Vegetation Health Index 1-km Grid Dataset in
Yellow River–Huangshui River Valley (2000-2020)
Sun, N. S.1 Chen, Q.1,2* Liu, F. G.1,2 Zhou, Q.1,2 Guo, Y. Y.1,3
1. School of Geographic
Science, Qinghai Normal University, Xining, Qinghai 810008, China;
2. Academy of Plateau
Science and Sustainability, Xining, Qinghai 810008, China;
3. Center for
Agricultural Resources Research, Institute of Genetics and Developmental
Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei 050022, China
Abstract: Yellow
River–Huangshui River Valley (YHV) is the most
important agricultural area and grain production base in Qinghai Province. The
analysis of the evolution trend of the agricultural drought in YHV is of great
significance for ensuring the healthy development of agriculture in Qinghai
Province. The dataset is obtained using the vegetation health index (VHI)
calculation model and the daily land reflectance MOD09GA and daily land
temperature MOD11A1 data. VHI is the metric parameter that can couple the
normalized differential vegetation index (NDVI) and land surface
temperature (LST) to reflect the agricultural drought level of the region. The
area covered by this dataset is YHV, and the observation duration is from March
to November (Vegetation growing season) during 2000–2020. The dataset is in the
GeoTiff format, has a spatial resolution of 1 km, comprises 84 files, has a data size of 19.9 MB.
Keywords: Yellow River–Huangshui River Valley; Agricultural
drought; Vegetation Health Index; Growing season
DOI: https://doi.org/10.3974/geodp.2022.04.10
CSTR: https://cstr.escience.org.cn/CSTR:20146.14.2022.04.10
Dataset Availability Statement:
The dataset supporting this
paper was published and is accessible through the Digital Journal of Global Change Data Repository at: https://doi.org/10.3974/geodb.2022.08.03.V1
or https://cstr.escience.org.cn/CSTR:20146.11.2022.08.03.V1.
1 Introduction
Agricultural
drought is characterized by long duration and wide impact, which can seriously
affect agricultural production, human activities, and economic development as
well as the stability and security of society. It is one of the major
agricultural disasters[1-3].
Intergovernmental Panel on Climate Change stated in its Sixth Assessment Report
that continued global warming will lead to enhanced evapotranspiration and an
increase in the agricultural drought area in the future[4].
The accumulated agricultural drought disaster in China in 2021 damaged 3426.2
thousand hectares of crops and caused direct economic losses of 20.09 billion Yuan[5]. Thus, studying the
agricultural drought problem in China is significant for ensuring food supply
and maintaining social stability.
YHV is located in the northeast of Qinghai
Province; it is the alluvial formation of the valley of Yellow River and its
tributaries Huangshui River[6].
The total area of the YHV region is about 3.3 × 104
km2, accounting for only about 4.5% of the total area of the
province. Nearly 70% of the province’s population is concentrated in this
region, and more than 80% of the land is arable. Therefore, studying the
agricultural drought in the YHV region is essential for promoting sustainable
agricultural development in the Qinghai Province. Compared to other indices,
the vegetation health index (VHI) has better applicability in the field of
agricultural drought monitoring[7]
and is widely employed by scholars worldwide. The dataset compiled herein is
based on the MODIS remote sensing data with the use of the VHI calculation
model to calculate the annual and seasonal VHI values of YHV from 2000 to 2020
and the threshold method to determine the agricultural drought. This dataset
can intuitively reflect the location of agricultural drought areas and
agricultural drought area changes in YHV and provide reference for drought
policy formulation and agricultural production and management in YHV.
2 Metadata of the Dataset
The metadata
summary of the dataset[8] is
provided in Table 1, including the dataset name, short name, authors, year,
temporal resolution, spatial resolution, data format, data size, data files,
publisher, and sharing policies.
3 Methods
3.1 Algorithm
VHI was proposed by
Kogan et al. and was calculated from the vegetation condition index (VCI) and
temperature condition index (TCI)[10].
When crops are affected by agricultural drought, VCI and TCI beneficially
reflect the crop growth status and temperature, respectively[11].
When a drought occurs, the vegetation growth will be stressed and the VCI index
will decrease. Additionally, a drought is usually accompanied by an abnormal
increase in temperature, and consequently, the TCI index will decrease. In this
study, the weighted combination index VHI[12],
which integrates the respective advantages of VCI and TCI, is adopted to study
the agricultural drought in the YHV. The specific calculation methods of VCI,
TCI, and VHI are as follows:
(1)
(2)
Table
1 Metadata summary of
the VHI 1-km grid dataset in YHV (2000–2020)
Item
|
Description
|
Dataset name
|
Vegetation health index 1-km grid dataset(2000‒2020)
|
Dataset short name
|
VHI_YHV_2000‒2020
|
Authors
|
Sun, N. S. GNW-6596-2022, School of Geographic Science, Qinghai
Normal University, say0524@163.com
Chen, Q. AAB-3346-2021, School of Geographic Science, Qinghai Normal
University, qhchenqiong@163.com
Liu, F. G. L-8795-2018, School of Geographic Science, Qinghai Normal
University, lfg_918@163.com
Zhou, Q. AAB-3351-2021, School of Geographic Science, Qinghai Normal
University, zhouqiang729@163.com
|
Guo, Y. Y. GOG-8661-2022, School of Geographic Science, Qinghai
Normal University, 821709854@qq.com
|
Geographical region
|
Yellow River–Huangshui River Valley
|
Year
|
2000–2020
|
Temporal resolution
|
Annually and Seasonally
|
Spatial resolution
|
1 km
|
Data format
|
.tif
|
Data size
|
14.3M(after compression)
|
Data files
|
84 annually and quarterly vegetation health index data files; the
format of filename is VHI.YYYY.1_km_season.tif and VHI.YYYY.1_km_GSeason.tif
|
Foundations
|
Ministry of Science and Technology of P. R. China (2019YFA0606902)
|
Computing
environment
|
GEE, ArcGIS
|
Data publisher
|
Global Change Research Data Publishing & Repository,
http://www.geodoi.ac.cn
|
Address
|
No. 11A, Datun Road, Chaoyang District, Beijing 100101, China
|
Data sharing policy
|
Data from the Global Change Research Data Publishing & Repository
include metadata, datasets (in the Digital Journal of Global Change Data
Repository), and publications (in the Journal of Global Change Data &
Discovery). Data sharing policy includes the following: (1) Data
are openly available and can be free downloaded via the Internet; (2) End
users are encouraged to use Data subject to citation; (3) Users, who
are by definition also value-added service providers, are welcome to
redistribute the Data subject to written permission from the GCdataPR
Editorial Office and the issuance of a Data redistribution license;
and (4) If the Data are used to compile new datasets, the “ten per
cent principal” should be followed, which signifies that the utilized Data
records should not surpass 10% of the new dataset contents, while sources
should be clearly noted in suitable places in the new dataset[9]
|
Communication and
searchable system
|
DOI, DCI, CSCD, WDS/ISC, GEOSS, China GEOSS, and Crossref
|
(3)
Here, the value of α is
generally 0.5[13]. Kogan et al. proposed the agricultural drought
discrimination threshold based on VHI[14]:
(4)
where G(VHI) is the drought value, with 1 representing agricultural
drought and 0 representing no agricultural drought.
3.2
Data Development Process
Based on MOD09GA
and MOD11A1 data of the study area from 2000 to 2020, the following steps were
conducted (Figure 1):
(1) The scope of the study area was
imported into GEE to obtain the MOD09GA and MOD11A1 data of the study area from
2000 to 2020.
(2) NDVI was calculated based on MOD09GA (
, where
is the
near-infrared band and
is the infrared
band), and the quality.Mosaic() function in GEE was
used to synthesize the maximum value of NDVI. The S-G filter was used to smooth
NDVI, and the mean() function in GEE was used to
synthesize the average value of LST.
(3) Projection conversion and resampling of
NDVI and LST were performed in ArcGIS, and the annual and seasonal VCI and TCI
were calculated. Finally, the annual and seasonal VHI were calculated.
(4) The temporal variation and spatial
distribution of the agricultural drought in YHV were obtained.

