Using Satellite Imagery for Variable Rate Maps Curtis Dick.

Slides:

Advertisements

Similar presentations

Advertisements

MnGeo Statewide Geospatial Advisory Council Hot Topics May 30, 2012 Drones, UAV’s, UAS’s.

Unit Five Review: Agriculture

Types of Agriculture LEARNING OBJECTIVES

What is the purpose of this presentation? n Provide a better understanding of site specific yield information and the value that it can bring to your.

Crop Science 6 Fall Crop Science 6 Fall 2004 What is Precision Agriculture?? The practice of managing specific field areas based on variability.

Change analysis of Northborough, Massachusetts, Kristopher Kuzera and Silvia Petrova 1987 LANDSAT TM – 30m resolution False Color Composite Bands.

Sparse Versus Dense Spatial Data R.L. (Bob) Nielsen Professor of Agronomy Purdue University West Lafayette, IN Web:

Some Significant Current Projects. Landsat Multispectral Scanner (MSS) and Landsat Thematic Mapper (TM) Sensor System Characteristics.

Echelon – Who Are We? Echelon was an independent agricultural management consulting firm based out of Weyburn, SK Echelon joined the CPS family on Oct.

Use of Multispectral Imagery for Variable Rate “Application-zone” Identification in Cotton Production Tim Sharp Beltwide Cotton Conference January 6-10,

Relationships Between NDVI and Plant Physical Measurements Beltwide Cotton Conference January 6-10, 2003 Tim Sharp.

GreenSeekerTM Variable Rate Applicator Equipment and Applications

Site-Specific Management Factors influencing plant growth Water Light Temperature Soil Compaction Drainage.

2014 Agronomy Seedsmanship Conference Precision Farming Technologies Overview Dr. Brian Arnall Oklahoma State University.

What is Precision Agriculture?

Types of Agriculture and Farming Practices

Digital Numbers The Remote Sensing world calls cell values are also called a digital number or DN. In most of the imagery we work with the DN represents.

Conversion of Forestland to Agriculture in Hubbard County, Minnesota By: Henry Rodman Cory Kimball 2013.

Agriculture as a system. Types of industry There are four main types of industry and these can be classified as: 1.PRIMARY INDUSTRY – this is the extraction.

Challenges to sensor- based N-Management for Cotton E.M. Barnes 1, T. Sharp 2, J. Wilkerson 3, Randy Taylor 2, Stacy Worley 3 1 Cotton Incorporated, Cary.

Tracking impacts of 2012 droughts on crop condition through daily satellite observations Currently droughts are affecting production in multiple main agricultural.

Realities of Satellite Interpretation (The things that will drive you crazy!) Rachel M.K. Headley, PhD USGS Landsat Project.

3-Year Results of Total Farm Management with Precision Ag Technologies Sharp T., Evans G., and Salvador A. Jackson State Community College – Jackson Tennessee.

AZ State Technical Committee Meeting September 7 th, 2011.

VARIABLES Notes.  Are factors that change  There are 3 variables in an experiment:  Manipulated (independent)  Responding (dependent)  Controlling.

UTILIZATION OF CROP SENSORS TO DETECT COTTON GROWTH AND N NUTRITION

Precision Farming System Tim Sharp Jackson State College Jackson, TN.

Map of the Great Divide Basin, Wyoming, created using a neural network and used to find likely fossil beds See:

The Glory of the farmer is that, in the division of labors, it’s his part to create. Emerson Help farmers make some money, and they will share it with.

ClimateEngine.org CLOUD COMPUTING AND VISUALIZATION OF CLIMATE AND REMOTE SENSING DATA ClimateEngine.org team, Desert Research Institute / University of.

© Phil Hurvitz, Introduction to Geographic Information Systems and their Potential Uses as Management Tools in Commercial Shellfish Farming Introduction.

In the rural areas of Kentucky, agriculture is how many families earn income. Due to Marion County’s fertile soil, you will see fields of crops each year.

Soil as a Resource Key idea: Soil is an important resource that can be conserved and protected.

Satellite Imagery for Agronomic Management Decisions.

State of Engineering in Precision Agriculture, Boundaries and Limits for Agronomy.

February 21, 2006 Lab Dan Kurz & Matt Chyba Team 4.

