geospatial activities at icrisat - cgiar-csi...geospatial activities at icrisatmurali krishna gumma...

Geospatial activities at ICRISAT

Murali Krishna GummaHead – RS/GIS UnitSenior Scientist - Geospatial Science

Big Data in AgricultureConvention

19th – 22th September 2017CIAT HQ Major crops (2014)

01. Rainfed-sc-sorghum

02. Rainfed-sc-millets/sorghum

03. Rainfed-sc-groundnut

04. Rainfed-sc-pigeonpea

05. Rainfed-SC-maize/sorghum/millet

06. Other crops

Overview

• Geospatial activities

• Key products

• Mobile application for Ground data

• Publications

Geospatial products for SAT

Target Research groups• Breeders• System modelers• Social scientists• Hydrologists• Planning departments

Crop type / intensity maps

Land use changes

Tracking adoption of NRM Technologies

Spatial modeling(Prioritization)

Simulated yield estimations and impact

Abiotic stresses

Impact assessment

Length of growing periods

Water productivity

GFSAD 30m project

Major goal is to produce high resolution (30-m) global cropland products, including:

• Cropland Vs Non croplands

• Irrigated Vs rainfed (including water bodies)

• Cropping intensities: single, double, continuous

• Global major crop types

• Cropland change

Overview: Mapping @ 30m Resolutions

CountryTotal

geographical area ('000 ha)

Bangladesh 14,804

Bhutan 4,365

India 345,623

Nepal 16,210

Pakistan 89,167

Sri Lanka 6,453

Iran 164,820

Afghanistan 64,750

Total 706,192

Background: Croplands of South Asia

• Geographical area: 706 Mha

• Population: 1.7 billion

• Croplands: 254 Mha

• GDP 7.7 (agriculture 19%)

• Major crops: rice, maize, wheat, barley,

pulses and Plantations (coffee, tea and etc)

CountryTotal

geographical area ('000 ha)

Total gross planted

area ('000ha)

Bangladesh 14,804 15002

Bhutan 4,365 121

India 345,623 184443

Nepal 16,210 4208

Pakistan 89,167 22817

Sri Lanka 6,453 2076

Iran 164,820 18130

Afghanistan 64,750 7770

Total 706,192 254,568

Methodology Flow-chart: Random Forest Classification

Seasonal 30m products

Season1: Jun – Oct

Season2: Nov – Feb

Season3: Feb -Apr

Image

segmentations

Landsat-8 16 daytime series data

Input Bands

(N=8)

Band1:blue

Band2:

Band3:

Band4:

Band5:

Band6:

Band7:

Random Forest Algorithms (RF)

Cropland classification (pixel based)

Ground data

• Field work during 2013-16• Validation datasets

(Thenkabail et al 2005; Gumma et al 2011, 2016)

*All samples were visualassessed using Google Earthhigh resolution imagery

Satellite image composition

Agro-ecological

zones

Cropland classification &image segmentation

Training data

Validation data

Cropland products

1. Croplands Vs non croplands

2. Irrigated Vs Rainfed croplands

Characteristics of Satellite data used for South Asia

Croplands of South Asia using Google Earth Engine (GEE) Cloud Computing

@ 30-m Resolution based on Landsat 16-day Time-Series

Region/ Country

Landsat image Series

Years of

Data

# Composites

Bands percomposite

Total # bands used

South Asia,Iran and

AfghanistanLS8

2014&

2015

Monsoon (151 – 300)

Winter (301-365,1-60)

Summer (61-150)

blue, green, red, NIR, SWIR1, temp, SWIR2 and NDVI (n= 8)

48



• Field work during 2013-16• Validation datasets

(Thenkabail et al 2005; Gumma et al 2011, 2016)

*All samples were visualassessed using GoogleEarth high resolutionimagery

Product 1: Cropland Vs Non-cropland

Sample size = 2088

Crop lands = 1204Non croplands = 884



Accuracy assessment: Cropland Vs Non-cropland

Land use / land cover01.

Croplands

02. Non-croplands

(Other LULC)

Row

TotalCommission

error

01. Croplands 615 32 647 4.9%

02. Non-croplands (Other

LULC) 40 76 116 34.5%

Omission error 6.1% 29.6%

Producers accuracy 93.9% 70.4%

Users accuracy 95.1% 65.5%

Overall Accuracy 90.56%

Kappa 0.623

Product 2: Irirgated Vs Rainfed cropland

Sample size = 2634Irrigated croplands = 1099 Rainfed= 651Non croplands = 884



Product 2: Irirgated Vs Rainfed cropland

Accuracy assessment: Irirgated Vs Rainfed cropland

Land use / land cover01. Irrigated-

croplands

02.

