5 Best APIs for Vegetation indices in Nigeria

We've analyzed and compared the top 5 API providers supporting Vegetation indices for Nigerian developers and businesses. Find the right infrastructure fit for your startup below.

Written by Editorial Staffs as at 5th August, 2026

All APIs with Vegetation indices

5 of 5 selected

Digital Earth Africa

Pricing
Free and open access — no subscription required; funded by African governments and international partners
Satellite imagery access
Available
Water body mapping
Available
Vegetation indices
Available
Land cover classification
Available
Coastline monitoring
Available
MODIS Data
Not available
Landsat Imagery
Not available
Vegetation Indices
Not available
Crop Type Maps
Not available
Global Coverage
Not available
Historical Archive
Not available
Real-time Updates
Not available
High Resolution
Not available
Free to Use
Not available
API Access
Not available
Weather Forecasts
Not available
Satellite Imagery
Not available
NDVI Index
Not available
EVI Index
Not available
Soil Moisture
Not available
Historical Data
Not available
Integration Tools
Not available
Crop Monitoring
Not available
Yield Prediction
Not available
Yield Maps
Not available
Field Analytics
Not available
Weather Data
Not available
Change Detection
Not available
Historical Analysis
Not available
Custom Alerts
Not available
Mobile Integration
Not available
Data Export
Not available
NDVI Satellite Imagery
Not available
Field Polygon Management
Not available
Historical Imagery
Not available
Weather Integration
Not available
Field Statistics
Not available

NASA Harvest / Earthdata

Pricing
Completely free. NASA public data with no usage fees.
Satellite imagery access
Not available
Water body mapping
Not available
Vegetation indices
Not available
Land cover classification
Not available
Coastline monitoring
Not available
MODIS Data
Available
Landsat Imagery
Available
Vegetation Indices
Available
Crop Type Maps
Available
Global Coverage
Available
Historical Archive
Available
Real-time Updates
Available
High Resolution
Available
Free to Use
Available
API Access
Available
Weather Forecasts
Not available
Satellite Imagery
Not available
NDVI Index
Not available
EVI Index
Not available
Soil Moisture
Not available
Historical Data
Not available
Integration Tools
Not available
Crop Monitoring
Not available
Yield Prediction
Not available
Yield Maps
Not available
Field Analytics
Not available
Weather Data
Not available
Change Detection
Not available
Historical Analysis
Not available
Custom Alerts
Not available
Mobile Integration
Not available
Data Export
Not available
NDVI Satellite Imagery
Not available
Field Polygon Management
Not available
Historical Imagery
Not available
Weather Integration
Not available
Field Statistics
Not available

Agromonitoring (Agro API)

Pricing
Paid. Per-call pricing. Free tier with limited polygons. Contact for enterprise rates.
Satellite imagery access
Not available
Water body mapping
Not available
Vegetation indices
Not available
Land cover classification
Not available
Coastline monitoring
Not available
MODIS Data
Not available
Landsat Imagery
Not available
Vegetation Indices
Available
Crop Type Maps
Not available
Global Coverage
Not available
Historical Archive
Not available
Real-time Updates
Available
High Resolution
Not available
Free to Use
Not available
API Access
Available
Weather Forecasts
Available
Satellite Imagery
Available
NDVI Index
Available
EVI Index
Available
Soil Moisture
Available
Historical Data
Available
Integration Tools
Available
Crop Monitoring
Available
Yield Prediction
Available
Yield Maps
Not available
Field Analytics
Not available
Weather Data
Not available
Change Detection
Not available
Historical Analysis
Not available
Custom Alerts
Not available
Mobile Integration
Not available
Data Export
Not available
NDVI Satellite Imagery
Not available
Field Polygon Management
Not available
Historical Imagery
Not available
Weather Integration
Not available
Field Statistics
Not available

EarthDaily Agro

Pricing
Paid enterprise pricing. Contact EarthDaily for rates. Not self-serve.
Satellite imagery access
Not available
Water body mapping
Not available
Vegetation indices
Not available
Land cover classification
Not available
Coastline monitoring
Not available
MODIS Data
Not available
Landsat Imagery
Not available
Vegetation Indices
Available
Crop Type Maps
Not available
Global Coverage
Not available
Historical Archive
Not available
Real-time Updates
Not available
High Resolution
Not available
Free to Use
Not available
API Access
Available
Weather Forecasts
Not available
Satellite Imagery
Not available
NDVI Index
Not available
EVI Index
Not available
Soil Moisture
Not available
Historical Data
Not available
Integration Tools
Not available
Crop Monitoring
Not available
Yield Prediction
Not available
Yield Maps
Available
Field Analytics
Available
Weather Data
Available
Change Detection
Available
Historical Analysis
Available
Custom Alerts
Available
Mobile Integration
Available
Data Export
Available
NDVI Satellite Imagery
Not available
Field Polygon Management
Not available
Historical Imagery
Not available
Weather Integration
Not available
Field Statistics
Not available

