An integrated novel triangulation framework for monitoring ecosystem health and sustainability under regenerative landscapes

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dc.creatorYeggina, Pavan Kumar
dc.creatorMishra, Ajay Kumar
dc.creatorChalla, Kranthi Kumar
dc.creatorMaurya, Piyush Kumar
dc.creatorSahoo, Manas Ranjan
dc.creatorSharma, Mayank
dc.creatorDhingra, Jasmer
dc.creatorSrivastava, Amit Kumar
dc.creatorSharma, Sheetal
dc.date2026-02-18
dc.date2026-06-22T07:57:25Z
dc.date.accessioned2026-06-27T04:07:04Z
dc.descriptionAccelerated climate change and unsustainable agricultural practices have intensified greenhouse gas (GHG) emissions and degraded soil health, particularly in intensively cultivated landscapes. This study presents an integrated geospatial and biophysical triangulation framework to monitor ecosystem health and sustainability in the rice-based systems of Chhindwara district, Madhya Pradesh, India. The objectives were to evaluate GHG emissions, assess land use change, analyze soil health, and identify socio-economic drivers influencing agricultural sustainability under a regenerative agriculture (RA) paradigm. A combination of high-resolution satellite imagery, field-based soil sampling (n = 430), socio-economic surveys, and carbon stock modeling using the InVEST tool was employed. Land Use and Land Cover (LULC) changes over a decade (2011–2021 years) were mapped using Random Forest classification. GHG emissions were estimated using the Cool Farm Tool, while Water Use Efficiency (WUE) and biodiversity indices were evaluated across villages and seasons. In Sausar, there was a 4.6% decrease in agricultural area, a 6.6% rise in dense vegetation, and noticeable soil degradation. Mokhed had a higher soil organic content (1.07%) than Sausar (0.51%), and its carbon stocks were higher (13–35 Mg C/ha) than Sausar’s (7–13 Mg C/ha). Furthermore, Mokhed’s GHG emissions during the Kharif season were much greater at 4,000 kg CO2 eq/ha than those during the Rabi season, which were just 1,500 kg CO2 eq/ha. WUE varied by season and crop, with Rabi vegetables achieving the maximum WUE at 10.4 kg/ha-mm and cotton demonstrating the lowest efficiency at 1.4 kg/ha-mm in Kharif, underscoring the potential of targeted interventions. The framework demonstrated that integrating geospatial, biophysical, and socio-economic data provides actionable insights for climate-resilient agriculture. The findings support landscape-level planning for soil restoration, GHG emission mitigation, and sustainable intensification in rainfed regions to escalate RA transitioning and benefits for the local communities.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/183419
dc.identifier.urihttp://hdl.handle.net/123456789/22154
dc.languageen
dc.publisherFrontiers Media
dc.rightsOpen Access
dc.sourceYeggina, Pavan Kumar, Ajay Kumar Mishra, Kranthi Kumar Challa, Piyush Kumar Maurya, Manas Ranjan Sahoo, Mayank Sharma, Jasmer Dhingra, Amit Kumar Srivastava, and Sheetal Sharma. "An Integrated Novel Triangulation Framework for Monitoring Ecosystem Health and Sustainability under Regenerative Landscapes." Frontiers in Environmental Science 13: 1677426.
dc.subjectregenerative agriculture
dc.subjectsoil organic carbon
dc.subjectwater-use efficiency
dc.subjectecosystem health
dc.subjectsoil degradation
dc.subjectsoil organic carbon
dc.subjectremote sensing
dc.subjectland-use change
dc.subjectsustainable agriculture
dc.titleAn integrated novel triangulation framework for monitoring ecosystem health and sustainability under regenerative landscapes
dc.typeJournal Article

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Instituto Internacional de Investigación del Arroz (IRRI)