Horticultural Crop Assessment using Satellite Data(Coordinated Horticulture Assessment and Management using geo-informatics: CHAMAN)

1Mahalanobis National Crop Forecast Centre. DAC&FW, New Delhi2Space Applications Centre, ISRO, Ahmedabad,3Natinal Remote Sensing Centre and RRSCs,ISRO, Bengaluru4National Horticulture development Foundation, Nasik5North eastern Space Application Centre ,ISRO, Shillong6Department of Agriculture , cooperation and Farmers welfare

S. Mamatha1, B. K. Bhattacharya2, Uday Raj3, H P Sharma4, B K Handique5, Mamta Saxena6 & S S Ray1

Email: mamatha.ncfc@nic.in

Overview of CHAMAN Project

• Area assessment and production forecasting of 7 major horticulturalcrops in selected districts of major states.

• Geospatial Applications for Horticultural Development andManagement Planning.

• Detailed scientific field level studies for developing technology for cropidentification, yield modelling and disease assessment

Objectives

Objective 1. Crop Inventory

Crop type

Crop States

Fruit Banana AP, Gujarat, Karnataka, Maharashtra, TN

Mango AP, Bihar, Gujarat, Karnataka, Telangana, UP

Citrus AP, Gujarat, Punjab, Maharashtra, MP, Telangana

Vegetables Potato Bihar, Gujarat, Punjab, UP, WB

Onion Gujarat, Karnataka, Maharashtra, MP Tomato AP, Bihar, Karnataka, MP, Odisha,

Telangana, WB Spices Chilli AP, Karnataka, MP, Odisha, Telangana,

WB

Only major crop growing districts of these states are considered

Total 185 Districts

Satellite Data Used for Crop Inventory

Satellite Sensor Resolution

Spectral Bands used

Sets of data required at a time

Crops

Resourcesat-2

AWIFS 56m NIR and Red Single date/ Multi-Date Potato.56m NDVI product Fortnightly Potato

LISSIII 23.5m NIR, Red and Green

Single date/ Multi-Date Potato, Onion, Banana

LISSIV 5.8m NIR, Red and Green

Single date/ Multi-Date Onion, Chili, Tomato, Mango, Citrus

IRS-P5 Cartosat 1 2.5m PAN Single date Mango, Citrus Landsat 8 OLI 30m SWIR, NIR, Red,

Green and BlueSingle date/ Multi-Date Potato, Onion

Sentinel-2A MSI 10m NIR, Red, Green and Blue

Single date/ Multi-Date Potato, Onion, Chili, Tomato

• Pre Processing of satellite data• Ground truth data collection• Satellite Image Classification • Post-classification analysis • Quality evaluation and Accuracy assessment• Area Estimation• Map Preparation • Bhuvan Interface

General Methodology

ClassificationTechniques

Characteristics Classifiers Crop

Pixel – basedtechniques

Each pixel isassumed pure andtypically labeled asa single land useland cover type

Unsupervised (e.g. K-means, ISODATA);Supervised (e.g.Maximum Likelihood-MXL)

Onion, Chili, Potato and Banana

Object BasedTechniques

Geographicalobjects, instead ofindividual pixels arecompared to thebasic unit

Image segmentation anobject based imageanalysis techniques (e.g.E-cognition, ArcGIS/Imagine Objective)

Mango,Citrus andBanana

Potato Classification using AWiFS & Sentinel Data

Onion Classification using Sentinel Data

Tomato and Chilli Classification using LISS III/Sentinel/Landsat/LISS IV Data

Citrus orchards in LISS IV data in Hoshiyarpur, Punjab

Citrus orchards in LISS IV +Cartosat merged data in Bijapur, Karnataka

Mango orchards in LISS IV + Cartosat merged data in Saharanpur District, UP

Mango Orchards in LISS IV + Cartosat merged data in Sitapur, UP

Orchard Mapping using LISS IV/ LISS IV + Cartosat Data

Final Mango Orchards mapped for entire Sitapur district derived Mango Orchard area= 15440 ha

Classification Method

Derivedarea (ha)

*Reference area (ha)

Pixel based 12117

15389Object based 15387

BHUVAN Updated

15440

99_52_B_15 April 2013, LISS 4 FCC with Ground Truth points

Classified Mango orchards overlaid on LISS 4 FCC with Ground Truth points

IRS R-2 LISS-IV, Pixel based Classified output

IRS R-2 LISS-IV, Object based Classified output

Refined Classified Output by manual editing over BHUVAN image as a Basemap

MANGO ORCHARD – Sitapur district of Uttar Pradesh

CHAMAN in BHUVAN Geoportal

http://bhuvan-staging.nrsc.gov.in/projects/moa_chaman/

Mango Orchard of Sitapur District, Bhuvan-CHAMAN Portal

Scale: 1:5000

Scale: 1:15000

Deviation Analysis of Crop Statistics

CropsMBE ('000 ha)

RMSE ('000 ha)

IA (unit less)

