A new approach for zoning irregularly-spaced, within-field data

Autor: Anthony Clenet, Corentin Leroux, Bruno Tisseyre, Hazaël Jones
Přispěvatelé: SMAG MONTPELLIER FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
0106 biological sciences
Engineering
IMAGE PROCESSING
MANAGEMENT ZONES
SEEDED REGION GROWING AND MERGING ALGORITHM
Image processing
VARIABLE RATE FERTILIZATION
Horticulture
computer.software_genre
01 natural sciences
SEGMENTATION ALGORITHMS
Domain (software engineering)
PRECISION AGRICULTURE
VARIABLE-RATE FERTILIZATION
FERTILIZER APPLICATION
MERGING ALGORITHMS
Segmentation
Technical management
LAND MANAGEMENT
MERGING
FIELD METHOD
Cluster analysis
TECHNICAL CONSTRAINTS
2. Zero hunger
IMAGE SEGMENTATION
SOIL SURVEYS
business.industry
Forestry
EXPERIMENTAL STUDY
04 agricultural and veterinary sciences
15. Life on land
Computer Science Applications
IRREGULARLY DISTRIBUTED SPATIAL DATA
CLUSTERING ALGORITHMS
SITE SPECIFIC MANAGEMENT
Region growing
GROWING SEASON
[SDE]Environmental Sciences
040103 agronomy & agriculture
0401 agriculture
forestry
and fisheries
MACHINERY
Precision agriculture
Data mining
business
Voronoi diagram
Agronomy and Crop Science
computer
METHODOLOGY
010606 plant biology & botany
Zdroj: Computers and Electronics in Agriculture
Computers and Electronics in Agriculture, Elsevier, 2017, 141, pp.196-206. ⟨10.1016/j.compag.2017.07.025⟩
ISSN: 0168-1699
DOI: 10.1016/j.compag.2017.07.025⟩
Popis: International audience; Management zones can be defined as homogeneous regions for which specific management decisions are to be considered. The delineation of these management units is important because it enables or at least facilitate growers and practitioners performing site specific management. The delineation of management zones has essentially been performed by (i) clustering techniques or (ii) segmentation algorithms arising from the image processing domain. However, the first approach does not take into account the spatial relationships in the data, and is prone to generate a large number of fragmented zones while he second methodology has only been dedicated to regularly-spaced, within-field data. This work proposes a new approach to generate contiguous management zones from irregularly-spaced within-field observations, e.g. within-field yield, soil conductivity, soil samples, which are a very important source of data in precision agriculture studies. A seeded region growing and merging algorithm has been specifically designed for these irregularly-spaced observations. More specifically, a Voronoi tessellation was implemented to define spatial relationships between neighbouring observations. Seeds were automatically placed at specific locations across the fields and management zones were first expanded from these seeds. The merging procedure aimed at generating more manageable and interpretable zones. The merging algorithm was defined in a way that made it possible to incorporate machinery and technical management constraints. Experiments demonstrated that the proposed methodology was able to generate relatively compact and contiguous management zones. Furthermore, machinery and technical constraints were shown to significantly influence the results of the delineation which proved the importance of accounting for these considerations.
Databáze: OpenAIRE
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