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LAND SUITABILITY ASSESSMENT

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KALLAKURICHI DISTRICT, TAMIL NADU

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The Technology�

  • Our innovation lies in unlocking the productive potential of degraded lands using of state-of-the-art solutions that combine satellite imagery, various public datasets and AI based modelling for development of a digital planning tool.

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  • LifeLands identifies and analyses the potential of degraded lands in terms of regenerative use for solar, sustainable water management and ecological restoration.

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KEY OBJECTIVE

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  • To identify unused lands in Kallakurichi district.
  • Evaluate its potential for development initiatives such as forestation, storm water harvesting, agriculture, solar energy, housing and industrial development.

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Agriculture

Solar energy

Identifies suitable land for a region of interest using multilayered data-analysis

Reforestation and creation of carbon sinks

Surface and ground water management

Solar

Energy development

Provide affordable housing

Water

Forest

Industry

Housing

Overcome agricultural challenges

Development of industries to boost the local economy

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METHODOLOGY

  • Combines geo-spatial and socio-economic data-layers.

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METHODOLOGY: EVALUATION STEPS

  • 4-step filtration process to identify unused lands.

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FOREST: CRITERIA

Criteria

 

 

Distance from substation

>1

km

Distance to railway

>200

m

Distance from highways

>500

m

Terrain (geology/soil)

suitable

 

Exclude lands within burial grounds

>100

m

Distance from sea shore

>100

m 

Criteria

 

 

Min. land size

>2.47

acres

Categories

 

 

Small

>2.47 to 20

acres

Medium

>20 to 100

acres

Large

>100

acres

Criteria

High

Medium

Low

Elevation

>0.70

>0.70

0

Water potential

yes

yes

no

Forest corridor

yes

no

no

Seclusion (km)

>1

no

no

Theoretical Potential

Criteria for distribution by size

Criteria for high priority setting

Technical potential

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WATER: CRITERIA

Criteria

 

Elevation (with respect to watershed elevation)

Lower (30%)

Run-off capture

yes

Criteria

High (H)

Medium (M)

Low (L)

Yearly run-off (m3 per pixel)

>200

>70-200

0-70

Water demand (% of cropland in watershed area with high ET)*

>50%

>30 - 50%

<30%

Criteria for unused lands

High

Medium

Low

Yearly run-off (m3 per pixel)

H &M

H, M, L

H, M, L

Water demand (% of cropland in watershed area with high ET)*

H

M

L

*Lands with high water demand and low run-off capture are filtered out

Technical potential

Priority ranking

Rating of unused lands

*High ET areas are pixels with ET greater than 600mm/year

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AGRICULTURE: CRITERIA

Criteria

​

Exclude lands within protected areas*

>1,000 m

Distance to airport**

>500 m

Exclude lands within burial grounds

>100 m

Criteria

High

Medium

Low

Distance from waterbody (m)

<200

>200 to 500

>500

Theoretical potential

*Areas designated as reserve forest

** There is no airport in Kallakurichi district

Technical potential

Listing lands with technical potential by size

Criteria for priority ranking

Criteria

​

Land size

>1 acres

Distance from highways

>500 m

Slope

<15 %

Categories

​

S1

>1 to 5 acres

S2

>5 to 10 acres

S3

>10 acres

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HOUSING DEVELOPMENT: CRITERIA

Criteria

​

Slope

<8%

Distance from water body

>500 m

Distance from sea shore

>500 m

Distance to railway

>1,000 m

Distance from highways

>500 m

Distance to airport

>500 m

Exclude lands within protected areas

>1,000 m

Exclude lands within burial grounds

>100 m

Criteria

 

Minimum land size

0.25 acre

Distance to settlement

<2,000 m

Distance to road access

<1,000 m

Categories

​

S1

>0.25 to 2 acres

S2

>2 to 5 acres

S3

>5 acres

Criteria

High

Medium

Low

Plot size (acres)

>5

>2

> 0.25

Distance to settlement (km)

<0.50

<0.50

<2

Distance from high-way (km)

