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独自のインデックスを作成する方法: Googleスプレッドシートを活用した簡単ガイド

November 28, 2024December 3, 2024 yuichiro

本記事では、地域の監視に役立つ独自のインデックスを作成する方法をご紹介します。ビデオによる説明は以下よりご覧いただけます、

メール登録

はじめに、Googleアカウントを用意してください。アカウントを作成またはログインしたら、登録用ウェブサイトにアクセスしサインアップしてください。

サインアップが完了すると、Googleスプレッドシートへのリンクが提供されます。このスプレッドシートは、インデックスの設定に使用します。

Googleスプレッドシートの編集

スプレッドシートをコピーする

まず、Googleスプレッドシートをコピーします。リンクにアクセスして、「コピーを作成」ボタンをクリックしてください。

シートから地域を抽出する

次に、QUERY関数を使用してシートからデータを抽出します。この関数を使用すると、スプレッドシート内のデータをフィルタリングおよびソートできます。

図3: `QUERY`関数を使用してインデックス用のデータを抽出（例: 「Australia」と「Queensland」でフィルタリング）

例えば、以下のようなQUERY関数を使用します：

SELECT C, D WHERE B = 'Australia' AND C LIKE '%Queensland%'

この場合、以下の結果が得られます：

スプレッドシートを公開する

ウェブに公開

スプレッドシートをCSV形式でウェブに公開します。

公開後、以下のようなURLが提供されます：

https://docs.google.com/spreadsheets/d/e/2PACX-xxxxxxxx/pub?gid=16********&single=true&output=csv

ここで：

2PACX-xxxxxxxx はスプレッドシートID
16******** はシートIDです。

独自のインデックスURLを作成する

最後に、以下の形式に基づいて独自のインデックスURLを作成します：

https://otani.co/crops/spring-wheat/NDVI/<インデックス名>/?sid=<スプレッドシートID>&gid=<シートID>

例えば、Spring Wheat / NDVIインデックスの名前が**「QLD, AU」**で、スプレッドシートIDが2PACX-xxxxxxxx、シートIDが16********の場合、URLは次のようになります

https://otani.co/crops/spring-wheat/NDVI/QLD,AU/?sid=2PACX-xxxxxxxx&gid=16********

これにより、同じデータに異なる名前でアクセスできます（例: QLD, AUまたはQueensland, Australia）。

結論

以上で、Googleスプレッドシートを使った独自のインデックス作成方法の説明を終わります。このガイドが役に立てば幸いです。ご不明点があれば、お気軽にお問い合わせください。

How to Build Your Own Index (Dashboard): A Step-by-Step Guide Using Google Spreadsheets

November 28, 2024December 3, 2024 yuichiro

In this post, we will guide you through creating your own index to monitor regions of interest effectively. A link to youtube video is provided below.

Email registration

To get started, you need a Google account. Once you’ve created or logged into your account, visit the registration website and sign up for the index.

After signing up, you will receive a link to a Google Spreadsheet. This spreadsheet will serve as your configuration.

Edit a google spreadsheet

Copy the Google Spreadsheet

First, make a copy of the Google Spreadsheet. Visit the provided link and click the “Make a copy” button.

Extract Regions from the Sheet

Next, extract regions from the sheet using the QUERY function. The QUERY function enables you to filter and sort data in the spreadsheet.

Figure 3: Extract data for your index using the QUERY function (e.g., filtering data for “Australia” and “Queensland”)

For example, a QUERY function like this:

SELECT C, D WHERE B = 'Australia' AND C LIKE '%Queensland%'

might return:

Publishing Your Spreadsheet

Publish to the Web

Publish your spreadsheet to the web in CSV format.

Once published, you will receive a URL like this:

https://docs.google.com/spreadsheets/d/e/2PACX-xxxxxxxx/pub?gid=16********&single=true&output=csv

Here:

2PACX-xxxxxxxx is the spreadsheet ID.
16******** is the sheet ID.

