JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Senthil Selvaradjou European Commission Updating traditional soil maps with DSM techniques DG JRC.

Slides:



Advertisements
Similar presentations
Innovation data collection: Advice from the Oslo Manual South East Asian Regional Workshop on Science, Technology and Innovation Statistics.
Advertisements

Digital Soil Mapping Future Directions in Europe
T-test Charmaine Bird.
Multiple Analysis of Variance – MANOVA
Phosphorus and Potassium. How is P managed? Key to managing soil and fertilizer P: Knowledge of whether or not the level of soil solution P is adequate.
Team Meeting #5, Great Lakes Protection Fund Grant A Phosphorus Soil Test Metric To Reduce Dissolved Phosphorus Loading to Lake Erie Heidelberg University.
Stoichiometry Applying equations to calculating quantities.
Asha Balakrishnan Vanessa Peña Bhavya Lal Task Leader November 5, 2011
Estimation A major purpose of statistics is to estimate some characteristics of a population. Take a sample from the population under study and Compute.
Chapter 9 Audit Sampling: An Application to Substantive Tests of Account Balances McGraw-Hill/Irwin ©2008 The McGraw-Hill Companies, All Rights Reserved.
An Overview of Today’s Class
Logo Certified Nutrient Management Planning7-1 Module 7: Manure Utilization By Hailin Zhang.
Quantitative Genetics
Chapter 9: Introduction to the t statistic
The Nitrogen Requirement and Use Efficiency of Sweet Sorghum Produced in Central Oklahoma. D. Brian Arnall, Chad B. Godsey, Danielle Bellmer, Ray Huhnke.
Lecture II-2: Probability Review
Experiences with WRB in the 1:250,000 mapping in Italy Institutional Framework and Soil Classification Systems Numerous authorities are active in many.
JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Senthil Selvaradjou European Commission Updating traditional soil maps with DSM techniques DG JRC F. Carré,
Behzod Abdullobekov Tajik Agrarian University August 16, 2012, Hungary.
What is Business Analysis Planning & Monitoring?
The Purpose of a Fertilizer is to Supply Nutrients.
Background Information : Projected prevalence of arthritis is expected to increase from 2.9 million to 6.5 million Canadians, a rise of 124% (Badley.
Plant tissue analysis for testing nutrients deficiency in Mango
880.P20 Winter 2006 Richard Kass Propagation of Errors Suppose we measure the branching fraction BR(Higgs  +  - ) using the number of produced Higgs.
Agronomic Spatial Variability and Resolution What is it? How do we describe it? What does it imply for precision management?
Statistical Techniques I EXST7005 Distribution of Sample Means.
Chapter 15 Data Analysis: Testing for Significant Differences.
CSE554AlignmentSlide 1 CSE 554 Lecture 5: Alignment Fall 2011.
RAILROAD COMMISSION OF TEXAS Stephanie Weidman Austin Regional Manager Oversight and Safety Division Pipeline Safety September 2015.
Making a curved line straight Data Transformation & Regression.
VARIANCE & STANDARD DEVIATION By Farrokh Alemi, Ph.D. This lecture is organized by Dr. Alemi and narrated by Yara Alemi. The lecture is based on the OpenIntro.
Biostatistics Class 6 Hypothesis Testing: One-Sample Inference 2/29/2000.
Virtual Academy for the Semi Arid Tropics Course on Insect Pests of Groundnut Module 5: Sorghum Plant Nutrition After completing this Lesson, you would.
Controlling for Common Method Variance in PLS Analysis: The Measured Latent Marker Variable Approach Wynne W. Chin Jason Bennett Thatcher Ryan T. Wright.
STATISTICS “CALCULATING DESCRIPTIVE STATISTICS –Measures of Dispersion” 4.0 Measures of Dispersion.
Dutch plan for finalising Hair software package Alterra – Wageningen University and Research Centre Roel Kruijne Working Group Meeting on Pesticide Statistics,
Regional Technical Forum Automated Conservation Voltage Reduction Protocol.
Household consumption survey
1 of 36 The EPA 7-Step DQO Process Step 6 - Specify Error Tolerances (60 minutes) (15 minute Morning Break) Presenter: Sebastian Tindall DQO Training Course.
1 3. M ODELING U NCERTAINTY IN C ONSTRUCTION Objective: To develop an understanding of the impact of uncertainty on the performance of a project, and to.
1 Blend Times in Stirred Tanks Reacting Flows - Lecture 9 Instructor: André Bakker © André Bakker (2006)
2.4 Measures of Variation Coach Bridges NOTES. What you should learn…. How to find the range of a data set How to find the range of a data set How to.
Statistics in Applied Science and Technology Chapter 10. Analysis of Variance.
Agronomic Spatial Variability and Resolution What is it? How do we describe it? What does it imply for precision management?
1 of 31 The EPA 7-Step DQO Process Step 6 - Specify Error Tolerances 60 minutes (15 minute Morning Break) Presenter: Sebastian Tindall DQO Training Course.
T tests comparing two means t tests comparing two means.
Hypothesis Testing. Suppose we believe the average systolic blood pressure of healthy adults is normally distributed with mean μ = 120 and variance σ.
May 2010 Understanding the NCDA&CS Plant Analysis Report NCDA&CS Agronomic Division Plant/Waste/Solution/Media Section.
1 of 48 The EPA 7-Step DQO Process Step 6 - Specify Error Tolerances 3:00 PM - 3:30 PM (30 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course.
Evaluation And Adjustment Of The 2008 Census Age & Sex Data.
Principal Components Analysis ( PCA)
Statistical Concepts Basic Principles An Overview of Today’s Class What: Inductive inference on characterizing a population Why : How will doing this allow.
IMPACT EVALUATION PBAF 526 Class 5, October 31, 2011.
CWR 6536 Stochastic Subsurface Hydrology Optimal Estimation of Hydrologic Parameters.
ENVIRONMENTALLY FRIENDLY POWER PLANTS
INTRODUCTORY STATISTICS FOR CRIMINAL JUSTICE
Writing a Formal Lab Report
Precision Agriculture an Overview
Precision Agriculture
Precision Agriculture an Overview
Overview of existing excretion factors
REMOTE SENSING Multispectral Image Classification
LDZ System Charges – Structure Methodology 26 July 2010
Network Screening & Diagnosis
A new way of looking at emission uncertainties
Evaluate the integral using integration by parts with the indicated choices of u and dv. {image} 1. {image} none of these
MAKING INCLUSIVE GROWTH HAPPEN IN REGIONS AND CITIES: Present and future developments for the metropolitan database SCORUS conference 16th - 17th June.
1 Chapter 8: Introduction to Hypothesis Testing. 2 Hypothesis Testing The general goal of a hypothesis test is to rule out chance (sampling error) as.
Indicator testing and evaluating
Evaluate the integral {image}
Presentation transcript:

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Senthil Selvaradjou European Commission Updating traditional soil maps with DSM techniques DG JRC

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Why is it important to be able to update traditional soil maps? Local knowledge on soils contained in traditional soil maps Usually, no associated guidelines on soil distribution rules Soil surveyors are now retiring and field expertise will be lost soon Due to lack of formalism of soil distribution, soil maps contain uncertainties which need to be removed

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Objectives Soil type map Extract the soil distribution rules Soil covariates (RS images, DEM…) Update the soil map Original soil type map New soil type map

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Two applications Updating potential soil erosion assessment Updating the Asian part of the FAO Soil Map (1988) Soil map Soil covariates New soil type map Soil erosion map (t o ) Soil covariates t o Soil covariates t 1 MODEL No change in time New soil erosion map (t 1 ) MODEL Change in time

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Methodology Based on the DRIS (Diagnosis Recommendation Integrated System) Approach (Beaufils, 1973) Purpose: to evaluate through indices the effect of each nutrient on the nutritional balance of the plant (agronomic issue) { 0 = excess} Premices (a) Ratios among nutrients are usually better indicators of nutrient deficiencies than isolated concentrations values (b) Some nutrient ratios are more important or significant than others (c) Maximum yield are only reached when important nutrient ratios are near the ideal or optimum values (obtained from high yielding-selected populations) (d) As a consequence, the variance of an important nutrient ratio is smaller in a high yielding (reference population) than in a low yielding populations and the relations between variances of high and low yielding populations can be used in the selection of significant nutrient ratios (e) The DRIS indices can be calculated individually, for each nutrient, using the average ratio deviation obtained from the comparison with the optimum value of a given nutrient ratio

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Methodology Main steps of DRIS Approach Dividing the population into two groups: high yield (reference population) and low yield Calculation of norms using the variance largest ratio among high and low yielding populations Calculation of nutrient indices based on the comparison between actual nutrient ratio and optimal nutrient ratios Consider 3 nutrients (A), (B) and (N) where Z =3 Mean ratios of the reference population

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. DRIS for updating soil erosion map

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. The original soil erosion map Soil Map of erosion of Tamil Nadu region (NBSS & LUP, 1997)

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Legend transformation

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. The nutrients equivalent Soil erosion is a function of

JRC Ispra - IES NCSS, 07/06/06Selvaradjou et al. Division of the population High yield ~ none to slight erosion {class 1} Low yield ~ From slight to severe erosion {classes 2 to 4}