AgroMonitoring Satellite Imagery API

Pricing
Free tier: limited polygon area and API calls; paid plans for larger areas and higher call volumes
Satellite imagery access
Not available
Water body mapping
Not available
Vegetation indices
Not available
Land cover classification
Not available
Coastline monitoring
Not available
MODIS Data
Not available
Landsat Imagery
Not available
Vegetation Indices
Not available
Crop Type Maps
Not available
Global Coverage
Not available
Historical Archive
Not available
Real-time Updates
Not available
High Resolution
Not available
Free to Use
Not available
API Access
Not available
Weather Forecasts
Not available
Satellite Imagery
Not available
NDVI Index
Not available
EVI Index
Not available
Soil Moisture
Not available
Historical Data
Not available
Integration Tools
Not available
Crop Monitoring
Not available
Yield Prediction
Not available
Yield Maps
Not available
Field Analytics
Not available
Weather Data
Not available
Change Detection
Not available
Historical Analysis
Not available
Custom Alerts
Not available
Mobile Integration
Not available
Data Export
Not available
NDVI Satellite Imagery
Available
Field Polygon Management
Available
Historical Imagery
Available
Weather Integration
Available
Field Statistics
Available

← Swipe to compare all 5 APIs →

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Digital Earth Africa

Digital Earth Africa

Digital Earth Africa (DE Africa) is a continental-scale open data platform that makes analysis-ready satellite data freely accessible for the entire African continent, providing tools, datasets, and APIs that allow researchers, governments, NGOs, and developers to extract valuable insights from years of Earth observation imagery without requiring specialized remote sensing expertise or high-performance computing infrastructure. Backed by African governments and international development partners including the African Union, Digital Earth Africa addresses the fundamental challenge that satellite data — while publicly available — historically required substantial technical expertise and computing resources to process, making it inaccessible to most African organizations. The DE Africa platform is built on the Open Data Cube framework and exposes satellite datasets as analysis-ready datacubes where each pixel contains atmospherically corrected, geometrically accurate surface reflectance values aligned across time. This means Nigerian data scientists and environmental analysts can query pixel-level time series data across Nigerian territory without the complex preprocessing normally required for raw satellite imagery. The Python API enables querying: "Show me the vegetation index (NDVI) for all farmland pixels in Kano State for every July from 2015 to 2025" — a query that would previously require months of data processing. Water monitoring datasets from DE Africa include the Water Observations from Space (WOfS) dataset, which classifies every pixel in Africa as water or non-water based on Landsat and Sentinel-2 imagery analysis. For Nigerian flood monitoring platforms, this dataset provides historical flood extent mapping across Nigeria — enabling analysis of which areas in the Niger Delta, Benue Valley, and Sokoto Rima floodplains are repeatedly inundated and need permanent flood risk classification. The Waterbodies dataset monitors changes in the extent of lakes, reservoirs, and rivers over time. Vegetation and land cover datasets support Nigerian agricultural and environmental monitoring. The Annual Crop Mask dataset classifies agricultural land across Africa, allowing Nigerian agricultural agencies to estimate cropland extent by state and track year-on-year changes in agricultural land use. The Fractional Cover dataset quantifies the proportion of bare soil, green vegetation, and non-green vegetation in each pixel, useful for monitoring rangeland health in the Sahel portions of northern Nigeria and detecting land degradation. Coastline monitoring data from the Continental Coastlines dataset maps the African shoreline and tracks changes over time due to erosion, sedimentation, and sea-level effects. Nigeria's Atlantic coastline in the Niger Delta region is subject to intense erosion pressures due to oil infrastructure, wave action, and reduced sediment supply. Nigerian coastal management agencies and environmental researchers can use DE Africa coastline data to quantify erosion rates and identify the most vulnerable coastal communities. The DE Africa Sandbox provides a browser-based Jupyter notebook environment where Nigerian developers and analysts can explore datasets, run Python code against the datacube API, and visualize results without any local installation. This browser-accessible development environment lowers the barrier to entry for Nigerian universities, research institutes, and NGOs that want to experiment with satellite data analysis without infrastructure investment. Digital Earth Africa data and platform access are entirely free, funded as a public good by African governments and international partners. Nigerian government agencies, universities, research institutes, and civil society organizations can access all datasets without subscription fees, supporting evidence-based environmental management, agricultural policy, and climate adaptation planning across Nigeria.