Developing Your Own Index URL

Finally, create a URL for your custom index using the following format:

https://otani.co/crops/spring-wheat/NDVI/<your own index name>/?sid=<spreadsheet id>&gid=<sheet id>

For example, if your Spring Wheat / NDVI index is named “QLD, AU“, with the spreadsheet ID 2PACX-xxxxxxxx and sheet ID 16********, the URL would be:

https://otani.co/crops/spring-wheat/NDVI/QLD, AU/?sid=2PACX-xxxxxxxx&gid=16********

This allows you to access the same data with different names, such as QLD, AU and Queensland, Australia.

Conclusion

That’s it! You’ve successfully built your own index using a Google Spreadsheet. We hope this guide has been helpful. For any questions, please feel free to contact us.

春小麦植生インデックス

November 26, 2024November 26, 2024 yuichiro

春小麦植生インデックス

春小麦植生指数は、正規化差分植生指数（NDVI）を用いて春小麦の生産性をモニタリングし、潜在的な収穫量を示すために設計された10日間隔の指数です。本インデックスは、春小麦の地上部総生産量（TAGP）を観測した地域を対象としています。データは0.1°×0.1°（緯度経度）のグリッドで表示され、全ての値はNDVIの平均値を表します。選択された地域のインデックスは指定されたページで提供されています（URLは本ページ下部に記載）。

グリッド

すべてのグリッドはコペルニクスから取得したTAGPデータに基づいており北半球と南半球にまたがっています。2020年7月以降の春小麦のTAGP（Total Above Ground Production）観測データを用いて30,000以上のグリッドを生成しています。各グリッドのサイズは0.1°×0.1°で、およそ12.5km×12.5kmです。各グリッド内には約1,000個のNDVIグリッドが含まれます。NDVIグリッドのサイズは500 m x 500 mです。

インデックス

春小麦植生インデックスは特定の日付におけるTAGPグリッド内のNDVIの平均値です。この平均NDVI値を春小麦の地上部総生産性の指標と考えます。各平均NDVI値は、2020年7月から2024年10月まで観測されたTAGPグリッドに基づいて計算されています。なお、インデックスは2020年7月からデータを提供しています。

以下の図 1 に示すように、春小麦の生育期には、NDVI の平均値は増加する傾向にあり、地上部の総生産性と相関しています。この散布図は、TAGPとNDVIを緯度と経度でグループ化し、TAGPの値を対数（自然対数）に変換したものでです。それぞれの地域でTAGP値が最大値から4番目の値より小さい期間を生育ステージとしています。相関型の違いはより考慮する必要がありますが、平均NDVI値は春小麦の収穫量を示す指標として役立ちます。

Figure 1 : Scatter plot of logged TAGP vs NDVI mean during the growing stage.

Indices for Selected Regions

各地域の指標は、以下のようなページで提供されています。

Gnowangerup, Western Australia, Australia

Beneath the vast Australian sky, the golden fields of Gnowangerup stretch towards the horizon, a testament to the region’s rich agricultural heritage and the resilience of its farmers.

Lower Eyre Peninsula, South Australia, Australia

A bountiful harvest of golden grain under the vast Australian sky.

Ararat, Victoria, Australia

Golden fields swaying under the Australian sun, a testament to the Ararat region’s bountiful spring wheat harvest.

La Pampa, Argentina

Across the boundless pampas, golden waves of wheat ripple in the wind, a symbol of Argentina’s rich agricultural heritage and the tireless work of its farmers.

South Africa

Beneath the vast African sky, golden fields shimmer, a testament to the resilience and agricultural prowess of South Africa’s farmers.

México

Beneath the vibrant Mexican sun, golden fields stretch across the landscape, a testament to the nation’s resilient spirit and agricultural bounty.

