Use of SAR data for Rice Assessment

Similar documents
W E E K L Y MONSOON INSIGHT

Probability models for weekly rainfall at Thrissur

O.I.H GOVERNMENT OF INDIA MINISTRY OF AGRICULTURE AND FARMERS WELFARE DEPARTMENT OF AGRICULTURE, COOPERATION AND FARMERS WELFARE

Date of. Issued by (AICRPAM), & Earth System

Leveraging Sentinel-1 time-series data for mapping agricultural land cover and land use in the tropics

DROUGHT RISK EVALUATION USING REMOTE SENSING AND GIS : A CASE STUDY IN LOP BURI PROVINCE

Indian Earth Observation Programme

Effect of rainfall and temperature on rice yield in Puri district of Odisha in India

O.I.H. GOVERNMENT OF INDIA MINISTRY OF AGRICULTURE AND FARMERS WELFARE DEPARTMENT OF AGRICULTURE, COOPERATION AND FARMERS WELFARE

Indian National (Weather) SATellites for Agrometeorological Applications

Water Resource & Management Strategies

NPTEL. NOC:Weather Forecast in Agriculture and Agroadvisory (WF) - Video course. Agriculture. COURSE OUTLINE

Long Range Forecast Update for 2014 Southwest Monsoon Rainfall

GEO Joint Experiment for Crop Assessment and Monitoring (JECAM): 2014 Site Progress Report

Summary and Conclusions

NAKSHATRA BASED RAINFALL ANALYSIS AND ITS IMPACT ON CROPS DURING MONSOON SEASON AT MANDYA DISTRICT

International Journal of Scientific Research and Reviews

RESEARCH NOTE Changing Dew Patterns in Anantapur District, Andhra Pradesh: A Generalistic Observation INTRODUCTION

Chapter 2 Drought Hazard in Bihar

Frequency analysis of rainfall deviation in Dharmapuri district in Tamil Nadu

Rice Monitoring using Simulated Compact SAR. Kun Li, Yun Shao Institute of Remote Sensing and Digital Earth

Development of regression models in ber genotypes under the agroclimatic conditions of south-western region of Punjab, India

ORIGINAL IN HINDI GOVERNMENT OF INDIA MINISTRY OF CONSUMER AFFAIRS, FOOD & PUBLIC DISTRIBUTION DEPARTMENT OF FOOD AND PUBLIC DISTRIBUTION

Rainfall is the major source of water for

PROJECT REPORT (ASL 720) CLOUD CLASSIFICATION

Agricultural land-use from space. David Pairman and Heather North

Outline. Remote Sensing, GIS and DEM Applications for Flood Monitoring. Introduction. Satellites and their Sensors used for Flood Mapping

ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of Climate Change on Agriculture

DROUGHT ASSESSMENT USING SATELLITE DERIVED METEOROLOGICAL PARAMETERS AND NDVI IN POTOHAR REGION

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

Rainfall variation and frequency analysis study of Salem district Tamil Nadu

Journal of Pharmacognosy and Phytochemistry 2017; 6(4): Sujitha E and Shanmugasundaram K

Development of Agrometeorological Models for Estimation of Cotton Yield

Applications of yield monitoring systems and agricultural statistics in agricultural (re)insurance

DECISION MAKING IN AGRICULTURE BASED ON LAND SUITABILITY SPATIAL DATA ANALYSIS APPROACH

Rainfall variation and frequency analysis study in Dharmapuri district, India

Fish Pond. Old Secretariate. Shaheed Smarak

CHANGE DETECTION USING REMOTE SENSING- LAND COVER CHANGE ANALYSIS OF THE TEBA CATCHMENT IN SPAIN (A CASE STUDY)

VILLAGE INFORMATION SYSTEM (V.I.S) FOR WATERSHED MANAGEMENT IN THE NORTH AHMADNAGAR DISTRICT, MAHARASHTRA

Traditional method of rainfall prediction through Almanacs in Ladakh

Stochastic Modelling of Daily Rainfall at Naogaon District in Bangladesh: A Comparative Study

Introduction to Satellite Derived Vegetation Indices

Effect of Weather Parameters on Population Dynamics of Paddy Pests

CROP COMBINATION REGION: A SPATIO-TEMPORAL ANALYSIS OF HARYANA: &

Development of the Regression Model to Predict Pigeon Pea Yield Using Meteorological Variables for Marathwada Region (Maharashtra)

ALL INDIA WEATHER SUMMARY AND FORECAST BULLETIN

Analytical Report. Drought in Sri Lanka January2017 ERCC Analytical Team and JRC Drought Team 26 January Map

3. HYDROMETEROLOGY. 3.1 Introduction. 3.2 Hydro-meteorological Aspect. 3.3 Rain Gauge Stations

MODELING RUNOFF RESPONSE TO CHANGING LAND COVER IN PENGANGA SUBWATERSHED, MAHARASHTRA

To Predict Rain Fall in Desert Area of Rajasthan Using Data Mining Techniques

10 emergency observation requests were successfully processed during the period

Advanced Image Analysis in Disaster Response

Study of Hydrometeorology in a Hard Rock Terrain, Kadirischist Belt Area, Anantapur District, Andhra Pradesh