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NASA Harvest / Earthdata

NASA Harvest / Earthdata

NASA Harvest and NASA Earthdata together form a satellite-based agricultural monitoring and data access ecosystem managed by NASA, providing researchers, governments, development organizations, and food security analysts with access to Earth observation data products specifically designed to support agricultural monitoring, crop assessment, and food security analysis globally, with particular programs focused on African agricultural systems including Nigeria. NASA Earthdata is the overarching data access portal for all NASA Earth observation data, providing a unified discovery and download interface — including programmatic API access — to the complete archive of NASA satellite data products across all Earth science domains. For agricultural applications, the most relevant Earthdata products include MODIS vegetation indices (NDVI and EVI at 250m and 500m spatial resolution), Landsat surface reflectance imagery at 30m resolution, SMAP soil moisture, GRACE groundwater anomalies, and various derived land cover and crop area products. The Earthdata API allows programmatic search, filter, and bulk download of these datasets covering Nigeria and all global agricultural regions. NASA Harvest is a specific program within the NASA Earth Applied Sciences Division focused on food security and agriculture. Led by the University of Maryland, NASA Harvest develops applied satellite-based monitoring tools for national-level crop assessment and food security analysis, with particular expertise in sub-Saharan Africa. NASA Harvest products include seasonal crop monitoring bulletins, crop area mapping for key countries, and research tools for improving crop production estimation using satellite data. The MODIS vegetation index products available through Earthdata — specifically MOD13Q1 and MYD13Q1 at 250m resolution with 16-day compositing — provide global time series of NDVI and EVI extending back to 2000. For Nigerian agricultural research, this 24+ year time series enables long-term analysis of vegetation condition trends, identification of multi-year drought signatures, and assessment of land degradation and agricultural expansion patterns across Nigerian agricultural zones. These historical baselines are essential for contextualizing current-season conditions relative to historical norms. Landsat imagery at 30m resolution and 16-day revisit provides detailed land cover analysis capability for Nigeria, enabling crop type mapping, agricultural area estimation, field boundary delineation, and land use change monitoring at scales relevant to individual farm fields. Nigerian government agencies building land cadastre systems, research programs mapping the extent of specific crop cultivation, and environmental organizations monitoring agricultural frontier expansion can use Landsat data through the Earthdata API for these applications. SMAP (Soil Moisture Active Passive) satellite data, accessible through Earthdata, provides global soil moisture estimates at approximately 9-36km spatial resolution. Soil moisture is the primary driver of rain-fed crop water stress across Nigeria's agricultural zones, and SMAP data allows monitoring of soil water conditions throughout the growing season. When SMAP shows below-average soil moisture across a major Nigerian agricultural zone during the critical crop growth period, this provides early warning of potential yield depression before satellite vegetation indices reflect the stress. The Earthdata programmatic API allows developers to search the entire NASA data catalog using spatial (bounding box or polygon), temporal, and product name filters, then download matched granules programmatically. For Nigerian research applications requiring large volumes of satellite data — multi-year time series, multi-sensor analysis, multi-region comparison studies — the API-based bulk download capability is essential for assembling the datasets needed without manual browsing and downloading of individual files through web interfaces.

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Agromonitoring (Agro API)

Agromonitoring (Agro API)