各ページの左上（または一番上）に表示されている値は、そのページに表示されているエリア全体のインデックスを集計したものです。この値は、サブエリアの個々のインデックス値の平均ではなく、エリア内のすべてのNDVIグリッドの平均NDVIとして計算しています。

例えば、以下のラ・パンパ（アルゼンチン）のページでは、全 86 グリッドの平均値は 0.38（2024年11月1日現在）と表示されています。

この値は、ラ・パンパの86,000以上のNDVIグリッドポイントに基づいており、個別に記載されている86のサブエリア指数（例えば、0.36、0.33、0.41）ではありません。

ダウンロード

インデックスデータは、エリアページからCSV、PNG、SVG形式でダウンロードできます。

引用

このデータを引用または利用する場合は、以下のAttributionまたはhtmlコードをお使いください。

Attribution

Otani & Co., Inc. Spring Wheat / NDVI Index. https://otani.co/docs/crop-spring-wheat-ndvi/

HTML

<a target="_blank" href="https://otani.co/docs/crop-spring-wheat-ndvi/">Spring Wheat / NDVI Index.</a>

Data Source

“European Union’s Copernicus Land Monitoring Service information; NDVI and Spring Wheat Total Above Ground Producton”

データやアプリケーションのカスタマイズについては、このページのフォームを使用してお問い合わせください。

Spring Wheat / NDVI

November 20, 2024November 25, 2024 yuichiro

Spring Wheat / NDVI

The Spring Wheat / NDVI index is a 10-day interval index designed to monitor spring wheat productivity and estimate potential harvests using the Normalized Difference Vegetation Index (NDVI). The index covers areas observed for Total Above Ground Productivity (TAGP) of spring wheat. Data is presented on grids sized 0.1° x 0.1° (latitude and longitude), with all values representing the mean NDVI values. Aggregated indices for selected areas are provided on designated pages, with URLs listed at the bottom of this page.

Grids

All grids are based on TAGP data retrieved from Copernicus, spanning the northern and southern hemispheres. Over 30,000 grids have been generated using TAGP observations of spring wheat since July 2020. Each grid measures 0.1° x 0.1°, approximately equivalent to 12.5 km x 12.5 km. Within each TAGP grid, approximately 1,000 NDVI grids are included, each measuring 500 m x 500 m. The NDVI data is also sourced from Copernicus.

Index

The Spring Wheat / NDVI index values are averages of NDVI within a given TAGP grid at specific times. Each mean NDVI value is calculated based on TAGP grids observed from July 2020 to October 2024, and the time-series data from July 2020 is provided. This average NDVI value is considered an indicator of total above-ground productivity for spring wheat.

As illustrated in the figure 1 below, during the growing stage of spring wheat, the mean value of NDVI tends to increase and correlate to total above-ground productivity. This scatter plot is developed by the process tha TAGP and NDVI are grouped by latitudes and longitude and the values of TAGP are converted into logged values (natural logarithm). The definition of the growing stage in the grouped area is the period that the TAGP value is less than the fourth value from its maximum. Although the difference of correlation types should be more in consideration, the average NDVI value serves as a straightforward and accessible indicator of spring wheat productivity.

Indices for Selected Areas

Indices for selected areas are provided on specific pages, such as:

Gnowangerup, Western Australia, Australia

Beneath the vast Australian sky, the golden fields of Gnowangerup stretch towards the horizon, a testament to the region’s rich agricultural heritage and the resilience of its farmers.

Lower Eyre Peninsula, South Australia, Australia

A bountiful harvest of golden grain under the vast Australian sky.

Ararat, Victoria, Australia

Golden fields swaying under the Australian sun, a testament to the Ararat region’s bountiful spring wheat harvest.

La Pampa, Argentina

Across the boundless pampas, golden waves of wheat ripple in the wind, a symbol of Argentina’s rich agricultural heritage and the tireless work of its farmers.

South Africa

Beneath the vast African sky, golden fields shimmer, a testament to the resilience and agricultural prowess of South Africa’s farmers.

México

Beneath the vibrant Mexican sun, golden fields stretch across the landscape, a testament to the nation’s resilient spirit and agricultural bounty.