>1

>0.50

>0.50

Distance to road (other than highway)*

<100

-

-

Theoretical potential

Technical potential

Listing lands with technical potential by size

Criteria for priority ranking

*Primary, secondary and tertiary roads

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INDUSTRIAL DEVELOPMENT: CRITERIA

Criteria

Filter

Slope

<8%

Distance from water body

>500 m

Distance from sea shore

>500 m

Distance from road

<2 km

Distance to airport

>500 m

Exclude lands within burial grounds

>100 m

Distance to notified forest

> 5 km

Criteria

​

Minimum land size

>1,200 m2 | 0.30 acres

Distance to settlement

<15 km

Categories

​

S1

>0.30 to 20 acres

S2

>20 to 100 acres

S3

>100 acres

*Primary, secondary and tertiary roads

Theoretical potential

Criteria for priority ranking

Technical potential

Listing lands with technical potential by size

Criteria

High

Medium

Low

Distance from road (km)*

<0.50

<0.50 to <1

>1

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KEY DATA LAYERS

Data layers

Description

Source

Accessibility

Roads and

railway lines

OSM

Barren/ unused area

Lands with barren signature

Sentinel-2 satellite images

Built-up cluster

Clusters of built-up areas.

World Settlement Footprint (WSF)

And Sentinel LandCover 10m

Elevation

Height of the area of interest.

Shuttle Radar Topography

Mission (SRTM)-30m

Evacuation

infrastructure

Transmission lines

and substations.

OSM, and Google Earth.

Evapotranspiration

Loss of water in the form of evaporation from the soil surface and transpiration from the plants.

Terra MODIS (Net

Evapotranspiration Yearly L4

Global 500m).

Data layers

Description

Source

Global Horizontal

Irradiance (GHI)

The total (direct and diffuse) solar energy intercepted by a unit of horizontal surface. Measured in kWh/m2/day.

SOLARGIS (https://solargis.com)

Land cover

7 categories

Sentinel-2 satellite images and

WSF

Population density

Number of people per unit area. The population data is from (Meta, 2022).

Derived from (Meta, 2022)

Protected areas/Reserve forest/Notified forest

These are areas allocated for reserve forests and other such classified lands.

Government Data

Soil erosion

Classified as slight, moderate, severe, indicating how easily surface soil particles are transported.

Tamil Nadu Government Data

 

Terrain/geology

Considers types of terrain

Bhukosh

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GROUND VERIFICATION PROCESS

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KALLAKURICHI DISTRICT, TAMIL NADU

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KEY OBJECTIVE

  • To evaluate the tool’s accuracy of identifying unused lands with the ground data.

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  • To verify 1% of the total unused area identified in Kallakurichi at ground level.

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METHODOLOGY

  • 3 key stages for completing the ground verification:

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1. Determine sample or areas for ground verification

2. Collect ground data

3. Conduct Analysis

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LAND SELECTION

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METHODOLOGY: DATA COLLECTION METHOD

  • The overall data collection procedure is as follows:

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  • Note: Only areas that appear unused at the site and that fall within the boundaries of the sample are recorded with geotagging. Patches within the boundaries that are not unused and are greater than 20m × 20m, are traced separately.

1. Locate the land parcels using maps and/or mobile app.

2. Trace or go around the boundary (as feasible) of the unused land parcel using the Kobotoolbox app.

3. Record if the land is unused or not.

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DATA COLLECTION FORM

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DATA COLLECTION FORM

  • The data collection form aims to record the unused area on the ground, and any disparities in the results with the ground reality.

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ANALYSIS

  • The data collected on the ground is processed in QGIS software. It is then compared and matched pixel by pixel with the results of the algorithm.

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  • For the analysis and comparison, the confusion or error matrix is used to measure false positives and false negatives.

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CONCLUSION�

  • The ground truthing exercise for Kallakurichi district indicates a high overall accuracy of 89.9 %. This accuracy indicates the algorithm’s high reliability to identify unused lands. However, for carrying out such studies successfully, the quality of and access to data are key.

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  • Time passed between period of analysis and ground truthing can be a challenge for measuring the accuracy, especially with the time required for coordinating, capacity building and collecting data.

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Thank you!