Rainfed-

croplands

03. other

LULC

04.

Waterb

odies

Row Total Commissi

on error

01. Irrigated-croplands 386 35 4 0 425 9.2%

02. Rainfed-croplands 56 218 4 0 278 21.6%

03. other LULC 27 20 32 0 79 59.5%

04. Waterbodies 2 1 0 2 5 60.0%

Omission error 18% 20% 20% 0%

Producers accuracy 81.95% 79.56% 80.00% 100%

Users accuracy 90.82% 78.42% 40.51% 40%

Overall Accuracy 81.07%

Kappa 0.655

Comparison : 1km, 250m, 30m and High resolution imagery

1-km Product 250-m Product 30-m Product High resolution image

Ganges river basin

Krishna river basin

Comparison : LANDSAT 30m (X-axis) Vs NAS (Y-axis)

Reference Data

Crop No-Crop Total User Accuracy

Map

Dat

a Crop 42 32 74 56.76%

No-Crop 17 159 176 90.34%

Total 59 191 250

Producer Accuracy 71.19% 83.25% 80.40%

Reference Data


Map

Dat

a Crop 4 3 7 57.14%

No-Crop 8 235 243 96.71%

Total 12 238 250


Reference Data


Map

Dat

a Crop 111 19 130 85.38%

No-Crop 40 80 120 66.67%

Total 151 99 250


Reference Data


Map

Dat

a Crop 140 18 158 88.61%

No-Crop 24 67 91 73.63%

Total 164 85 249


Zone 1

Zone 2

Zone 3

Zone 4

Total land area of Zone 1 (TLAZ1): 159.6 MhaCropland as % of TLAZ1: 22.26 %Total net cropland area of SAsia (TCASA) = 262.47 MhaCropland as % of TCASA : 13.54 %




Accuracy assessment: Error Matrix

Reference Data


Map

Dat

a Crop 104 17 121 85.95%

No-Crop 36 92 128 71.88%

Total 140 109 249


Reference Data


Map

Dat

a Crop 15 3 18 83.33%

No-Crop 16 216 232 93.10%

Total 31 219 250


Reference Data


Map

Dat

a Crop 418 92 510 81.96%

No-Crop 141 849 990 85.76%

Total 559 941 1,500


Zone 5

Zone 6

All Zones Overall Error Matrix



Accuracy assessment: Error Matrix

Rice-fallows: South Asia

Legend

01. Irrigated-SC-rice in kharif-fallow in rabi-fallow in summer

06. Rainfed-SC-rice in kharif-fallow in rabi-fallow in summer

Rice-rice/othercrops

Product 5: Rice-fallows (rainfed agriculture)

StateRainfed:

rice-fallows

% of total rice-fallow

Chhattisgarh 4111731 35.2%

Madhya Pradesh 1871816 16.0%

Orissa 1793852 15.3%

Jharkhand 975780 8.3%

Maharashtra 664907 5.7%

West Bengal 605092 5.2%

Telangana 407943 3.5%

Assam 302036 2.6%

Bihar 266314 2.3%

Karnataka 235265 2.0%

Gujarat 168620 1.4%

Andhra Pradesh 95469 0.8%

11,498,823 98%

Gumma et al., (2016)Accuracy 80%

Baseline Scenario @ present

New Scenario with Improved water Productivity and less water consuming crops

Season 1

Season 1

Season 2

Season 2

Total area of croplands, season 1 (TAC) = 47,696 ha Total area of croplands, season

2 (TAC) = 33,864 ha

Total area of croplands, season 1 (TAC) = 47,696 ha

Total area of croplands, season 2 (TAC) = 37,231 ha

Croplands (%)

01. Rice (71)

02. Pulses (20)

03. Corn (3)

04. Onions (0)

05. Cropland fallow (6)

06. Other LULC

Telangana_dist

Croplands (%)

01. Rice (68)

02. Pulses (0)

03. Corn (3)

04. Onions (0)


06. Other LULC

Telangana_dist

Croplands (%)

01. Rice (46)

02. Pulses (36)

03. Corn (14)

04. Onions (0)


06. Other LULC

Telangana_dist

Croplands (%)

