| CPC G06T 7/0012 (2013.01) [A01B 79/02 (2013.01); G06T 7/73 (2017.01); G06V 20/13 (2022.01); G06V 20/188 (2022.01); G06V 20/38 (2022.01); G06T 2207/30004 (2013.01); G06T 2207/30188 (2013.01)] | 14 Claims |
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1. A processor-implemented method assessing soil carbon sequestration of farming based on remote sensing comprising:
receiving a plurality of satellite data from a satellite, via a one or more hardware processor, wherein the satellite data is obtained by remote sensing a land area and comprises a plurality of satellite images with corresponding geo co-ordinates, a carbon map, a plurality of agroclimatic zone for the plurality of satellite images, a biological yield, a Soil Organic Carbon Below Ground (SOC BG) and an Organic Carbon Above ground (OC AG), and wherein the SOC BG and the OC AG are real-time values received from the plurality of satellite data at a particular time instant;
receiving a plurality of farming data from a plurality of sources, via the one or more hardware processor, wherein the plurality of farming data is associated with a farm in the land area and comprises the farm's location, the farm's geo-coordinates and a crowd sourcing data;
locating the farm in the plurality of satellite data using the plurality of farming data, via the one or more hardware processor, based on a location identification technique;
identifying an agroclimatic zone and a suitable crop for the farm using the plurality of satellite data, via the one or more hardware processor, wherein the agroclimatic zone and the suitable crop are identified based on a Machine Learning (ML) technique;
estimating an initial Soil Organic Carbon (SOC) level for the farm using the plurality of satellite data, via the one or more hardware processor, wherein the SOC level is estimated based on a carbon sequestration estimation technique;
recommending a set of agricultural practices for a crop life cycle of the suitable crop using a carbon smart crop protocol, via the one or more hardware processor, wherein the carbon smart crop protocol is identified based on the agroclimatic zone and the SOC of the farm, wherein the recommended set of agricultural practices are aligned to ensure effective carbon sequestration in the soil and increase carbon levels in the soil, and wherein the carbon smart crop protocol is a personalized recommendation of a set of tillage operations, a nutrient management, an irrigation management, a pest and disease management for farming of the suitable crop;
continuously monitoring the farm at real time for the crop life cycle of the suitable crop using the plurality of satellite data and the plurality of farming data based on a remote sensing technique, via the one or more hardware processor, wherein the remote sensing technique comprises estimating a crop health index and an adoption index, wherein the crop health index is an indicator of a health condition of the suitable crop and the adoption index is associated with the recommended set of agricultural practices, wherein the health condition of the suitable crop is determined based on the crop health index and a set of pre-determined threshold values, wherein adoption is a degree of actual use of the carbon smart crop protocol by farmers and measured on three-point continuum including a full adoption, a partial adoption and a non-adoption by assigning a score of 2, 1 and 0, and wherein the adoption index is directly proportional to the crop health index;
assessing a soil carbon sequestration for the farm at real time by computing a set of carbon sequestration parameters for the farm using the plurality of satellite data, the plurality of farming data, the agro-climatic zone, the initial SOC, the crop health index and the adoption index, via the one or more hardware processor, wherein the set of carbon sequestration parameters comprises a final SOC, a carbon loss and a net carbon sequestration level; and
displaying the set of carbon sequestration parameters on an input/output (I/O) interface for remotely monitoring the farm.
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