NDVI observations for Common and Winter Wheat, Maize and Soybean – Adige River-Fed Downstream Irrigated Plain, 2022

Demonstration Case Name
Multi-Hazards in the Downstream Area of the Adige River Basin.

Dataset Name/Title
NDVI observations for Common and Winter Wheat, Maize and Soybean – Adige River-Fed Downstream Irrigated Plain, 2022

Dataset Description

NDVI (Normalized Difference Vegetation Index) and Bare Soil Index (BSI) observations at the crop field level for Common and Winter Wheat, Maize, and Soybean. The dataset contains one row per crop field representing the average crop field NDVI, covering 10 distinct dates between March 9 and August 26, 2022. All observations are located in a plain area that relies on the Adige River for cropland irrigation, and are integrated with Hydrologic Soil Group data. 

Dataset column names:

id

crop_type

HSG: Hydrologic Soil Group

area_sqm: crop field area in square meters

avg_ndvi_YYYYmmdd: average crop field NDVI for the specific date (e.g., 2022 March 9, 20220309)

avg_bsi_YYYYmmdd: average crop field BSI for the specific date (e.g., 2022 March 9, 20220309)

Key Methodologies

Crop field-level NDVI values were calculated by averaging pixel-level NDVI derived from Sentinel-2 L2A observations within the irrigated districts fed with the Adige River waters (data courtesy of ANBI Veneto). Crop field-level NDVI values were linked to specific crops using in situ crop type information (data obtained from Regional Local Agencies). The observations in the dataset result from a multi-step data cleaning process. Raw observations were excluded if more than 50% of their pixels were unavailable e.g., due to cloud cover; remaining observations were filtered using a Bare Soil Index (BSI) threshold of 0.08 (Mzid et al., 2021), to distinguish vegetated from non vegetated (soil) pixels. Finally, fields associated with alternating crops required further processing, in order to disentangle double entries and assure that the satellite observation referred to the correct crop. Temporal NDVI profiles were inspected to identify two green-up periods separated by at least one observation identified as bare soil (BSI > 0.08). To disentangle alternating crop field, the following assumptions were made: if soybean was one of the reported crops, the vegetation period following the bare-soil break was attributed to soybean, while the preceding growth phase was assigned to the initial crop (e.g., winter wheat or maize); in cases where no double cropping was reported but a second green-up phase was evident, it was assumed to result either from an unreported second crop or from spontaneous vegetation regrowth after harvesting. In such instances, only observations preceding the bare-soil interval and considered relevant to the declared crop growing season were retained for analysis. 

Temporal Domain
2022

Spatial Domain
The dataset is provided over the [10.7, 45.0, 12.3, 45.6] spatial domain (min longitude, min latitude, max longitude, max latitude in WGS84, EPSG:4326).

Key Variables/Indicators
Normalized Difference Vegetation Index (NDVI); Bare Soil Index (BSI)

Data Format
csv

Source Data

NDVI and BSI were obtained from ESA Copernicus Sentinel-2 L2A

Crop field level information on farmer declared crop were obtained from the Veneto Agency for Payments in Agriculture (AVEPA, Agenzia Veneta per i Pagamenti, https://www.avepa.it/web/avepa)

Hydrologic Soil Group at 1:250000 scale data were obtained from the Agenzia Regionale per la prevenzione e protezione ambientale Veneto (ARPAV, Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto - Regional Agency for Environmental Prevention and Protection of Veneto, https://www.arpa.veneto.it/), and follow the classification scheme outlined in USDA National Engineering Handbook (USDA-NRCS, 2009)

Irrigated districts were provided by courtesy of ANBI Veneto (Associazione Nazionale Bonifiche Irrigazioni - National Association of Land Reclamation and Irrigation)

Accessibility
https://doi.org/10.5281/zenodo.15189872

Stakeholder Relevance
The NDVI is a valuable indicator of vegetation health due to its ability to capture chlorophyll activity and biomass dynamics through the differential reflectance between red and near-infrared wavelengths. This index is widely recognized for its robustness in monitoring vegetation vigor, phenological stages, and crop stress. Associating field-level NDVI values with specific crops may enable the identification of patterns linked to co-occurring natural hazards, such as extreme dry and hot events. Moreover, the availability of information on soil hydraulic properties (retrieved from the Hydrologic Soil Group) allows for the identification of relationships between crop average NDVI values and soil properties, potentially allowing for adaptation strategies related to crop performance during dry and hot events. The reliability of the dataset has been further enhanced through a dedicated data cleaning methodology, allowing to distinguish between vegetated and non vegetated crop fields as well as identifying alternating crops.   

Limitations/Assumptions
In cases where a field was associated with more than one crop, a disaggregation technique was applied based on assumptions about crop growth phases. 

Additional Outputs/Information
The dataset access is currently restricted due to pending related publication.