The Agromonitoring Agro API is a satellite-based crop monitoring and agricultural weather API developed by the OpenWeather team, providing farm field monitoring through satellite imagery analysis and integrated meteorological data. The platform is specifically designed for agritech developers and precision agriculture application builders who need to combine satellite vegetation health monitoring with weather intelligence in a single API integration, covering registered farm field polygons across Nigeria and globally. The Agro API centers on a field polygon management system: developers register farm field boundaries as GeoJSON polygons through the API, and the platform automatically monitors those fields with available satellite imagery, computing vegetation indices and weather observations for each registered location. This automated monitoring eliminates the need for agritech developers to manage satellite data pipelines, handle image processing, or schedule individual imagery requests — the platform handles all of this automatically for registered fields. NDVI (Normalized Difference Vegetation Index) is the primary crop health metric delivered by Agromonitoring. NDVI values derived from satellite imagery measure green vegetation density and are directly related to crop biomass and canopy health. For Nigerian farms monitoring maize, cassava, rice, sorghum, or vegetable crops, seasonal NDVI time series track the crop growth curve from emergence through canopy closure and eventually senescence. The Agro API provides NDVI statistics — mean, minimum, maximum, and standard deviation — for each registered field at each available satellite observation date. Beyond NDVI, Agromonitoring provides EVI (Enhanced Vegetation Index) and NRI (Normalized Red Index) for crop condition assessment. EVI is less sensitive to atmospheric effects and soil background than NDVI, making it more reliable in conditions with high aerosol loading — a consideration for northern Nigerian zones where harmattan dust can affect optical satellite observations. Providing multiple indices allows Nigerian agritech developers to select the most appropriate measure for their specific crop monitoring context. The satellite imagery underlying Agromonitoring's vegetation indices comes from Landsat-7, Landsat-8, Sentinel-2, and MODIS constellations, providing a range of spatial and temporal resolution options. Sentinel-2's 10-meter resolution and approximately 5-day revisit provides detailed field-level monitoring with high temporal frequency. Landsat's 30-meter resolution and 16-day revisit offers coarser but longer historical coverage. MODIS at 250-500 meter resolution provides rapid updates for broad-area monitoring. Applications can access imagery from multiple sensors through the same API, selecting the sensor appropriate for each monitoring need. Weather data integration within the Agro API provides agricultural meteorological intelligence for each registered field location: current conditions, hourly and daily forecasts, and historical weather records. Precipitation data, temperature, wind speed, humidity, and solar radiation are available for field coordinates, enabling correlation of crop health observations with weather history and providing agricultural decision support that goes beyond vegetation index monitoring alone. Soil data endpoints within Agromonitoring provide estimated soil temperature and soil moisture for field locations, derived from models that combine weather observations with soil property information. For Nigerian farmers making planting timing decisions or irrigation management choices, soil condition data alongside crop health monitoring provides a more complete agronomic picture than either data type alone. For Nigerian precision agriculture companies building commercial farm management products, Agromonitoring provides a cost-effective API starting point with a free tier that covers limited field area, allowing proof-of-concept development and early customer pilots without initial API costs. As commercial scale grows, paid tiers accommodate larger field portfolios and higher API call volumes. The OpenWeather backing provides confidence that the platform has stable commercial infrastructure and developer support resources that align with the needs of Nigerian agritech companies building products they intend to scale.

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EarthDaily Agro

EarthDaily Agro

EarthDaily Agro is the precision agriculture data intelligence platform from EarthDaily Analytics, providing field-level crop monitoring, agronomic analytics, and agricultural intelligence derived from high-frequency, high-resolution satellite imagery. EarthDaily Agro is designed for agribusinesses, commodity trading firms, agricultural insurance companies, and agritech developers that require enterprise-grade crop intelligence for operational decisions involving significant financial stakes. The satellite data foundation of EarthDaily Agro is the EarthDaily Constellation — a network of small satellites operating in low Earth orbit designed to image the Earth's entire land surface at 3-5 meter resolution daily, cloud permitting. This daily imaging cadence is a step change from the 5-16 day revisit typical of government satellite constellations like Sentinel-2 and Landsat. For agricultural monitoring where crop stress, pest outbreaks, and weather events can dramatically change field conditions within days, daily satellite imagery means that problems are detected much faster than with weekly or biweekly revisit systems. Vegetation monitoring products from EarthDaily Agro deliver NDVI, EVI, and NDWI at field level with daily temporal resolution where cloud cover allows, providing near-real-time crop health tracking. For Nigerian commercial farms where management teams need to act quickly on crop stress signals — ordering irrigation, dispatching spray equipment, alerting field staff to investigate — daily satellite monitoring dramatically reduces the lag time between a crop problem developing and the monitoring system detecting it. Field-level analytics in EarthDaily Agro aggregate satellite observations into actionable field health metrics rather than requiring users to interpret raw imagery. Crop stress indexes, phenological stage indicators (estimating where in the crop growth cycle a field currently is based on vegetation index time series shape), and yield potential indicators provide farm managers and agronomists with synthesized intelligence that directly informs management decisions without requiring remote sensing expertise. For Nigerian large-scale commercial farming operations — the rice estates in Kebbi and Niger States, large maize and soybean operations in the middle belt, plantation-scale oil palm in Rivers and Cross River States — EarthDaily Agro's enterprise monitoring capabilities match the scale and sophistication of operations where precision management decisions can affect many thousands of hectares and the associated commodity value. Daily monitoring at this scale is economically justified by the production values at risk and the management improvements precision data enables. Agricultural commodity trading firms sourcing Nigerian agricultural products use EarthDaily Agro for crop condition intelligence that informs procurement strategy. Understanding crop health and yield outlook for major sourcing regions during the growing season allows traders to make informed decisions about forward contract volumes, delivery scheduling, and price discovery — weeks before harvest outcomes become publicly visible through production reports. This information advantage has direct financial value in commodity markets. Agricultural insurance underwriting and claims assessment is a high-value use case for EarthDaily Agro's daily satellite monitoring. Insurance companies offering yield-based or damage-based agricultural insurance to Nigerian farmers can use satellite monitoring to assess crop condition continuously throughout the insured period, identify claims-worthy events (drought stress, flooding, pest damage patterns visible from space) objectively, and support or challenge claim submissions with satellite evidence. This objective, cost-effective claims assessment approach reduces both fraudulent claims and legitimate claims that are denied due to inability to verify damage at scale. Supply chain deforestation compliance — required for agricultural commodity exporters under the EU Deforestation Regulation — benefits from EarthDaily Agro's continuous monitoring capability. For Nigerian cocoa and palm oil supply chains subject to EUDR, high-frequency satellite monitoring of source farm locations provides the continuous observation record needed to demonstrate that no deforestation occurred at or around sourcing locations throughout the monitoring period.

