Measure the village before you model it.
A student-led living laboratory for climate-resilient agriculture, environmental monitoring, and rural innovation.
Rural communities around the world are being asked to reduce emissions, protect natural resources, and remain economically productive. Yet many interventions begin without a sufficiently detailed local environmental baseline.
Ivanovka offers an unusual test case: an integrated agricultural community where farmland, livestock, water resources, machinery and production are connected within one system. Founded in 1840 by Molokan settlers, it is the only collective farm still operating in the former Soviet Union — its fields, machinery, herds and harvest remain in shared ownership. The farm carries the name of Nikolai Nikitin, who chaired it from 1953 to 1994. Open data
Ivanovka 2050 begins with a simple principle: measure the system before attempting to change it.
Can a low-cost, community-based environmental monitoring system help agricultural villages measure and improve climate resilience over time?
What is the environmental condition of the village at the point of first measurement — its soil, its water, its ground cover?
Completed · 2023Can low-cost field measurements and sensors produce data that stays useful when repeated across seasons and years?
Completed · 2024Can that record guide measurable improvements in water use, biodiversity, emissions, waste and energy?
Completed · 2025–2026Measure → observe change → only then intervene
The project ran over thirty-seven months and culminated in a field campaign in Ivanovka, hosted by the Nikitin collective farm. Four workstreams ran in parallel.
Samples were taken across cultivated plots, field margins, disturbed ground near the road and vegetated slopes, then bagged and labelled on site. A subset spread evenly across the six points was characterised in full.
Samples were drawn from the farm reservoir known locally as Ivan-gölü, which feeds the irrigated fields, and assessed against daylight at the shoreline.
At every point the team recorded ground cover and surface condition, comparing drip-irrigated sunflower rows against unmanaged margins and gravel-disturbed ground.
Emission-relevant context for the village was assembled from published sources. It frames where emissions in Ivanovka are likely to sit; it is not a measured inventory, and this site does not present it as one.
Photographic recordKept at every sampling point alongside the labelled samples, so the same ground can be compared when the points are revisited.
Twenty characterised soil samples and one water sample. Every figure below is calculated from the ledger at the foot of this section — nothing is estimated.
Mean of the samples taken at each point.
Mean moisture content at each point.
Dominant colour and structure recorded at each point, from cultivated through disturbed to vegetated ground.
| Point | Land use | n | pH range | Dominant colour | Structure |
|---|
The characterised subset in full — one row per sample, nothing aggregated away.
| Point | Type | Colour | Structure |
|---|
Filter by point or sort by ID, pH or moisture. Empty cells (—) were not recorded for that sample type.
Six points across the village and its surrounding land. Coordinates are approximate and listed as such until verified GPS records replace them.
Base map: Esri World Topographic Map, with data © OpenStreetMap contributors and others. Point positions are indicative.
How the record was produced, and what each figure on this site rests on.
Six locations were chosen to span the land-use types present in the village: cultivated field margin, drip-irrigated plot, disturbed roadside ground, unmanaged vegetated slope, reservoir shoreline and the ridge overlooking the settlement.
Surface samples were taken by hand at each point, sealed in labelled bags and kept together until characterisation. Twenty were characterised on pH, moisture, colour and structure using field methods, not accredited laboratory equipment.
Samples were collected in vials from the shoreline of Ivan-gölü and assessed against daylight for turbidity and suspended matter, with pH recorded by the same field method used for soil.
Point positions are currently recorded as approximate coordinates derived from the survey route and plotted on OpenStreetMap. Verified GPS capture is the first task of the next campaign.
Every figure on this site carries its provenance. Measured means the team produced the number. Observed means it was recorded in the field without instrumentation. Open data means a published source, cited.
The pilot has established the environmental baseline. The remaining components were delivered in the next phase.
A characterised soil dataset, a water sample from the reservoir feeding the irrigation system, and a ground-condition record across six land-use types — the reference point every later measurement is compared against.
Six sampling locations selected, mapped and documented photographically, with a repeatable protocol so the same points can be revisited in later seasons.
Moving from desk study to a measured village-wide inventory: herd numbers, fuel use, heating and machinery hours drawn from farm records, producing CO₂, energy and waste maps.
Repeat monitoring of soil quality, vegetation health and degradation to build a Living Nature Index and identify areas for replanting, extended with image analysis.
Continuous monitoring across the irrigation system to detect leaks, excess irrigation and quality issues, with recommendations that cut consumption without cutting yield.
Sensor monitoring of the herd to reduce methane emissions, optimise feeding schedules, improve animal health and cut water use.
Demand, storage and transport prediction for dairy and produce, aimed at cutting losses along the chain between the farm and the market.
Feasibility assessment of solar generation, biogas from livestock waste, storage and a community microgrid — turning a waste stream the farm already produces into energy for local facilities.
A community that runs as a single collective system is an unusually clean test case. The aim is that what works here becomes a replicable Smart Village Framework for agricultural regions across Azerbaijan and beyond, published openly so the next community does not start from zero.
Ivanovka 2050 is designed around transparent, reproducible field research. Wherever possible, raw observations, sampling metadata, methodology and derived datasets are made openly available.
The dataset carries the twenty characterised soil samples and the Ivan-gölü water sample, with sampling point, land-use type and all four parameters. A written sampling protocol and verified coordinates will be published as separate files once the next campaign records them.
Ivanovka 2050 is currently an independent student-led pilot. The next phase is designed for collaboration with universities, environmental laboratories, agricultural researchers, data scientists and rural development organisations.
Ivanovka 2050 is an open field case study for researchers interested in rural sustainability, environmental monitoring, agricultural systems, climate resilience and community-scale data collection. The baseline, the protocol and the full field ledger are all published on this page.
Roles reflect the work each person took on across the campaign. Several members covered more than one.
Fieldwork was conducted with permission from the Nikitin collective farm, providing direct access to agricultural land and local environmental conditions. An acknowledgement from the Ismayilli District Executive Authority has been requested and will be published here once issued.