Pinki Mondal, University of Delaware

E-mail: mondalp@udel.edu

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Environmental Geography

Spatial distribution of human-environmental interactions

Land Change Science(Land Use Land Cover Change)

Environmental/Societal Effects of Climate Change/Hazards

Biodiversity Conservation / Natural Resource Management

Overall Research Focus

Central Indian Highlands

Pench

Kanha

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Pench, Maharashtra

Pench, Madhya Pradesh

National Park: 1975

Tiger Reserve: 1999

Area: 257 km2

NPench – the Forest of Jungle Book

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Specific Research Question

Are parks working as an ecologically sustainable management regime?

Has Pench Tiger Reserve, Maharashtra been effective to conserve forest, promote regeneration, and maintain connectivity with the surroundings?

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How can we evaluate

conservation interventions?

• Mixed methods used: –Field work

–Remote sensing analysis• Land cover classification

• Change detection analysis

–Landscape fragmentation analysis

–Land cover modeling• Cellular-automata Markov

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Land Covers in Park and Buffer –Actual vs. Predicted

Χ2 test at 95% confidence level suggests statistically significant difference between actual and predicted land covers

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50

60

70

80

90

1970 1980 1990 2000 2010

Park_forest - actual

Park_forest - predicted

Buffer_forest - actual

Buffer_forest - predicted

(a)

0

10

20

30

40

50

60

1970 1980 1990 2000 2010

Park_bare soil - actual

Park_bare soil - predicted

Buffer_bare soil - actual

Buffer_bare soil - predicted

(b)

Are

a

(%)

Are

a (

%)

Year

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Main Findings

• The park suffered deforestation until 1989, despite its protected status, due to regular forest management activities conducted by the state government.

• The Revised Forest Policy in 1988 has been effective for forest conservation within the park, e.g. in the simulated scenario the park could have suffered 20%-26% more deforestation.

• State- and World bank-funded forestry projects have been effective to establish a reforesting trend in the buffers. While the buffer is mainly managed for commercial logging, increasing amount of stable forest is encouraging.

9[Source: Mondal & Southworth, 2010a, 2010b; Mondal, 2011]

Private forest, housing pressure, and

alternate scenarios

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• Examining changing spatial distribution of harvesting activities on private forests across the urban–rural gradients.

• Comparing projected changes in the amount of impervious surface within private forests under different scenarios between 2010 and 2060.

• Quantifying overall pressure on private forests in the US.

[Source: Mondal et al. 2013]

Data Sources:Forest Inventory and Analysis (FIA) dataNational Woodland Owner Survey (NWOS) dataNational Land Cover Database (NLCD)Environment Protection Agency (EPA) housing density data

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Environmental Geography

Spatial distribution of human-environmental interactions

Land Change Science(Land Use Land Cover Change)

Environmental/Societal Effects of Climate Change/Hazards

Biodiversity Conservation / Natural Resource Management

Overall Research Focus

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Smallholder Agricultural System

Spatial distribution of human-environmental interactions(GIS and big data)

• Land Change Science (Land Use/Land Cover Change)• Environmental/Societal Effects of Climate Change/Extreme Events• Sustainability

Current Research Focus

Weather variability

Socio-economic

Well-being (food & nutrition

security)

Adaptation strategies

Samberg et al., 2016

Mean agricultural area in three global regions.

Research Context

>380 million farming households70% of food calories produced>50% staple crops worldwide

Samberg, Gerber, Ramankutty, Herrero & West, 2016. Subnational distribution of average farm size and smallholder contributions to global food production. Environmental Research Letters 11: 12401013

Current Research Context

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• 78% of Indian farmers are smallholders

• 263 million (10% of global total) depend on agriculture

• 210 million are hungryCNN: April, 2016

H. Times: September, 2017 Photo: P. Mondal

IND

IA

***2017 US population: 326 million***

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Research Context• 37% of agricultural land

is irrigated

• 60% of irrigation is provided by groundwater

• 29% less winter cropped area in regions with low groundwater availability

Map produced using India Water Tool

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Rapidly changing weather patterns is one of the biggest challenges facing smallholder farmers

Modified after Google Image

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Questions

• How does weather variability affect smallholder agricultural systems?

• What are the potential adaptation strategies under future scenarios?

• Can these strategies lead us to achieve food and nutrition security?

Ph

oto

cou

rtesy: Go

ogle Im

age

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Questions

• How does weather variability affect smallholder agricultural systems?

Location-specific component

Crop-specific component

Socio-economic component

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Satellite-derived Crop Phenology

Climate Parameters Crop Types Irrigation Demography

Methods: PIXEL to PEOPLE

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Methods: Satellite data

Mondal, Jain, DeFries, Galford & Small, 2015. Sensitivity of crop cover to climate variability: Insights from two Indian agro-ecoregions. Journal of Environmental Management 148: 21-30

Enhanced Vegetation Index (EVI)

Source: MODIS

Spatial resolution: 250m

Temporal resolution: 16 days

(a) Single crop

(b) Double crop

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Methods: Satellite data

Double crop

Single crop Mixed crop

MODIS pixel

250 m

Landsat pixel

30 m

Ph

oto

: P. M

on

da

l

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Methods: Satellite data

Precipitation

• Monsoon start date• Monsoon end date• Seasonal total• Season length• Monsoon dry days• Days with low rain• Days with heavy rain

Mondal, Jain, Singh, Galford, & DeFries. Relative importance of climatic and non-climatic factors in Indian winter crop. In prep.

