water phases of the kayamkulam estuary located in the Southwest coast of Kerala, besides the impact of gas based thermal power plant located at the northern part of the estuary. Estuaries are an important stage in the transport of the solid weathering product of the earth’s crust. These weathered products or sediments are complex mixtures of a number of solid phases that may include clays, silica, organic matter, metal oxides, carbonates, sulfides and a number of minerals. Studies on the aquatic systems revealed the fact that it posses severe ecological impairments due to heavy discharge of sediments from 44 rivers, the continued disposal of pollutants rich materials from industries, sewage channels, agricultural areas and retting yards