On each page, the value displayed in the top-left (or top) position represents the aggregated index for the entire area shown on the page. This value is calculated as the mean NDVI of all NDVI grids within the area, rather than the mean of individual index values for sub-areas.

For instance, on the La Pampa, Argentina page, the aggregated mean for all 86 grids is shown as 0.38 (as of 1st Nov, 2024). This value is based on over 86,000 NDVI grid points in La Pampa, rather than the 86 sub-area indices listed individually (e.g., 0.36, 0.33, 0.41).

Note that the index data on selected area are free to use with the attribution or link to this page.

Data Download

The index data can be downloaded in CSV, PNG, and SVG formats from the area pages.

Citation

When citing or utilizing this index data, please include the following attribution or html code:

Attribution

Otani & Co., Inc. Spring Wheat / NDVI Index. https://otani.co/docs/crop-spring-wheat-ndvi/

HTML

<a target="_blank" href="https://otani.co/docs/crop-spring-wheat-ndvi/">Spring Wheat / NDVI Index.</a>

Data Source

“European Union’s Copernicus Land Monitoring Service information; NDVI and Spring Wheat Total Above Ground Producton”

For additional information, customization, or applications of the data, please contact us using the form on this page.

Mayze Data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) / Copernicus

October 17, 2024October 17, 2024 yuichiro

Our data for Mayze Data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) is based on the data from Copernicus project in Europe. This page purposes to explain detailed information for the downloadable data.

Example Dataset (DVS)

Please download a free example dataset and use it in you app or analysis.

Download

URL Expiration

All downloadable URLs expire in 90 days after your order.

Temporal Resolution and Update

The temporal resolution for this data is 10-daily. Also, the latest data is usually updated within 2-3 days after the latest Copernicus data is published.

When you see your ordered data first time, you would recognize that the data does not contain the whole data. This is NOT a bug but the data creation process has not done yet. After the order, the process begins, and then the whole data becomes accessible in several hours. In every 15 minutes, the data is revised in the direction of both the future and in the past.

Data Format

The default format is csv where no single/double quotation marks are used in the file. Also, the geojson format is available, changing the file extension in the provided url from “csv” to “geojson.” Note that the geometry of geojson format is Point.

Example (DVS)

Example on Spreadsheet.

Column Names / Property Names

Names	Description	Physical unit / classes	Physical min	Physical max	Digital max	Scaling	Offset
time	Datetime	YYYY-MM-10 12:00:00	–	–	–	–	–
lat	Latitude	Decimal	–	–	–	–	–
lon	Longitude	Decimal	–	–	–	–	–
MayzeDWS	Crop phenological stage: 0 at emergence, 1.0 at flowering, 2.0 at crop maturity	–	0	2	–	–	–
MayzeTAGP	Total above-ground production (dry matter)	kg/ha	–	–	–	–	–
MayzeTWSO	Total weight storage organs (dry matter), e.g. grains or pods	kg/ha	–	–	–	–	–

Based on the provided information on Crop Productivity Indicators: Product User Guide and Specification (PUGS), This table is created by Otani & Co., Inc.

Further Details on Mayze Data

For further details, concerns such as satellite sensors and data accuracy, please refer the Copernicus pages and the ECMWF pages.

Crop productivity and evapotranspiration indicators from 2000 to present derived from satellite observations

Crop Productivity Indicators: Product User Guide and Specification (PUGS)

Spring wheat data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) / Copernicus

October 17, 2024October 17, 2024 yuichiro

Our data for Spring wheat data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) is based on the data from Copernicus project in Europe. This page purposes to explain detailed information for the downloadable data.

Example Dataset (DVS)

Please download a free example dataset and use it in you app or analysis.

Download

URL Expiration

All downloadable URLs expire in 90 days after your order.

Temporal Resolution and Update

The temporal resolution for this data is 10-daily. Also, the latest data is usually updated within 2-3 days after the latest Copernicus data is published.

Data Format

Example (DVS)

Example on Spreadsheet.

