• Aucun résultat trouvé

Very High Spatial Resolution in AGRICULTURE and expectations

N/A
N/A
Protected

Academic year: 2021

Partager "Very High Spatial Resolution in AGRICULTURE and expectations"

Copied!
13
0
0

Texte intégral

(1)

Very High Spatial Resolution in

AGRICULTURE

AGRICULTURE

and expectations

(2)

Specific issues in agriculture (1/4)

• Accurate identification of land use

 detailed mapping for spotting, detection, mapping, inventory, control…

 vineyards, orchards, olive, dry nuts groves, pine or poplar plantations

recognition…

 perennial crops (market-garden) distinction

 grass/waste/fallow-lands and crops discrimination

 grass/waste/fallow-lands and crops discrimination

• Crop monitoring and precision farming

eg. adapted to tree crops & market-garden crops + accidents

(3)

Structured crops (orchards, vineyards,…)

Quickbird – 2.8 m SPOT - 10 m Quickbird - 0.7 m

(4)

Specific issues in agriculture (2/4)

SPOT – 2.5m GEOEYE – 0.5m

•Agricultural practices

Cropping systems evaluation, GAECs control

(ploughing directions, stubbles burning, mechanization…)

(5)

Specific issues in agriculture (3/4)

• Fine characterization of soils

(intraplot variability/heterogeneity)

Soil organic content heterogeneity

SPOT - 2,5m WorldView - 2m SPOT - 20m

(6)

Specific issues in agriculture (4/4)

SPOT – 10m SPOT – 2.5m

Spotting and characterization of landscape elements

hedges, small woody elements, grass strips, etc…

for CAP, "Grenelle-Environnement", biodiversity, hydrological models

(7)

What have been analyzed so far ?

Evaluation of X-band radar for the agricultural control over 4 sites, H. Kerdilès, O. Léo, AGRIFISH/MARS-PAC, JRC.

Detecting ineligible features and potentially incorrect LPIS boundaries, H. Kerdilès, O. Léo, AGRIFISH/MARS-PAC/JRC.

SPOT-FORMOSAT 8-20m temporal complementarity with VHSR (0.70-2.5m) for land cover monitoring, C. Marais-Sicre, D. Ducrot, CESBIO

Detection, segmentation, and classification of tree crops in optical VHSR images (St Gilles/Gard), C. Lelong, TETIS/CIRAD

Tropical tree plantations characterization(Costa Rica, Brazil), G. Lemaire, Eco&Sols/CIRAD

Structure indicators of tropical agroforestry systems, C. Lelong, TETIS/CIRAD

Structure indicators of tropical agroforestry systems, C. Lelong, TETIS/CIRAD

Sugar cane yield and intraplot heterogeneity (Île de la Réunion), A. Bégué, TETIS/CIRAD

Agriculture monitoring with X-band radar remote sensing, F. Baup, CESBIO

Soil spatial variability mapping (Boigneville/Beauce, Villamblain), B. DeSolan, ARVALIS

Soil hydric status and rugosity mapping based on optical and radar VHSR images (Villamblain), N. Zribi, CETP/BRGM, N. Baghdadi, TETIS/Cemagref

Soil organic carbon concentration estimation(Plaine de Versailles, Plateau des Alluets), E. Vaudour, Agroparistech 3D-characterization of the lanscape elements(Avignon/Vaucluse), INRA avignon

Agri-enrivonmental measures (plot limits, winter cover, spatiotemporal sonstraints on grass strips, Wallonie), D.

Buffet, CRA –W

Small wood elements and grass strips extraction in agri-forested landscapes, D. Sheeren, F. Collard, Dynafor/ENSAT

(8)

What comes out of the different

explorations ?

Traditionnal remote sensing methodologies

are not suitable anymore

Availability of a much higher amount of information

(scale of objects and purity of associated signal)

accompanied by a higher amount of perturbations and complications

(large spectral heterogeneity & spatial incoherence)

are not suitable anymore

Specific needs for new algorithms and tools

and more time to generalize and operationalize the methods

Examples of tested orientations:

Object-based cognitive approaches

Higher level of classification algorithms (SVM, NN, Markov

chains, waveletts …)

(9)

Perspectives of use of vhsr in agriculture

1. Assistance for crops/resources management

(precision farming) and

production systems valuation

2. Landscape Ecology and Agri-environment

2. Landscape Ecology and Agri-environment

(biodiversity management, ecosystemic services

characterization...)

3. Management and control of agricultural and

agri-environmental aids

(10)

Perspectives of use of vhsr in agriculture

1. Assistance for crops/resources management

(precision farming) and

production systems valuation

1.1 Crops mapping and species identification

1.2 Parcels area estimation 1.2 Parcels area estimation

1.3 Agricultural practices monitoring 1.4 Cropping systems valuation 1.5 Irrigated areas

1.6 Crop vitality (diagnostic)

1.7 Quantitative approach (eg: nitric status) 1.8 Quality approach (eg: proteins rate)

1.9 Agro climatic accidents impact on crops, fierce changes 1.10 Soil structure

1.11 Soil condition at surface 1.12 Soil moisture

(11)

Perspectives of use of vhsr in agriculture

2. Landscape Ecology and Agri-environment

2. Landscape Ecology and Agri-environment

(biodiversity management, ecosystemic services

characterization...)

2.1 Landscape composition, structure, organization, and dynamics 2.2 Damage assessment (area + intensity)

(12)

Perspectives of use of vhsr in agriculture

3. Management and control of agricultural and

agri-environmental aids

3.1 Parcels localisation 3.2 Area measurements

3.3 Crops species sorting (in subvention groups) 3.4 Census and density

3.5 Agri-agroenvironmental mesures control 3.6 Cross compliance control (GAECs)

(13)

Références

Documents relatifs

Department of Physics, Faculty of Science, Benha University, Benha, 13518, Egypt In this paper, we compare the quantum corrections to the Schwarzschild black hole temperature due

Spatial modelling of weeds and crop growth in century-old charcoal kiln sites with integration of high and very high resolution remote sensing.. University of Liege – Arlon

Nous avons étu- dié parallèlement les propriétés d’une couche mince de MnAs/GaAs(001) et d’une couche de clusters de MnAs dans une matrice de GaAs (GaAs:MnAs), ainsi que le

For lower redshifts and large scales, aside from giving us clues as to how fresh matter is funnelled into galaxies and galaxy clusters to sustain their star formation activity

Our systematic styled review compares fragmentation in industrial oil palm (IOP) and smallholder agroforestry (SH) landscapes, and how this influences biodiversity (soil fauna,

The understanding of the main factors driving the chemistry of soil solutions led therefore to a simplification of fertilization regimes over huge areas of eucalypt plantations on

Instead, we computed individual values –for tree diversity and aboveground carbon–for each 20 × 20 m plot (12 plots each for young and old secondary regrowth areas and rubber

Seven landscape attributes (Table 2) were derived from the land-cover vegetation map, and calculated for the 98 ponds of the study area: the pond surface, the pond loca- tion (inside