A Weighing System for Grab Loaders for Sugar Cane Yield Mapping

There are no commercial yield monitors for sugar cane despite the economic importance of the crop for sugar and alcohol production. As sugar cane is not mechanically harvested in some regions, special yield monitors need to be developed considering the harvest and load methods used. Grab loaders are essential when the crop is manually harvested. If the weight of the crop being loaded is monitored, yield maps can be produced. This paper presents the development of a weight measurement system for grab loaders. It is based on a mechanical device that contains a load cell adapted to the machine. As it is necessary to perform this measurement dynamically, the effect of movement on the measured value must be corrected. Thus, a mathematical model was developed to assess the effect of each parameter on the dynamics of the load and on the measured weight. In order to collect data to evaluate the model, an experimental measurement system was assembled and used in field tests. The analysis of the results showed that the model was able to describe the machine behaviour within the limits considered. Mean errors of ±2% or less were obtained for each load if the sampling period was adequately chosen. The frequency response of the angle sensors used and the low sampling rate of the subsystems used restricted the ability to define a single period for error minimisation. These two points will be addressed in the development of dedicated hardware, to allow the use of filtering and processing techniques in real time to obtain measurements with consistently low errors.     

Impact of anthropogenic induced nitrogen input and liming on phosphorus leaching in forest soils

Phosphorus (P) is essential for sustainable forest growth, yet the impact of anthropogenic impacts on P leaching losses from forest soils is hardly known. We conducted an irrigation experiment with 128 mesocosms from three forest sites representing a gradient of resin extractable P of the A‐horizon. On each site we selected a Fagus sylvatica and a Picea abies managed subsite. We simulated ambient rain (AR), anthropogenic nitrogen input (NI) of 100 kg (ha · a)^?1 and forest liming (FL) with a dolomite input of 0.3 Mg (ha · a)^?1. Soil solution was extracted from the organic layer, 10 cm depth and 20 cm depth of the mesocosms, and analyzed for molybdate reactive phosphorus (MRP) and molybdate unreactive phosphorus (MUP). Additionally, we separated colloids from the soil solution using Asymmetric Field Flow Fractionation for assessing the colloidal fraction of total element concentrations. NI increased MRP and MUP concentrations for all plots with one exception, while FL decreased MRP and MUP with the exception of another plot. While the irrigation treatments had little impact on the P‐richest site, MRP and MUP concentrations changed strongly at the poorer sites. The colloidal fraction of P in the soil solution equaled 38–47% of the total P load. Nitrogen input and liming also affected the Fe, Al, Ca, and Corg contents of the colloidal fraction.     

A FRAMEWORK FOR NATIONAL ASSESSMENT OF LAND DEGRADATION IN THE DRYLANDS: A CASE STUDY OF SOMALIA

Land degradation is a gradual, negative environmental process that is accelerated by human activities. Its gradual nature allows degradation to proceed unnoticed, thus reducing the likelihood of appropriate and timely control action. Presently, there are few practical frameworks to help countries design national strategies and policies for its control. The study presented here developed a framework for the national assessment of land degradation. This framework is envisaged to support governments in formulating policies on land degradation. It uses time‐series remote sensing data to identify the rate and extent of land degradation, local experts to identify prevalent degradation types and drivers of the degradation and field observations to validate the overall assessment. Its simplicity, use of freely downloadable input data and self‐triangulation of the assessment methods make it suitable for rapid assessment of land degradation on a national scale. It was tested in Somalia, where it exhibited accuracy greater than 60 per cent when assessing land degradation. This framework is relevant for designing national strategies and policies that address land degradation and provides an opportunity for accurate identification of areas to target with comprehensive local assessment. Testing of the framework in Somalia showed that about one‐third of the country was degraded because of loss of vegetation cover, topsoil loss and to the decline of soil moisture. Overgrazing, excessive tree cutting and poor agronomic practices in agricultural areas were identified as the primary drivers of the country's land degradation. These drivers are encouraged by the prevailing communal land tenure practices, poor governance and civil war. Copyright © 2011 John Wiley & Sons, Ltd.     

Application of spectral mixture modelling to the regional assessment of land degradation: A case study from basilicata,Italy

Mapping and monitoring of land degradation processes such as soil erosion has become an important task for both agricultural and environmental planners. The potential of using SPOT-HRV data for assessing the types of soil erosion and land degradation is obvious. The spectral information and the spatial resolution of the multispectral data allow a high accuracy in local mapping and rapid regional assessment. In Basilicata, southern Italy, spectral mixture modelling (end-member techniques) has been applied to extract relevant information for assessing soil erosion. This method allows an estimate of the proportion of surface cover types (end-members) within the pixel. From the data sets average spectral responses were extracted for growing vegetation, non-green sclerophylous vegetation mixed with dry grasses and bare soil. Using these spectra as end-members in the model, it was possible to decompose the spectral information of all pixels into the three surface components, giving the percentage cover of the three types within every pixel. Classification of the pixels according to the percentage of surface cover or bare soil allows an assessment of erosion or erosion risk.     

Soil Sealing: Quantifying Impacts on Soil Functions by a Geospatial Decision Support System

Soil sealing is considered among the most dangerous of land degradation processes on global, European and national scales. Despite important policy documents aiming to mitigate this soil threat, it currently shows no signs of abating, and current efforts often do not result in appropriate implementation of soil sealing mitigation in spatial planning, which represents the subject area governing soil sealing. In this paper, we show a spatial decision support system – based on a Geospatial Cyberinfrastructure – with the aim of applying it as an operational instrument aiming towards soil sealing mitigation. The system has the ambition to impact on those who take decision over soil sealing; typically, these are not agriculture experts but rather spatial planners. This tool, focusing on mitigating such crucial land degradation, allows the users – via the Web – to produce ‘what‐if’ land planning scenarios thanks to the ‘on‐the‐fly’ modelling engines. Therefore, integrated geospatial quantitative data and procedures may be directly and freely used by planners. The tool has been applied to and tested in an area in the South of Italy. Results from two applications are reported: one addressing municipal planning and the other on a more detailed spatial scale. Furthermore, results include quantification of rural fragmentation, loss of soil ecosystem services and an estimate of soil sealing evolution over time. The tool was developed with the help of end users and indirectly explores a change of paradigm where soil science and landscape/urban planning work together to provide operational instruments that may be adopted by local communities in addressing soil sealing issues with a proactive approach. Copyright © 2017 John Wiley & Sons, Ltd.     

Modelling soil erosion and sediment yield at a catchment scale: the case of Masinga catchment,Kenya

Development of improved soil erosion and sediment yield prediction technology is required to provide catchment stakeholders with the tools they need to evaluate the impact of various management strategies on soil loss and sediment yield in order to plan for the optimal use of the land. In this paper, a newly developed approach is presented to predict the sources of sediment reaching the stream network within Masinga, a large‐scale rural catchment in Kenya. The study applies the revised universal soil loss equation (RUSLE) and a developed hillslope sediment delivery distributed (HSDD) model embedded in a geographical information system (GIS). The HSDD model estimates the sediment delivery ratio (SDR) on a cell‐by‐cell basis using the concept of runoff travel time as a function of catchment characteristics. The model performance was verified by comparing predicted and measured plot runoff and sediment yield. The results show a fairly good relationship between predicted and measured sediment yield (R²=0·82). The predicted results show that the developed modelling approach can be used as a major tool to estimate spatial soil erosion and sediment yield at a catchment scale. Copyright © 2006 John Wiley & Sons, Ltd.