Column Names / Property Names

Names	Description	Physical unit / classes	Physical min	Physical max	Digital max	Scaling	Offset
time	Datetime	YYYY-MM-10 12:00:00	–	–	–	–	–
lat	Latitude	Decimal	–	–	–	–	–
lon	Longitude	Decimal	–	–	–	–	–
SpringWheatDVS	Crop phenological stage: 0 at emergence, 1.0 at flowering, 2.0 at crop maturity	–	0	2	–	–	–
SpringWheatTAGP	Total above-ground production (dry matter)	kg/ha	–	–	–	–	–
SpringWheatTWSO	Total weight storage organs (dry matter), e.g. grains or pods	kg/ha	–	–	–	–	–

Based on the provided information on Crop Productivity Indicators: Product User Guide and Specification (PUGS), This table is created by Otani & Co., Inc.

Further Details on Spring Wheat Data

For further details, concerns such as satellite sensors and data accuracy, please refer the Copernicus pages and the ECMWF pages.

Crop productivity and evapotranspiration indicators from 2000 to present derived from satellite observations

Crop Productivity Indicators: Product User Guide and Specification (PUGS)

Winter wheat data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) / Copernicus

October 17, 2024October 17, 2024 yuichiro

Our data for Winter wheat data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) is based on the data from Copernicus project in Europe. This page purposes to explain detailed information for the downloadable data.

Example Dataset (DVS)

Please download a free example dataset and use it in you app or analysis.

Download

URL Expiration

All downloadable URLs expire in 90 days after your order.

Temporal Resolution and Update

The temporal resolution for this data is 10-daily. Also, the latest data is usually updated within 2-3 days after the latest Copernicus data is published.

Data Format

Example (DVS)

Example on Spreadsheet.

Column Names / Property Names

Names	Description	Physical unit / classes	Physical min	Physical max	Digital max	Scaling	Offset
time	Datetime	YYYY-MM-10 12:00:00	–	–	–	–	–
lat	Latitude	Decimal	–	–	–	–	–
lon	Longitude	Decimal	–	–	–	–	–
WinterWheatDVS	Crop phenological stage: 0 at emergence, 1.0 at flowering, 2.0 at crop maturity	–	0	2	–	–	–
WinterWheatTAGP	Total above-ground production (dry matter)	kg/ha	–	–	–	–	–
WinterWheatTWSO	Total weight storage organs (dry matter), e.g. grains or pods	kg/ha	–	–	–	–	–

Based on the provided information on Crop Productivity Indicators: Product User Guide and Specification (PUGS), This table is created by Otani & Co., Inc.

Further Details on Winter Wheat Data

For further details, concerns such as satellite sensors and data accuracy, please refer the Copernicus pages and the ECMWF pages.

Crop productivity and evapotranspiration indicators from 2000 to present derived from satellite observations

Crop Productivity Indicators: Product User Guide and Specification (PUGS)

Wet rice data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) / Copernicus

October 17, 2024October 17, 2024 yuichiro

Our data for Wet rice data of Development Stage (DVS), Total Above-Ground Production (TAGS) and Total Weight Storage Organs (TWSO) is based on the data from Copernicus project in Europe. This page purposes to explain detailed information for the downloadable data.

Example Dataset (DVS)

Please download a free example dataset and use it in you app or analysis.

Download

URL Expiration

All downloadable URLs expire in 90 days after your order.

Temporal Resolution and Update

The temporal resolution for this data is 10-daily. Also, the latest data is usually updated within 2-3 days after the latest Copernicus data is published.

Data Format

Example (DVS)

Example on Spreadsheet.

