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Alibaba Cloud Agriculture China Translated from Chinese

Jiage Tiandi (佳格天地)

Real-time Analytics · Risk Management

Jiage Tiandi needed a scalable way to turn satellite remote sensing, IoT telemetry, weather data, and agricultural expertise into usable operational intelligence. Traditional local data-center deployments were not meeting requirements for secure storage, elastic performance, remote operations, or rapid delivery of crop-risk and production insights to customers.

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Reported impact

Business outcome

Jiage Tiandi turned multi-source environmental data into a cloud service that can be delivered securely and maintained remotely across many customers. Alibaba Cloud lowered compute and storage costs, improved reliability and flexibility, and gave the company a base for expanding agricultural AI into adjacent land, emergency, and financial use cases.

  • Productivity Improvement
  • Risk Reduction
  • Scalability

Solution

Jiage Tiandi built its agricultural intelligence services on Alibaba Cloud to transform fragmented environmental data into production-ready AI applications. The company collects satellite remote-sensing imagery, IoT sensor signals, meteorological data, and agronomic knowledge, then fuses and analyzes them to produce spatial services for farmland protection, growth-cycle estimation, yield forecasting, disaster prediction, crop-protection advice, and harvest-timing recommendations. As customer scale grew, the team shifted core workloads to Alibaba Cloud ECS, RDS, and OSS so compute, databases, and data storage could be operated with stronger security, remote maintainability, and elastic scale than its previous local-machine-room model allowed. Jiage Tiandi also collaborated with Alibaba Cloud technical teams on visualization components and database work, which helped it extend the same data platform into land resources, emergency management, and financial-risk scenarios. The result is a cloud-native remote-sensing platform that makes agricultural decision support practical across widely distributed farmland.

Data flow

Satellite images, IoT telemetry, weather feeds, and agronomic data are collected into Jiage Tiandi's cloud platform, where they are fused, processed, and visualized on Alibaba Cloud infrastructure. The resulting predictions and recommendations are delivered to agricultural, land, emergency-management, and financial users for field planning and risk response.

Solution architecture

3 components · 2 layers
  1. Compute
    • Elastic Compute Service (ECS) Runs Jiage Tiandi's remote-sensing analytics and application services with elastic compute capacity.
  2. Storage
    • ApsaraDB RDS Stores structured agricultural and operational data used by the spatiotemporal intelligence platform.
    • Object Storage Service (OSS) Holds large remote-sensing and environmental datasets for downstream analysis and visualization.

Architecture clues

  • Cloud storage and databases are part of the production platform because remote-sensing workloads require both large object storage and structured serving layers.
  • Jiage Tiandi extends the same core intelligence stack beyond agriculture into land and financial scenarios.
  • The platform combines satellite, IoT, and weather signals instead of relying on a single agricultural data source.

Evidence from the source

Jiage Tiandi said it uses AI to collect, fuse, process, analyze, and visualize satellite remote sensing, IoT, and meteorological data to provide spatiotemporal services. (original: 基于人工智能技术，佳格天地通过将卫星遥感、物联网、气象等多源数据进行收集、融合、处理、分析及可视化展现，提供时空数据应用服务。)
Since 2015, Alibaba Cloud ECS, RDS, and OSS have reduced compute and storage cost and solved Jiage Tiandi's agile development, continuous delivery, cluster operations, and remote-maintenance needs. (original: 从2015年开始，我们与阿里云展开合作，阿里云的ECS、RDS、OSS等，降低了计算和存储的成本，解决了我们在实际产品研发、运维方面的敏捷开发、持续交付、集群运维的问题。)
The platform supports yield estimation, natural-disaster prediction, crop-protection suggestions, and harvest recommendations so farmers can plan work with data rather than only experience. (original: 能够为农民提供生长周期估算、产量预估、自然灾害预测、植保方案建议、最佳收割期推荐等服务。)
Transparency Evidence & methodology 75/100 reference value · 86% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence86%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability25/25
    12 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Alibaba Cloud

    佳格天地：科技赋能，让粮食安全更有保障

    First-party
    https://enterprise.aliyun.com/customer/jiagetiandi
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Region
    • Company size
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • Published on source page Apr 4, 2023 · Alibaba Cloud · First-party
    Open date source
Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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