Layers Documentation
Index:
Introduction
What is Layers?
¿A quién está dirigida esta documentación?
How to use this documentation
Data Sources
Field Parameters Information and Management
Spatially and Temporally Discrete Information
Field Samples
Spatially Discrete and Temporally Continuous Information
Meteorology
Remote Sensing: Low Spatial Resolution and High Temporal Resolution
Satellite: Sentinel-1
Satellite: Sentinel-2
Satellite: Landsat 8-9
Satellite: Planet
Remote Sensing: High Spatial Resolution and Low Temporal Resolution
Access Layers
Users and roles
Create a client account
AGROMOM Access
Client creation
CROP MASTER
What is
CROP MASTER
?
Why
CROP MASTER
?
Resources at your disposal
The value of recognition
Products
SatTech2.0
Product Objective
Information Sources
Frequency
Layers
RGB
Vegetative Vigor (NDVI, LUVI)
Vegetative Moisture (NDMI)
Nitrogen-Chlorophyll (NDRE)
Soil Texture
Digital Elevation Model 2010-2015
Crop Growth
Historical productive potential (NDVI)
Water stress (LWS)
Wee
Error
Combined use of Layers for sampling point selection
Automatic Alert Report
Automatic Alert Variability Report
PredTech
Input data to the model
Customer data (real data)
Spectral data + radar
Spectral + radar data (temporal)
Climatological data
Agro-climatic
Processed climatological and agro-climatic data
Data Review
Model generation
Generation of predictions
Gaps
Soil
SoilTech Objective
Uses of SoilTech
SoilTech includes
Physical and nutritional parameters analyzed by SoilTech
Laboratory Data Required for SoilTech
SoilTech Options and Features
Basic
Satellite Guidance
Soil
Additional information about the analyzed parameters
Hydrogen Potential (pH)
Organic Matter
Cation Exchange Capacity (CEC)
Nitrogen
Match
Potass
Other nutrients present in the soil
DroneT
TraceTech
Product Objective
Information sources
Using the application
Types of users and their actions
Trace View
Step visualization
Creating trace
Step creation
Offline
Agronomist Library
Layers web
User menu
Search bar
Tools
Global Layers
Report system
Progress Excel
Download geometry JSON
Map
Creating plots
Plot selection and visualization
Plot view
Plot editing
Data visualization by date and type
Layer visualization
Drone deliverables download
Samples
File Generator
Dashboard
Client Overview
Temporal evolution
Thermal storage
Harvest planning tool
Harvest prediction tool
Layers app
Download and installation
Login
Main menu
Installments
Sample and Gauging Records
Traffic count methodology
Required material for nutritional capacity measurements
Offline Mode: Final Considerations
Reports in the
Layers
application
List of Reports
Filter Reports by current season/all
Open/close multiple Reports
Creating plots
BI Labs
Pilot Library
Agromom
Maintenances and Operations Management
Pre-flight
Creation of pre-flight agromom journey
Steps to follow for creating a workday in agromom
Post-flight
Hemav Link
What is HEMAV link?
Hemav Link Download
Sign in
Match day selection
Upload images
Upload complete
First-use problems
Common Problems
Uncommon problems
Protocols
Sampling
Methodology for crop sampling in sugar beet
Protocol for sampling in sugar beet
Soybean gauging methodology
Hemav Traffic Analytics
App
Measurement methodology
Required materials for nutritional assessment
Capacity for PRODUCTION AND QUALITY
Equipment required for production and quality gauging
Final considerations
Traffic count methodology for sugarcane
1. Objetivo
2. Muestreos
3. Características del muestreo
4. Material Necesario
5. Identificación de las zonas a muestrear
6. Insertar AFORO de PRODUCCIÓN en APP HEMAV
7. Insertar AFORO de CALIDAD en APP HEMAV
8. Toma de muestras
9. Valores de referencia para los aforos
9. Referencias
Instructions for collecting leaf samples in sugar cane
Material
**Procedure
Guidelines for use app to take samples
Create soil samples
Locate samples previously created with app
Offline mode
FAQ
Fertilization
Background fertilization correction protocol with soil samples
Objective
Minimum fertilization requirements
Minimum CAPACITY Requirements
Steps to fill in the data in the AFOROS APP
Top and Base Fertilization - Generic
Objective
TOP DRESSING FERTILIZATION
BACKGROUND PAYMENT
SUBSCRIBER - MULTI-PLOT
Topdressing fertilization for soybeans
1. Objetivo
2. Satélite
3. Dron
4. Correciones según clase
5. Momento óptimo para la realización de coberteras
Topdressing fertilization for sugarcane
1. Objetivo
2. Satélite
3. Dron
4. Correciones según clase
Flight Procedures
Flight Procedures
Best Practices for Flying Over Large Plots
About calibration plates
Other protocols
Basic Nitrogen Management in Sugar Beet
Objective
1. Selección de campos en Layers
2. Acceso al panel de nitrógeno
3. Descarga de ficheros: Shape y PDF
Advanced Nitrogen Management in Sugar Beet
Objective
1. Selección de campos en layers
2. Acceso al panel de Evolución Nitrógeno (Dashboard)
3. Distribución nitrógeno en la parcela
Protocol and basic concepts for data collection with SOILXPLORER (Soil mapping sensor)
Objective
NDVI variable deliverable
Objective
Delivery collection
API
1. API end points
Users
Fields
Seasons
Snapshots
Reports
Postman collection
2. HEMAV DB Organization
3. Workflows
3.1. Customer & field creation
3.2. Update season information and creating new season
3.3. Extracting HEMAV DB information
3.3.1. Sat-tech, Planet, Landsat9 and drone-tech. Snapshot sources.
3.3.2. Weather, Irrigation and Pred-tech. SeasonLog types.
4. Season requirements and limitations
4.1. Fields
4.2. Seasons
4.3. Geometries
4.4. Season parameters
5. Step by step - Creating and updating season information
5.1. Get ApiKey
5.2. Authorize
5.3. Get information of all your customers
5.4. Create a field
5.5. Check field season information
5.6. Update season
6. Extracting information
6.1. Sat-tech, Planet, Landsat9 and drone-tech. Snapshot sources.
6.2. SeasonLog types. Weather, Irrigation and Pred-tech.
Frequently Asked Questions
WEB Layers
It seems there is a misalignment or a missing button
Map viewer
Geometries
Satellite
Report Generator
SAR
Dashboard
Satellite
Drone
References
Artificial intelligence and computer vision
Earth observation and remote sensing
SAR
What is SAR?
SAR in agriculture
Information Sources
Sentinel 1
Layers Documentation
References
Artificial intelligence and computer vision
View page source
Artificial intelligence and computer vision
Layers
Español
Languages
Español
English
Português