Precision Agriculture an Overview. Precision Agriculture? Human need Environment –Hypoxia –$750,000,000 (excess N flowing down the Mississippi river/yr)

Casey Andrews SOIL 4213 April 22, 2009

Agronomic Spatial Variability and Resolution Resolution for Sensing/Soil Sampling And Yield Measurements.

Weekly NDVI Relationships to Height, Nodes and Productivity Index for Low, Medium, and High Cotton Productivity Zones T. Sharp, G. Evans and A. Salvador.

By Jeremy R. Smith University of North Dakota April 30, 2012.

Precision Ag in Cotton Clint Sharp. Use NDVI to Map “Vigor Zones” We map Vigor Zones, not yield zones. –Can be done with Aircraft or GreenSeeker –Vigor.

Camera Pod Mounted on Cessna 172. Using Landsat TM Imagery to Predict Wheat Yield and to Define Management Zones.

Precision Ag in Horticulture A growing Trend Mal Frick.

Cost/Return Analysis of Precision Agriculture on Oklahoma Farms Aaron Witt April 25, 2001.

Utilizing Landsat TM and Forest Service Aerial Survey Data for Mapping Mountain Pine Beetle Outbreak in Medicine Bow National Forest, WY UW Undergraduate.

Weather Cloud Detection

Mapping Variations in Crop Growth Using Satellite Data

Using vegetation indices (NDVI) to study vegetation

Precision Agriculture in Cotton Production

Fly Expertly. Detect Truthfully. Perform Consistently.

What is Precision Agriculture?

Unmanned Aircraft Systems in Agriculture

Mapping wheat growth in dryland fields in SE Wyoming using Landsat images Matthew Thoman.

Hui Wang1,2*, Anders K. Mortensen1 and René Gislum1

Precision Agriculture an Overview

Precision Agriculture

Precision Agriculture an Overview

Redball NUE Conference August 9, 2007

Konstantin Ivushkin1, Harm Bartholomeus1, Arnold K

Management Zones Starr Holtz SOIL 4213 April 26, 2006.

Summary Probability of a cloud free image no more than 16 and 32 days apart during the growing season Still using a fixed growing season April 1st to Oct.

Structure of Images Images could be: Pictures in the head

By Blake Balzan1, with Ramesh Sivanpillai PhD2

Photography for DUS test

UNL Algorithm for N in Corn

Precision Ag Precision agriculture (PA) refers to using information, computing and sensing technologies for production agriculture. PA application enables.

Agricultural Intelligence From Satellite Imagery

Presentation transcript:

Using Satellite Imagery for Variable Rate Maps Curtis Dick

What Satellite Imagery is useful for Designating Management Zones Building Variable Rate Maps Helping Identify Problems in Growing fields Help identifying where to soil sample Measuring Biomass

Satellite Imagery Technology Agri-ImiGIS ▫Started in 1994 in North Dakota by providing satellite images for a variety of farming applications ▫Currently provide 2 types of images (both have NDVI capabilities) ▫Main use is for building management zones ▫Also provide products that allows producers to have access to the system via an app ▫The products allow for soil sampling and other practices to be tied into the imagery into a browser base

Landsat vs. Rapid Eye LandsatRapid Eye

Major Uses in Oklahoma A very successful use in Oklahoma has been with variable rate Growth Regulator in Cotton Production The Images allow a producer or consultant to see the differences in a growing field Landsat is updated every 16 days no matter if there is cloud cover or not Rapid Eye takes 4-5 pictures during a growing season and will stay in an area until it gets a clear picture

Hard to tell in a growing field the amount of an input certain plants need

Drones Around 140 different type of drones available for use Prices range from $100,000 to $12,800 As of right now primary purpose is for surveillance

senseFly Switzerland based company that produces two types of Drones ▫Swinglet CAM ▫eBee

Are Drones Useful? AdvantagesDisadvantages Are very easy to operate Does not matter if it is cloudy Can have an image of a field in 1 day Do not fly well in winds over 25 mph Are somewhat costly If drones are being used commercially they can not be flown over 400 ft elevation in U.S.

Using Drones for Mapping NDVI Vs Green Seeker Swinglet Cam /crop-protection/drone-plane- your-future-0http://farmindustrynews.com /crop-protection/drone-plane- your-future-0 Green Seeker

Review Best use of satellite imagery seems to be to measure biomass Satellite imagery is a useful tool in developing management zones, but should probably not be the only information the zones are based off of. Drones for commercial purposes must be flown below 400ft.

Questions?