Research graph
References from Satellite-based monitoring of crop intensity changes in kaleshwaram lift irrigation command area. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
External reference
10.35709/ory.2022.59.2.13
10.35709/ory.2022.59.2.13 · External reference
Crop yield prediction using multi sensors remote sensing
2022 · External reference
Advances in remote sensing of agriculture: Context description, existing operational monitoring systems and major information needs
10.3390/rs5020949 · 2013 · External reference
Copernicus global land cover layers—collection 2.
10.3390/rs12061044 · 2020 · External reference
A coefficient of agreement for nominal scales
10.1177/001316446002000104 · 1960 · External reference
A review of assessing the accuracy of classifications of remotely sensed data
10.1016/0034-4257(91)90048-b · 1991 · External reference
A Research Article on Importance of Hybrid Rice Cultivation in West Bengal
2022 · External reference
Mapping seasonal rice cropland extent and area in the high cropping intensity environment of Bangladesh using MODIS 500m data for the year 2010
10.1016/j.isprsjprs.2014.02.007 · 2014 · External reference
Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data
10.1080/17538947.2016.1168489 · 2016 · External reference
Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud
10.1080/15481603.2019.1690780 · 2020 · External reference
Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and spectral matching techniques (SMTs) in support of food and water security
10.1080/15481603.2022.2088651 · 2022 · External reference
Unresolved reference
2023 · External reference
Contribution of remote sensing on crop models: a review
10.3390/jimaging4040052 · 2018 · External reference
Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems
10.3390/w13243627 · 2021 · External reference
Unresolved reference
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Sustainable agriculture for food and nutritional security
2023 · External reference
Machine learning approaches and sentinel-2 data in crop type mapping
2022 · External reference
Applications of remote sensing in agriculture-A Review
10.20546/ijcmas.2019.801.238 · 2019 · External reference
Yield gaps in rice-based farming systems: Insights from local studies and prospects for future analysis
10.1016/j.fcr.2016.04.039 · 2016 · External reference
Unresolved reference
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Unresolved reference
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Global Croplands and their Importance for Water and Food Security in the Twenty-first Century: Towards an Ever Green Revolution that Combines a Second Green Revolution with a Blue Revolution
10.3390/rs2092305 · 2010 · External reference
WorldCereal: a dynamic open-source system for global-scale, seasonal, and reproducible crop and irrigation mapping
2023 · External reference
Unresolved reference
2017 · External reference
Influence of Resolution in Irrigated Area Mapping and Area Estimations
10.14358/pers.75.12.1383 · 2009 · External reference
