Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India
Wheat is a major food grain crop of main agricultural region i.e. northern plain of India. Haryana state holds a premium position in wheat production (Rabi Season) in the country. Pre-harvest yield estimation of wheat has key role in policy framing. In Haryana, Agriculture is a big support to its e...
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| Format: | Article |
| Language: | English |
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Action for Sustainable Efficacious Development and Awareness
2022-02-01
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| Series: | Environment Conservation Journal |
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| Online Access: | https://journal.environcj.in/index.php/ecj/article/view/811 |
| _version_ | 1811240455378042880 |
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| author | Man jeet Anurag Ram Niwas Dinesh Tomar |
| author_facet | Man jeet Anurag Ram Niwas Dinesh Tomar |
| author_sort | Man jeet |
| collection | DOAJ |
| description |
Wheat is a major food grain crop of main agricultural region i.e. northern plain of India. Haryana state holds a premium position in wheat production (Rabi Season) in the country. Pre-harvest yield estimation of wheat has key role in policy framing. In Haryana, Agriculture is a big support to its economy which continues to occupy a prominent position in State GDP. In present research, Agromet-Spectrals models have been developed for this purpose i.e.yield estimation in Haryana with the help of input data such as meteorological indices and satellite based NDVI(NASA’s-MODIS) from 2000-2017. Empirical models were developed for predicting wheat yield for Hisar and Karnal districts representation the two agro-climatic zone of state in Haryana, India.The models were developed used weather variable (Temperature (Minimum and Maximum), Relative Humidity (Morning and Evening) and Rainfall) and spectral indices Normalized Difference Vegetative Index viz. Agromet- model(weather model) and Agromet-spectral model (MODIS-NDVI). Weather or Agromet model was integrated with NDVI values for both location to enhanced the accuracy of models. Regression models were developed using significant weather variables and NDVI data for wheat yield prediction at both location. The result revealed that the models when integrated with remote sensing data (NDVI) gave better prediction as compared to agromet model that depends only on weather variables. Agromet-models (adjusted R2 = 0.38 to 0.78) whereas satellite data based NDVI i.e. MODIS-NDVI for both stationgave best result (Adjusted R2 = 0.61-0.86) as compared to weather models. MODIS-NDVI pixel based values observed to be more effective for wheat yield predication in integrated with weather parameters.This study could help the provincial government of Haryana as well as in northern plains in estimation of yield prior harvest at first week of April by using weather spectral (NDVI-MODIS) models.
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| first_indexed | 2024-04-12T13:20:35Z |
| format | Article |
| id | doaj.art-5683039b7d9043d28fe5d9e4c52eb1f2 |
| institution | Directory Open Access Journal |
| issn | 0972-3099 2278-5124 |
| language | English |
| last_indexed | 2024-04-12T13:20:35Z |
| publishDate | 2022-02-01 |
| publisher | Action for Sustainable Efficacious Development and Awareness |
| record_format | Article |
| series | Environment Conservation Journal |
| spelling | doaj.art-5683039b7d9043d28fe5d9e4c52eb1f22022-12-22T03:31:29ZengAction for Sustainable Efficacious Development and AwarenessEnvironment Conservation Journal0972-30992278-51242022-02-01231&210.36953/ECJ.021811-2118Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, IndiaMan jeet0Anurag1Ram Niwas 2Dinesh Tomar3Department of Agricultural MeteorologyDepartment of Agricultural Meteorology, CCS Haryana Agrivulture University, HisarDepartment of Agricultural Meteorology, CCS Haryana Agrivulture University, HisarDepartment of Agricultural Meteorology, CCS Haryana Agrivulture University, Hisar. Wheat is a major food grain crop of main agricultural region i.e. northern plain of India. Haryana state holds a premium position in wheat production (Rabi Season) in the country. Pre-harvest yield estimation of wheat has key role in policy framing. In Haryana, Agriculture is a big support to its economy which continues to occupy a prominent position in State GDP. In present research, Agromet-Spectrals models have been developed for this purpose i.e.yield estimation in Haryana with the help of input data such as meteorological indices and satellite based NDVI(NASA’s-MODIS) from 2000-2017. Empirical models were developed for predicting wheat yield for Hisar and Karnal districts representation the two agro-climatic zone of state in Haryana, India.The models were developed used weather variable (Temperature (Minimum and Maximum), Relative Humidity (Morning and Evening) and Rainfall) and spectral indices Normalized Difference Vegetative Index viz. Agromet- model(weather model) and Agromet-spectral model (MODIS-NDVI). Weather or Agromet model was integrated with NDVI values for both location to enhanced the accuracy of models. Regression models were developed using significant weather variables and NDVI data for wheat yield prediction at both location. The result revealed that the models when integrated with remote sensing data (NDVI) gave better prediction as compared to agromet model that depends only on weather variables. Agromet-models (adjusted R2 = 0.38 to 0.78) whereas satellite data based NDVI i.e. MODIS-NDVI for both stationgave best result (Adjusted R2 = 0.61-0.86) as compared to weather models. MODIS-NDVI pixel based values observed to be more effective for wheat yield predication in integrated with weather parameters.This study could help the provincial government of Haryana as well as in northern plains in estimation of yield prior harvest at first week of April by using weather spectral (NDVI-MODIS) models. https://journal.environcj.in/index.php/ecj/article/view/811Agromet-Spectral modelMODISNDVIRemote sensingWeather parameter |
| spellingShingle | Man jeet Anurag Ram Niwas Dinesh Tomar Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India Environment Conservation Journal Agromet-Spectral model MODIS NDVI Remote sensing Weather parameter |
| title | Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India |
| title_full | Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India |
| title_fullStr | Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India |
| title_full_unstemmed | Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India |
| title_short | Integrating weather model & Remote sensing indices for wheat yield prediction in Haryana, India |
| title_sort | integrating weather model remote sensing indices for wheat yield prediction in haryana india |
| topic | Agromet-Spectral model MODIS NDVI Remote sensing Weather parameter |
| url | https://journal.environcj.in/index.php/ecj/article/view/811 |
| work_keys_str_mv | AT manjeet integratingweathermodelremotesensingindicesforwheatyieldpredictioninharyanaindia AT anurag integratingweathermodelremotesensingindicesforwheatyieldpredictioninharyanaindia AT ramniwas integratingweathermodelremotesensingindicesforwheatyieldpredictioninharyanaindia AT dineshtomar integratingweathermodelremotesensingindicesforwheatyieldpredictioninharyanaindia |