Influence of Micro-Climate Parameters on Natural Vegetation A Study on Orkhon and Selenge Basins, Mongolia, Using Landsat-TM and NOAA-AVHRR Data

Key Finding: Long Term Trend During 2014: Rain in Indian Tradition Measuring Rain

GOVERNMENT OF INDIA MINISTRY OF HEALTH AND FAMILY WELFARE DEPARTMENT OF HEALTH AND FAMILY WELFARE

Chapter-3 GEOGRAPHICAL LOCATION, CLIMATE AND SOIL CHARACTERISTICS OF THE STUDY SITE

ALL INDIA WEATHER SUMMARY AND FORECAST BULLETIN

BOTSWANA AGROMETEOROLOGICAL MONTHLY

Seasonal Hydrological Forecasting in the Berg Water Management Area of South Africa

Plantations Mapping of Dabwali, Rania and Ellenabad blocks of Sirsa District Using on Screen Visual Interpretation Approach on WV-2 Data

SMAP and SMOS Integrated Soil Moisture Validation. T. J. Jackson USDA ARS

Use of Geospatial data for disaster managements

Weather and climate outlooks for crop estimates

Spatial and Temporal Analysis of Rainfall Variation in Yadalavagu Hydrogeological unit using GIS, Prakasam District, Andhra Pradesh, India

MARKOV CHAIN MODEL FOR PROBABILITY OF DRY, WET DAYS AND STATISTICAL ANALISIS OF DAILY RAINFALL IN SOME CLIMATIC ZONE OF IRAN

Seasonal Activity of Sogatella furcifera H.,Cnaphalocropcis medinalis G. and Mythimna separata W. in Relation to Weather Parameters in Central India

CHAPTER VII FULLY DISTRIBUTED RAINFALL-RUNOFF MODEL USING GIS

Indian Earth Observations Satellites and Applications - Reaping Social Benefits

Abstract. TECHNOFAME- A Journal of Multidisciplinary Advance Research. Vol.2 No. 2, (2013) Received: Feb.2013; Accepted Oct.

Land Use and Land Cover Mapping and Change Detection in Jind District of Haryana Using Multi-Temporal Satellite Data

Dry spell analysis for effective water management planning

Best Fit Probability Distributions for Monthly Radiosonde Weather Data

Assessment of Ground Water in a Part of Coastal West Bengal using Geo-Electrical Method

An Approach to Analyse the Agriculture Acreage and Estimate Production

CHAPTER 4 METHODOLOGY

Analysis of Rainfall and Other Weather Parameters under Climatic Variability of Parbhani ( )

Remote Sensing Geographic Information Systems Global Positioning Systems

The study of the impact of climate variability on Aman rice yield of Bangladesh

Joint Meeting of RA II WIGOS Project and RA V TT-SU on 11 October 2018 BMKG Headquarter Jakarta, Indonesia. Mrs. Sinthaly CHANTHANA

Land Use Land Cover Change in Active Flood Plain using Satellite Remote Sensing

The Importance of Snowmelt Runoff Modeling for Sustainable Development and Disaster Prevention

USE OF GEOREFERENCE INFORMATION FOR DRM Arnob Bormdoi Research Associate, GIC

[Penumaka, 7(1): January-March 2017] ISSN Impact Factor

CURRENT STATUS OF MONSOON Main Meteorological conditions of the last week (27August to 2 September)

B.A. /B.Sc. (Honours) Course in Geography (Revised Syllabus) (W.e.f. from the Academic Session )

Droughts are normal recurring climatic phenomena that vary in space, time, and intensity. They may affect people and agriculture at local scales for

ALL INDIA WEATHER SUMMARY AND FORECAST BULLETIN

OVERVIEW OF IMPROVED USE OF RS INDICATORS AT INAM. Domingos Mosquito Patricio

Effective Utilization of Synthetic Aperture Radar (SAR) Imagery in Rapid Damage Assessment

Drought risk assessment using GIS and remote sensing: A case study of District Khushab, Pakistan

over the next three weeks could lower this estimate significantly. Near perfect conditions are needed to realize this projected yield.

LAND USE AND LAND COVER ANALYSIS USING 8- BAND DATA: A CASE STUDY OF BELGAUM CITY AND ITS SURROUNDING.

CLASS XII GEOGRAPHY (029) SAMPLE QUESTION PAPER ( ) Time allowed - 3 Hrs. Max. Marks 70

Comparison between Multitemporal and Polarimetric SAR Data for Land Cover Classification

A looming drought is manageable. Long-term changes to the monsoon might be catastrophic

Population dynamics of chiku moth, Nephopteryx eugraphella (Ragonot) in relation to weather parameters

Statistical Analysis of Temperature and Rainfall Trend in Raipur District of Chhattisgarh

AFP Surveillance Bulletin - India Report for week 1, ending 5 January 2019

STUDY OF CLIMATE VARIABILITY AND ITS CORRELATION WITH SUGARCANE YIELD OVER BAGALKOT USING REMOTE SENSING.