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AgroMonitoring Satellite Imagery API

AgroMonitoring Satellite Imagery API

The AgroMonitoring Satellite Imagery API (also known as the Agro API) is a precision agriculture data platform developed by the team behind OpenWeatherMap, combining satellite-based vegetation monitoring with integrated weather data to deliver field-level crop health insights to agritech developers. By registering farm field polygons with the API, agricultural applications can access regular NDVI-based crop monitoring imagery, field statistics, and weather integration for every registered field with minimal development effort. The field polygon management model is the foundation of AgroMonitoring's workflow. Developers upload farm field boundaries as GeoJSON polygons — the standard format for geographic feature representation — and the API begins monitoring each registered field automatically. As satellite passes occur and clear imagery is available for a field's location, vegetation index calculations are performed and stored, building a time-series of field health data without any per-query scheduling required. Nigerian farms registered through an agritech app built on AgroMonitoring accumulate satellite observation records automatically throughout the growing season. NDVI (Normalized Difference Vegetation Index) is the primary vegetation health metric delivered by AgroMonitoring. NDVI quantifies green vegetation density from satellite spectral measurements, with higher values indicating healthier, denser crop canopy. For Nigerian farmers growing maize, cassava, rice, sorghum, or vegetables, NDVI tracking over the growing season provides a quantitative record of crop development — a healthy crop shows steadily increasing NDVI through vegetative growth stages, plateauing at canopy closure, and declining as senescence begins. Deviations from the expected seasonal NDVI curve indicate stress events that warrant investigation. The API also delivers EVI (Enhanced Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index) in addition to NDVI, providing alternative vegetation indices that may perform better in specific conditions. SAVI accounts for soil background reflectance, making it more accurate in Nigerian fields with partial crop cover, sparse canopy, or significant bare soil exposure early in the season. Having multiple vegetation indices available allows agritech platforms to select the metric most appropriate for their specific use case and crop types. Weather data integration through AgroMonitoring connects satellite observations with meteorological context. For each registered field, the API provides current conditions and forecasts based on field coordinates, and historical weather records that can be correlated with NDVI time series. When satellite imagery shows NDVI declining in a specific Nigerian field, correlating the timing with recent rainfall data helps distinguish drought stress from disease-related stress from flooding damage — each requiring different agricultural management responses. Historical satellite imagery access allows agritech platforms to retrieve imagery and vegetation indices for registered fields from past dates, enabling multi-season comparisons. A Nigerian farm management platform can show users their current-season NDVI map alongside the same field's NDVI from the prior two or three seasons, providing context for evaluating whether current field health is above or below historical norms. Fields that consistently underperform in a specific area within the polygon may indicate a structural soil or drainage issue worth investigating. Field statistics from AgroMonitoring summarize vegetation conditions across an entire field with mean, minimum, maximum, and standard deviation metrics for each vegetation index. For Nigerian agricultural applications displaying field health to users who may not have image interpretation skills, these statistical summaries provide actionable numbers — a field health score or percentile ranking — that communicate overall status clearly without requiring raw imagery display. The API includes soil moisture estimates derived from satellite data for registered fields, complementing vegetation health monitoring with a crop water status indicator. Soil moisture data is particularly important in Nigeria's northern farming zones where seasonal water deficit is a primary yield-limiting factor, and where timely irrigation decisions can be the difference between good and poor harvests. AgroMonitoring is accessible through a REST API with JSON responses, supported by documentation and code examples. The API is compatible with any HTTP client, making integration feasible for Nigerian developers working in Python, JavaScript, PHP, or any other language. The free tier with limited field area and API calls allows Nigerian agritech developers to build and test applications before committing to paid plans scaled for commercial deployment.