01. Rice (19)

02. Pulses (17)

03. Corn (28)

04. Onions (15)


06. Other LULC

Telangana_dist

Crop production and water use – Kadam command area

Table A. Kaddam water use in: (A) baseline scenario, and (B) New scenario of improved water productivity and re-allocation of crops

Crop type

Percent of total

cropland area

in season 1A,C

(%)

Percent of total

cropland area in

season 2A,C

(%)

Water used for

producing 1 kg of

grainE,F

(liters)

Yield per

hectares in

(kg/hectare)

Total water used

by all crops in 2

season (liters)

Rice 71 68 3400 2500 483579280000

Pulses 20 0 1608 1320 20247524352

corn 3 3 1222 6500 19434932400

onions 0 0 345 19000 0

Cropland fallow 6 29 100 0 0

Total Area of croplands (hectares) 47696 33864 532,262 billion liters

Other land cover area (hectares) 8910 22742 Current water use 523 billion litersTotal area (croplands + non-croplands) (hectares) 56606 56606

Rice 46 19 2600 2400 1.81048E+11

Pulses 36 17 1608 1320 49879799165

corn 14 28 1222 6500 1.35842E+11

onions 0 15 345 19000 36607380750

Cropland fallow 4 22 100 0 0

Total Area of croplands (hectares) 47696 37231 403,377 billion liters

Other land use land cover area (hectares) 8910 19375 New reduced water use 403 billion litersTotal area (croplands + non-croplands) (hectares) 56606 56606

Reduced water use in new scenario Water Savings 120 billion liters

A. Baseline scenario: with business as usual crops at present during season 1 and\or 2

B. New scenario: with improved water productivity, re-allocation of less water consuming water-smart, economically-smart crops

25% water savings and 52% rice equivalent yield gain

Crop land extent map: Africa

Products can be accessed through our map web portal:https://web.croplands.org/app/map

(Jun et al. 2017)

https://web.croplands.org/app/map

Cropland area comparison with Survey-based stat

The total net cropland area of Africa was estimated as 313 Mha. Cropland areas were computed for each of the 55 African Countries and compared with the UN FAO statistics; this explained 65% of variability for all 55 Countries

Season wise Crop extent maps: Myanmar

Season

Months of the season

Overall accuracy of 7 classes (%)

Kappa (no units)

Producer's accuracy for fallow cropland classes (%)

Users'saccuracy for fallow cropland classes (%)

1June-October

90 0.85 57 80

2November-February

85 0.77 98 82

3 March-May 87 0.7 92 92

Accuracy assessment

Ground data collection: iCrops

After Syncing the data it will display the message

Tap on Toggle button and select map plotting to see the points plotted on google map.

Finally data can be downloaded in .csv format.

Data access

Ground data: Year 2016-17 (Eastern India)

• Ideal Signature total number of points – 353

• Validation total number of points – 1463

• Total number of kilometers travelled - 7083

Ground data: Year 2016-17 (Maharashtra)

Conclusions

▪ Random forest algorithm was used to create Crop extent for South Asia using Google Earth Engine on Landsat 30m data at good accuracy;

▪ Irrigation vs. rainfed (Product 2) was produced based on irrigation information (secondary sources)

▪ 7 Journal articles; 4 book chapters; 6 papers in review(from last CSI meeting to till now)

Further work▪ Crop extent maps in South Asia and African smallholders regions

▪ Ground data collection for crop type mapping

▪ Publications

Data access / web portals

Web sites and Data portals: http://croplands.org (30-m global croplands visualization tool)http://geography.wr.usgs.gov/science/croplands/index.html (GFSAD30 web portal and dissemination)http://geography.wr.usgs.gov/science/croplands/products.html#LPDAAC (dissemination on LP DAAC)http://geography.wr.usgs.gov/science/croplands/products.html (global croplands on Google Earth Engine)croplands.org (crowdsourcing global croplands data)

• ICRISAThttp://maps.icrisat.org/rs/maps/index.html

http://geography.wr.usgs.gov/science/croplands/index.html

http://geography.wr.usgs.gov/science/croplands/products.html#LPDAAC

http://geography.wr.usgs.gov/science/croplands/products.html

http://www.croplands.org/

http://maps.icrisat.org/rs/maps/index.html

Thank You

geospatial activities at icrisat - cgiar-csi...geospatial activities at icrisatmurali krishna gumma...

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