Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery
The monitoring of wheat crop growth plays a crucial role in ensuring effective agricultural management and enhancing food security. Valuable insights into the spatial distribution and various growth stages of wheat crop can be obtained through the combination of multi-spectral remote sensing dataset...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Biology and Life Sciences Forum |
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| Online Access: | https://www.mdpi.com/2673-9976/27/1/16 |
| _version_ | 1797241864778153984 |
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| author | Baljit Singh Bhavya Chauhan Sandeep Kumar Kaushik Varun Narayan Mishra |
| author_facet | Baljit Singh Bhavya Chauhan Sandeep Kumar Kaushik Varun Narayan Mishra |
| author_sort | Baljit Singh |
| collection | DOAJ |
| description | The monitoring of wheat crop growth plays a crucial role in ensuring effective agricultural management and enhancing food security. Valuable insights into the spatial distribution and various growth stages of wheat crop can be obtained through the combination of multi-spectral remote sensing datasets, data analysis, and ground-truth verification. This work aims to monitor wheat crops at farm level in the Bathinda district of India during the agricultural year 2022–23. It involves collecting and analyzing multispectral satellite data over five selected farmlands in the study region. Preprocessing of the multispectral satellite data is performed, including radiometric and atmospheric corrections. The wheat crops’ health and growth are examined, utilizing various indices such as the Land Surface Water Index (LSWI), Normalized Difference Red Edge (NDRE), and Normalized Difference Vegetation Index (NDVI) retrieved from time series remote sensing datasets. Furthermore, wheat crop monitoring is performed, using fortnightly data encompassing its health, moisture levels, and growth stages on individual farmlands. Different farmlands have shown varied LSWI, NDRE, and NDVI values. Variations in crop growth and productivity were observed among farmlands due to differences in soil properties and sowing dates. The findings from this study offer valuable insights into the importance of timely sowing, crop health monitoring, irrigation management, and soil suitability in optimizing wheat crop production. |
| first_indexed | 2024-04-24T18:30:06Z |
| format | Article |
| id | doaj.art-6ef03344e7a74822b3d3051bb8ef63f8 |
| institution | Directory Open Access Journal |
| issn | 2673-9976 |
| language | English |
| last_indexed | 2024-04-24T18:30:06Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biology and Life Sciences Forum |
| spelling | doaj.art-6ef03344e7a74822b3d3051bb8ef63f82024-03-27T13:28:22ZengMDPI AGBiology and Life Sciences Forum2673-99762023-10-012711610.3390/IECAG2023-14983Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite ImageryBaljit Singh0Bhavya Chauhan1Sandeep Kumar Kaushik2Varun Narayan Mishra3Amity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, Sector 125, Noida 201313, IndiaAmity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, Sector 125, Noida 201313, IndiaDeHaat Pvt. Ltd., Sector 30, Gurugram 122011, IndiaAmity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, Sector 125, Noida 201313, IndiaThe monitoring of wheat crop growth plays a crucial role in ensuring effective agricultural management and enhancing food security. Valuable insights into the spatial distribution and various growth stages of wheat crop can be obtained through the combination of multi-spectral remote sensing datasets, data analysis, and ground-truth verification. This work aims to monitor wheat crops at farm level in the Bathinda district of India during the agricultural year 2022–23. It involves collecting and analyzing multispectral satellite data over five selected farmlands in the study region. Preprocessing of the multispectral satellite data is performed, including radiometric and atmospheric corrections. The wheat crops’ health and growth are examined, utilizing various indices such as the Land Surface Water Index (LSWI), Normalized Difference Red Edge (NDRE), and Normalized Difference Vegetation Index (NDVI) retrieved from time series remote sensing datasets. Furthermore, wheat crop monitoring is performed, using fortnightly data encompassing its health, moisture levels, and growth stages on individual farmlands. Different farmlands have shown varied LSWI, NDRE, and NDVI values. Variations in crop growth and productivity were observed among farmlands due to differences in soil properties and sowing dates. The findings from this study offer valuable insights into the importance of timely sowing, crop health monitoring, irrigation management, and soil suitability in optimizing wheat crop production.https://www.mdpi.com/2673-9976/27/1/16wheat cropLSWINDRENDVImulti-spectral remote sensing |
| spellingShingle | Baljit Singh Bhavya Chauhan Sandeep Kumar Kaushik Varun Narayan Mishra Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery Biology and Life Sciences Forum wheat crop LSWI NDRE NDVI multi-spectral remote sensing |
| title | Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery |
| title_full | Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery |
| title_fullStr | Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery |
| title_full_unstemmed | Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery |
| title_short | Monitoring of Wheat Crop Growth at Farm Level Using Time Series Multispectral Satellite Imagery |
| title_sort | monitoring of wheat crop growth at farm level using time series multispectral satellite imagery |
| topic | wheat crop LSWI NDRE NDVI multi-spectral remote sensing |
| url | https://www.mdpi.com/2673-9976/27/1/16 |
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