Insight into the world through data.

Inside datawaearth

Live product, in operation today · datawaearth.live ↗

01

Commodities and crops in one dashboard

A live ticker of futures, ETFs and equities runs across the top while assets are grouped by commodity — lithium, copper, aluminium, rare earths, nickel, manganese, cobalt, iron ore — beside maize, soybean, wheat and coffee. Every card carries capacity, operator and a satellite thumbnail.

datawaearth — dashboard grouping lithium and copper assets under a live market ticker
02

Asset registry with an AI analyst

Open any asset — Salar de Atacama, Escondida, Oyu Tolgoi — for operator, capacity, linked tickers and the specific satellite signal worth watching. An AI analyst reads the imagery, the registry and the news timeline together, and the map replays Sentinel-2 time-lapse back to 2017.

datawaearth — lithium asset detail with AI analysis panel and satellite time-lapse
03

Crop conditions graded every day

Producing countries are graded Healthy / Normal / Watch / Alert daily. The current season (orange) is plotted against a 10-year baseline median and its IQR band, with base score, stall, level-low and critical readings broken out — 252 sample points across the US soy belt alone.

datawaearth — US soybean NDVI against a ten-year baseline with condition grade
04

Perennials, not just row crops

Coffee is sampled across the arabica belts of Sul de Minas, Cerrado Mineiro and Mogiana plus the conilon zones of Espírito Santo and Rondônia. On a perennial canopy the NDVI anomaly is the signal — it flags drought stress and frost damage, as in the July 2021 frost.

datawaearth — Brazil coffee NDVI across arabica and conilon sampling zones
05

Industrial build-outs, tracked from orbit

Monitoring is not limited to what grows. Follow a company’s footprint site by site — 11 Samsung locations across HQ, fabs and assembly plants — and watch greenfield construction like the Taylor, Texas fab progress through shell completion and cleanroom fit-out.

datawaearth — Samsung Taylor fab construction monitored on satellite imagery

How it works

From raw data to actionable insight.

  1. 1

    Data in

    Satellite imagery, public datasets, and domain-specific sources are ingested and normalized.

  2. 2

    AI analytics

    An LLM-powered guide layers natural-language interaction on top of interactive maps, charts, and tables.

  3. 3

    Insight out

    You get answers, dashboards, and alerts you can act on — not just numbers.

About

데이터와통찰 — “Data and Insight” in Korean.

DATAWATONGCHAL (데이터와통찰) is Korean for “Data and Insight.” Our mission is simple: insight into the world through data — and put that insight in the hands of the people who need it most.

We start where data already exists but insight does not. Satellite imagery now covers every mine, crop belt and construction site on Earth — yet turning that coverage into something you can act on is still specialist work. Closing that gap is what datawaearth does, and the same approach extends to any domain where observation outpaces interpretation. Every product pairs interactive visualization with an AI analyst, so non-experts can read the data the way a specialist would.

Founder

The person behind datawatongchal.

Dongki Chung 정동기

Founder & CEO · Ph.D., Geospatial Information Engineering

LinkedIn ↗

15+ years of leadership in geospatial AI — drone and satellite imagery analysis, deep learning, and large-scale national R&D programs across agriculture, disaster monitoring, and infrastructure.

Previously Executive Director & Head of R&D at Innopam (2018–2024) and Head of R&D at Korea IMU (2012–2017). KOICA overseas volunteer for geospatial information (Dominican Republic, 2007–2009). Visiting Researcher, University of Calgary, Department of Geomatics Engineering (2005–2006).

Doctoral research at the University of Seoul focused on drone imagery and deep learning for automated wintering-vegetable acreage estimation — the direct foundation for the crop-condition work inside datawaearth.

Education
  • Ph.D., Geospatial Information Engineering — University of Seoul (2022)
  • M.S., Urban Engineering (Geospatial Information) — Gyeongsang National University (2006)
  • B.S., Civil Engineering — Gyeongsang National University (2003)
Selected national R&D
  • Hydrogen-fuel-cell drone & AI for crop monitoring and yield prediction — MOLIT (2023)
  • GeoAI imagery analysis service — Jeju Province (2023)
  • Automated detection of Jeju winter crops — NIA / AI Hub dataset (2023)
  • GeoAI urban change detection algorithms — Seoul Digital Foundation (2022)

Office

Find us at Seoul Startup Hub Gongneung.

Address

1F Coworking Space, Seoul Startup Hub Gongneung
27 Dongil-ro 174-gil, Nowon-gu
Seoul, Republic of Korea

한글 주소

서울특별시 노원구 동일로174길 27
1층 코워킹스페이스 (공릉동, 서울창업디딤터)

Open in Google Maps ↗

Approximate location — click the marker or “Open in Google Maps” for directions.

Get in touch

Talk to us.