Column Names / Property Names

Names	Description	Physical unit / classes	Physical min	Physical max	Digital max	Scaling	Offset
time	Datetime	YYYY-MM-10 12:00:00	–	–	–	–	–
lat	Latitude	Decimal	–	–	–	–	–
lon	Longitude	Decimal	–	–	–	–	–
WetRiceDVS	Crop phenological stage: 0 at emergence, 1.0 at flowering, 2.0 at crop maturity	–	0	2	–	–	–
WetRiceTAGP	Total above-ground production (dry matter)	kg/ha	–	–	–	–	–
WetRiceTWSO	Total weight storage organs (dry matter), e.g. grains or pods	kg/ha	–	–	–	–	–

Based on the provided information on Crop Productivity Indicators: Product User Guide and Specification (PUGS), This table is created by Otani & Co., Inc.

Further Details on Wet Rice Data

For further details, concerns such as satellite sensors and data accuracy, please refer the Copernicus pages and the ECMWF pages.

Crop productivity and evapotranspiration indicators from 2000 to present derived from satellite observations

Crop Productivity Indicators: Product User Guide and Specification (PUGS)

Burnt Area (300m) / Copernicus

October 17, 2024October 17, 2024 yuichiro

Burnt Area is based on the data from Copernicus project in Europe. This page purposes to explain detailed information for the downloadable data.

Example Dataset

Please download a free example dataset and use it in you app or analysis.

Download

URL Expiration

All downloadable URLs expire in 90 days after your order.

Temporal Resolution and Update

The temporal resolution is daily. Also, generally, the latest data is usually updated within 12-24 hours after the latest Copernicus data is published.

Data Format

The default format is csv where no single/double quotation marks are used in the file. The geojson format is available, changing the file extension in the provided url from “csv” to “geojson.” Note that the geometry of geojson format is Point.

Example

Example on Spreadsheet

Column Names / Property Names

Names	Description	Physical unit / classes	Physical min	Physical max	Digital max	Scaling	Offset
time	Datetime the Copernicus file is published (GST).	YYYY-MM-DD hh:mm:ss	–	–	–	–	–
lat	Latitude	Decimal	-90	90	–	–	–
lon	Longitude	Decimal	-180	180	–	–	–
BurntArea	Day of burn in the year	days	0	366	–	–	–

Based on the provided information on Burnt Area 2023 – present (raster 300 m), global, daily – version 3.1 This table is created by Otani & Co., Inc.

Note that “Some specific values are used: -1 for missing (no-data) pixels, -2 for water pixels.”

Further Details on Burnt Area Data

For further details, concerns such as satellite sensors and data accuracy, please refer the Copernicus pages.

Burnt Area 2023 – present (raster 300 m), global, daily – version 3.1

Gross Dry Matter Productivity (300m) / Copernicus

October 17, 2024October 17, 2024 yuichiro

Gross Dry Matter Productivity (300m) is based on the data from Copernicus project in Europe. This page purposes to explain detailed information for the downloadable data.

Example Dataset

Please download a free example dataset and use it in you app or analysis.

Download

URL Expiration

All downloadable URLs expire in 90 days after your order.

Temporal Resolution and Update

The temporal resolution is 10-day. Also, generally, the latest data is usually updated within 12-24 hours after the latest Copernicus data is published.

Data Format

Example

Example on Spreadsheet

Column Names / Property Names

Names	Description	Physical unit / classes	Physical min	Physical max	Digital max	Scaling	Offset
time	Datetime the Copernicus file is published (GST).	YYYY-MM-DD hh:mm:ss	–	–	–	–	–
lat	Latitude	Decimal	-90	90	–	–	–
lon	Longitude	Decimal	-180	180	–	–	–
GDMP	Gross Dry Matter Productivity (-1 for missing (no-data) pixels and -2 for water pixels.”)	kg / ha / day	0	655.34	32767	1/50	0
QFLAG	Bitwise quality flag	–	0	–	–	–	–

Based on the provided information on Gross Dry Matter Productivity 2014-present (raster 300 m), global, 10-daily – version 1 This table is created by Otani & Co., Inc.

Further Details on Gross Dry Matter Productivity (300m)

For further details, concerns such as satellite sensors and data accuracy, please refer the Copernicus pages.

Gross Dry Matter Productivity 2014-present (raster 300 m), global, 10-daily – version 1