Transcription:

Use of SAR data for Rice Assessment N e e t u, S h i b e n d u S R a y a n d T e a m M a h a l a n o b i s N a t i o n a l C r o p F o r e c a s t C e n t r e, D e p a r t m e n t o f A g r i c u l t u r e, C o o p e r a t i o n & F a r m e r s W e l f a r e M i n i s t r y o f A g r i c u l t u r e & F a r m e r s W e l f a r e G o v e r n m e n t o f I n d i a N e w D e l h i - 1 1 0 0 1 2, I n d i a E m a i l : n e e t u. n c f c @ n i c. i n

Outlines Introduction Satellite Data Methodology What can be done from SAR data for Rice? Acreage estimation Biomass estimation Area estimation during Flood/Drought CCE Planning Crop Map Validation Future Scope

Introduction Rice is the major food grain crop of India. Rice is grown in multiple seasons in India i.e. Kharif, Rabi and Summer Rice India is the second largest producer of Rice in world (https://apps.fas.usda.gov/). Rice is grown in different environment in India. Rice is grown with multiple cultural types in India. Rice crop is highly dependent on Rainfall in India (58.0 % Rice crop is irrigated) (Source: DAC&FW). Rice yield is highly varying in India. Mean Yield (Bihar ~1650 kg/ha and Punjab ~3900 kg/ha) (Source: DAC&FW)

Satellite Data Radarsat-2 and RISAT-1Swath Coverage's over India Satellit e Radars at-2 Sens or Scan SAR Narro w B RISAT-1 MRS mode Sentine l -1 A Resol ution Swath Spectral Bands used 25m 300 km C band SAR HH Polarizat ion data 18m 115km C Band SAR HH Polarizat ion data SAR 20m 250 km C Band VV Polarizat ion SAR data Sets of data required at a time Multi-date Multi-date Multi-date Time Period Kharif Season (May to July) for Punjab, Haryana and (June to September) for rest of the Study States, (October to January) for Tamil Nadu Rabi Season (January to March) for Rabi Paddy Crop Kharif Rice No. of Study States State to Nation (% Area Contributio n) State to Nation (% Production Contributio n) 14 90 91

Methodology

What can be done from SAR data for Rice? Acreage Estimation

Acreage Estimation

Acreage Estimation District wise Kharif Rice Area (left) and Production (Right) using SAR data

Acreage Estimation State wise Rice Area and Production using SAR data for Kharif Rice in India from 2012-13 to 2016-17

Biomass Estimation Mean TP vs Frequency and Normalized age vs Biomass for Bihar 2015-16 Source: SAC, ISRO

Area estimation during Flood

Area estimation during Flood Rice-Flooded Area Assessment, post-phailin Cyclone in Odisha State, October, 2013

Area estimation during Drought GT Used - 2015-16 Number of GT: 93 GT Period : 03 to 21-Sept-15 Seasonal Rainfall of Telangana upto 30/09/15 (Source: www.imd.gov.in) Source: NADAMS Report Nizamabad district in Telangana State showing reduction in rice area

CCE Planning Generation of crop specific map using SAR data and ground truth NDVI computation for specific cropped area. Integration with other parameters (remote sensing, soil, weather), if available Classification into 4-6 classes, based on the variability existing Select CCE points randomly within each stratum Overlay the village boundary on the CCE locations Prepare a list of CCE points, along with the geographical coordinates, village (and block and district names)

Crop Map Crop map for Odisha and West Bengal for Kharif paddy using RISAT-1 data from June 25 to September 10, 2016

Validation Data Source: FASAL and DAC&FW

Future Scope Methodology needs to be developed for more crops (Cotton, Maize etc.) grown in Kharif Season using SAR data. Farm level/ Village level crop area/loss assessment using High Resolution SAR (Sentinel, 10 m in every 5 days) data. Improved data frequency and resolution will definitely improve the biomass estimation accuracy. Further research needed for crop parameter retrieval (biomass, LAI, Phenology, Yield) from SAR.

Acknowledgment Organizations Indian Space Research Organization Department of Agriculture, Cooperation & Farmers Welfare India Meteorological Department Institute of Economic Growth State Agriculture Departments State Remote Sensing Centres Team Members from MNCFC Team Dr. Shalini Saxena Mr. Sunil Kumar Dubey Mr. Kanwar Vivek Singh Mr Akhilesh Porwal Mr Rajat Saxena Mr Santosh Kumar Dr. Varunika Jain Mr Ashutosh Kumar Gavli This work has been done under FASAL project of DAC&FW. THANK YOU