Total monsoon rainfall for 2015

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Methods: Satellite data

Temperature

• Monthly average of daily Tmax

• Monthly average of daily Tmin

• Daily temperature range (DTR)

Monthly average of daily Tmax for August 2015

Mondal, Jain, Singh, Galford, & DeFries. Relative importance of climatic and non-climatic factors in Indian winter crop. In prep.

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Methods: Space time cube

Image courtesy: ArcGIS Pro

Time: 16 years (2001 - 2016)

Space:

• 3,660 pixels (NOAA CPC)• 14,157 pixels (TRMM)• 355,116 pixels (CHIRPS)• 1,787,433 pixels (MODIS)

Variables:

• Response: winter cropped area

• Predictors: precip., temp.

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Methods: Census data

Time: 2 years (2001, 2011)

Space:

• 554 districts

Variables:

• Response: winter cropped area

• Predictors: density of cultivators and agricultural laborers

26Mondal, Jain, DeFries, Galford & Small, 2015. Sensitivity of crop cover to climate variability: Insights from two Indian agro-ecoregions. Journal of Environmental Management 148: 21-30

Gujarat, Western India

Madhya Pradesh,Central India

Location-specific Vulnerability

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• Sensitivity of crop productivity to climate variability is location specific – mostly due to different cropping practices and irrigation access

• Temperature is critically important for winter crops

• Sensitivity of crop productivity to precipitation depends on irrigation source

Location-specific Vulnerability

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Crop-specific Vulnerability

Mondal, Jain, Robertson, Galford, Small & DeFries, 2014. Winter crop sensitivity to inter-annual climate variability in central India. Climatic Change 126: 61-76

PULSES (chickpea, pigeon pea,

lentil, moong)

WHEAT

Photo: P. Mondal

Irrigated field wheat Non-irrigated field pulses

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Crop-specific Vulnerability

• Ground-truth points collected in field for wheat and pulse fields

• Other data collected in field include access to irrigation and type of irrigation

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Crop-specific Vulnerability

PulsesWheat

Mondal, Jain, Robertson, Galford, Small & DeFries, 2014. Winter crop sensitivity to inter-annual climate variability in central India. Climatic Change 126: 61-76

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Crop-specific Vulnerability

• A longer wet season followed by higher winter temperatures OR a late and dry monsoon limited water availability through surface irrigation

• Pulses can be grown on residual moisture in rainfed rice fallowlands potential candidate for alternate winter crop

• Some possible adaptation strategies: • Switching to crops less sensitive to heat• shifting planting date• new early maturing crop varieties

DeFries, Mondal, Singh, Agrawal, Fanzo, Remans & Wood, 2016. Synergies and trade-offs for sustainable agriculture: Nutritional yields and climate-resilience for cereal crops in Central India. Global Food Security 11: 44-53

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• Findings indicate a fluctuating landscape – 2.11 million ha to 3.73 million ha of winter cropped area in central India.

• Seasonal labor migration to nearby towns was found to be associated with less winter crop.

• Increasing irrigation coverage will eventually result in more agricultural intensification.

Fluctuations – where & why?

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Overall findings

• More irrigation accessibility more winter crop

• Current winter crops might not be climate resilient

• Potential for coarse cereals, along with pulses, needs to be examined under projected conditions

• Ongoing and planned collaborative work with crop-climate modelers

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Machine Learning for Crop Phenology

Issues:

• Dense time-series data required

• Lack of cloud-free data

• Fine spatial resolution suitable for small farms

Synthetic Aperture Radar (SAR):

• Freely available SAR data

• Advancement of machine learning algorithms

Mondal. Drought and rice intensification in Vietnam: Mapping small farms using time-series ofSentinel-1radar data. In prep.

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Food and Nutrition Security

0

0.2

0.4

0.6

0.8

1Grain/tuber

Pulse

Nut/seed

Dairy

Meat/fish

Egg

Dark greenleafy veg

Other Vit-Arich veg/fruit

Other veg

Other fruit

Summer

0

0.2

0.4

0.6

0.8

1Grain/tuber

Pulse

Nut/seed

Dairy

Meat/fish

Egg

Dark greenleafy veg

Other Vit-Arich veg/fruit

Other veg

Other fruitWinter

Mondal, DeFries, Harou, Downs, Md. Arif, Gallant, & Fanzo. Implications of Agricultural Intensification for Diet and Nutrition in Rural India. In prep.

Photo: P. Mondal

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Food and Nutrition Security

Goal: identifying problem nutrients in smallholder farmer diet using Linear Programing Tool

Collaborators: Rutgers, Johns Hopkins, McGill

Photo: P. Mondal

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Summary

Research focus:

• Using satellite data and GIS to understand smallholder agricultural system

• Human-environment interaction

• Integrated framework Holistic approach

• Developing countries transferable to other regions

Potential collaboration beyond Geography:

• Computer and Information Sciences

• Applied Economics and Statistics

• Plant and soil sciences

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QUESTIONS??