Contact Information
Albergo, Edoardo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data curatorFurlanetto, Jacopo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data curatorMasina, Marinella (CMCC Foundation - Euro-Mediterranean Center on Climate Change)- Data curatorMaraschini, Margherita (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorFerrario, Davide Mauro (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorTorresan, Silvia (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data manager

示范案例名称：阿迪杰河下游流域多灾种

数据集名称/标题：2022年阿迪杰河下游灌溉平原普通小麦、冬小麦、玉米及大豆归一化植被指数观测数据

数据集描述

本数据集包含普通小麦、冬小麦、玉米与大豆的田块级归一化植被指数（Normalized Difference Vegetation Index, NDVI）及裸土指数（Bare Soil Index, BSI）观测值。每个田块对应一行数据，记录该田块的平均NDVI，覆盖2022年3月9日至8月26日期间的10个独立观测日期。所有观测数据均位于依赖阿迪杰河进行农田灌溉的平原区域，并整合了水文土壤组（Hydrologic Soil Group, HSG）数据。

数据集列名：

id
作物类型（crop_type）
HSG：水文土壤组（Hydrologic Soil Group）
area_sqm：以平方米为单位的田块面积
avg_ndvi_YYYYmmdd：对应日期的田块平均NDVI（例如2022年3月9日对应20220309）
avg_bsi_YYYYmmdd：对应日期的田块平均BSI（例如2022年3月9日对应20220309）

关键方法

田块级NDVI值通过对阿迪杰河灌溉灌区范围内的Sentinel-2 L2A观测影像的像素级NDVI取平均计算得到（数据由ANBI Veneto提供）。利用田间实测作物类型信息（由地区地方机构获取），将田块级NDVI值与具体作物进行关联。本数据集的观测值经过多步数据清洗流程得到：若某条观测数据中超过50%的像素不可用（例如因云覆盖导致），则将其剔除；剩余观测数据通过阈值为0.08的裸土指数（Mzid et al., 2021）进行过滤，以区分植被与非植被（土壤）像素。针对轮作田块，需进一步处理以拆分重复条目，确保卫星观测对应正确的作物类型。通过检查时间序列NDVI曲线，识别出至少被一个裸土观测（BSI>0.08）分隔的两个返青期。针对轮作田块，采用如下假设：若报告的作物包含大豆，则裸土间隔后的植被生长期归为大豆，而此前的生长阶段归为初始作物（例如冬小麦或玉米）；若未报告复种但存在第二个返青期，则认为该现象由未报告的第二季作物或收获后自发植被再生导致。此类情况下，仅保留裸土间隔前与目标作物生长期相关的观测数据用于分析。

时间范围
2022年

空间范围
本数据集的空间范围为WGS84（EPSG:4326）坐标系下的[10.7, 45.0, 12.3, 45.6]（最小经度、最小纬度、最大经度、最大纬度）。

关键变量/指标
归一化植被指数（NDVI）；裸土指数（BSI）

数据格式
csv

源数据

NDVI与BSI数据来自欧洲空间局哥白尼计划（ESA Copernicus）的Sentinel-2 L2A产品
农户申报的田块作物类型信息来自威尼托农业支付局（AVEPA, Agenzia Veneta per i Pagamenti, https://www.avepa.it/web/avepa）
1:25万比例尺的水文土壤组数据来自威尼托区域环境预防与保护局（ARPAV, Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto - 威尼托大区环境预防与保护署, https://www.arpa.veneto.it/），其分类方案遵循美国农业部国家工程手册（USDA-NRCS, 2009）
灌溉灌区数据由ANBI Veneto（全国土地复垦与灌溉协会, Associazione Nazionale Bonifiche Irrigazioni）友情提供

可访问性
https://doi.org/10.5281/zenodo.15189872

利益相关方相关性

归一化植被指数（NDVI）能够通过红光与近红外波段的反射差异捕捉叶绿素活性与生物量动态，是评估植被健康状况的重要指标。该指数因在监测植被活力、物候期与作物胁迫方面的稳健性而被广泛认可。将田块级NDVI值与具体作物关联，可用于识别与协同发生的自然灾害（如极端干热事件）相关的模式。此外，通过水文土壤组获取的土壤水力属性信息，能够揭示作物平均NDVI值与土壤属性之间的关联，进而为干热事件下的作物生产适应性策略提供支撑。本数据集通过专属的数据清洗方法进一步提升了可靠性，能够区分植被与非植被田块，并识别轮作田块。

局限性/假设

当某田块关联多种作物时，将基于作物生长阶段的假设采用拆分技术进行处理。

额外输出/信息

本数据集目前因相关出版物待发表而受限访问。

联系方式

Albergo, Edoardo（CMCC基金会——地中海气候变化中心、国家生物多样性未来中心）——数据管理员
Furlanetto, Jacopo（CMCC基金会——地中海气候变化中心、国家生物多样性未来中心）——数据管理员
Masina, Marinella（CMCC基金会——地中海气候变化中心）——数据管理员
Maraschini, Margherita（CMCC基金会——地中海气候变化中心）——数据管理员
Ferrario, Davide Mauro（CMCC基金会——地中海气候变化中心）——数据管理员
Torresan, Silvia（CMCC基金会——地中海气候变化中心、国家生物多样性未来中心）——数据经理