ME (unit less)

r2 Number of data points

Citrus -2.64 4.64 0.92 0.76 0.87 9Mango -2.10 4.89 0.97 0.90 0.94 26Banana -3.56 7.26 0.84 0.61 0.82 9Onion -14.98 25.75 0.84 0.52 0.75 15Potato -0.06 6.47 0.98 0.91 0.91 44

Horticultural Development using Geospatial Technology

S.N. Component Activity

1 Site Suitability Introduction/expansion of Horticulture development activities inNorth Eastern States (One district in each state)

2 Post-HarvestInfrastructure

Assessing the potential for new cold storage sites for in Bihar andUP State

3Crop Intensification Understanding the scope of improving crop intensity through

horticulture in selected districts of Haryana and Madhya Pradesh

4 GIS database creation Characterization of orchards and GIS database creation ofvarious layers and uploading on Bhuvan platform

5 Orchard Rejuvenation Identifying plantations /orchards that needs Rejuvenation in oneDistrict in UP and One district of Karnataka/Gujarat/WB usingremote Sensing data

6 Aqua-horticulture Developing plans for promoting aqua-horticulture in 1 –2 districtsin Bihar and Odisha state

Perspective view of Jhum land clusters

Land Suitability Analysis for Mango Plantation in Nuzvid mandal, AP

Site Suitability Analysis for Horticulture Expansion in NER -States

Sl No State District Crop1 Arunachal

PradeshPapumpare Orange

2 Assam Goalpara Banana3 Manipur Senapati Pineapple4 Meghalaya Jaintia Hills Turmeric5 Mizoram Champhai Grape6 Nagaland Dimapur Pineapple7 Sikkim West Sikkim Cardamom8 Tripura West Tripura Banana

Geospatial Applications: Post-Harvest Infrastructure

Existing

Proposed

Geospatial Applications: Aqua-Horticulture

Category Area (Ha) Number

Area under Foxnut cultivation

339.6 109

Ponds under priority 1 99.0 47

Ponds under priority 2 102.9 33

LegendRoads

Railways

!( Priority1 Villages

# Priority2 Villages

Major Towns

District Boundary

Potential Wetlands Priority 2

Potential Wetlands Priority 1

Makhana Ponds

Not Potential Zones

Geospatial Applications: Orchard Rejuvenation

Potential Area Identification

Based on NDVI Change Based on Orchard Structure

Fallow Period 2015 Full Seasonal Fallow 2015

Number of monthsArea(ha)

2015 Rabi 2015 Kharif 2015 Summer1 month 82231 134075 768502 month 11412 36543 2342193 month 1637 6231 864254 month 24700

LegendAnnual Fallow

Built_up

Water

Taluk Boundary

Geospatial Applications: Crop Intensification, Bhiwani, Haryana

Precision Farming Study

Study Area: Karsul Village, Niphad Taluk, NasikData Collected: Ground Spectral, UAV, High Resolution Satellite, Crop and Soil ParametersActivity: Phenology Mapping, Variability Assessment, Crop and Soil Parameter Retrieval

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Temporal NDVI Profiles of Grapes with Varying Vigour Grape-Nov Fruit Pruning Low Vigour Grape-Nov Fruit pruning High Vigour

Figure 5: Temporal spectral profile of grapes with varying vigour identified by stacking monthly NDVI Landsat imagery of 2013-14, 2014-15 and 2015-16 for Karsul village, Niphad block, Nasik district

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Temporal NDVI Profiles of Grapes with Varying Phenology Grape Young Orchard Grape-Sept Fruit Pruning Low Vigour

Grape-Oct Fruit pruning High Vigour Grape-Nov Fruit pruning High Vigour

Oct Fruit PruningSept Fruit

Pruning

Nov Fruit PruningOct

Fruit PruningSept

Fruit Pruning

Nov Fruit Pruning

Figure 7: Temporal spectral profile of grapes with varying phenology identified by stacking monthly NDVI Landsat imagery of 2013-14, 2014-15 and 2015-16 for Karsul village, Niphad block, Nasik district

Summary

• For crops like Potato, Mango, Citrus and Banana use of remote sensing data forassessment have been feasible, but for other crops accuracy is still an issue, due toscattered and small fields, mixed cropping, multiple seasons and short duration.

• Yield estimation for horticultural crops, especially fruit crops, is a problem due tomultiple picking.

• However use of satellite data and geospatial tools has shown a great promise forhorticultural development, especially for infrastructure development andhorticultural expansion.

Acknowledgment

• Indian Space Research Organization (SAC, NRSC, NESAC)• Department of Agriculture, Cooperation & Farmers’ Welfare (Hort Div)• National Horticultural Research & Development Foundation• India Meteorological Department• State Horticulture Departments• ICAR:NRCG

Team Members1. M M Kimothi2. Seema Sehgal3. Shreya Roy4. Aditi Srivastava5. Niti Singh6. Gargi Upadhyay7. Moreshwar Karale

Thank you