Figure
1 Flowchart
of the dataset development
4 Data Results and Validation
4.1 Data Products
The 1-km grid VHI
dataset in YHV was named as VHI.YYYY.1_km_season.tif and
VHI.YYYY.1_km_GSeason.tif. The specific respective meanings are as follows: (1)
VHI: represents the vegetation health index product; (2) YYYY: represents that
the production year; (3) 1_km: represents the spatial resolution of 1 km; (4)
GSeason: represents annual data. (5) season:
represents seasonal data.
4.2
Data Results
4.2.1 Interannual spatial and temporal variation of agricultural drought
in growing season
VHI in the growing
season of YHV from 2000 to 2020 is shown in Figure 2. The figure shows that the
agricultural arid area in the annual growing season of YHV in the recent 20
years exhibits a decreasing trend, from more than 1.0 × 104 km2
in 2000 to less than 0.7 × 104 km2 in 2020, with an
average annual decrease of 142.85 km2. Thus, the agricultural
drought area greatly decreased. The agricultural arid areas of YHV are mainly
located in the central and southern regions of YHV, i.e., the low-heat valley
zone of the Yellow River and Huangshui River.

Figure
2 Growing season VHI
2000–2020
4.2.2 Temporal and spatial variations of the agricultural drought in the
growing season
The VHI of the YHV region in the spring,
summer, and autumn from 2000 to 2020 (Figure 3, 4 and 5) intuitively shows that
(1) the agricultural dry areas in spring are mainly located in the northern,
central, and southern regions of YHV, (2) the annual agricultural drought areas
in summer and autumn are mainly located in the central and southern parts of
YHV, and (3)

Figure
3 Spring
VHI 2000–2020

Figure
4 Summer
VHI 2000–2020

Figure
5 Autumn VHI
2000–2020
the agricultural dry areas in each season are basically located in the
low-heat valley area with large evapotranspiration. The changes of the
agricultural arid area in the YHV region in the spring, summer, and autumn from
2000 to 2020 are shown in Figure 6, respectively. In the YHV region, the
agricultural arid area in the spring exhibits almost no change in the past 20
years and is always above 1.4 × 104 km2, while that in
the summer and autumn exhibits a very obvious downward trend. The decrease is
significantly greater in the summer than in the
autumn. In the 20 years, agricultural drought area annually decreased by an
average of 187.09 km2, the summer and autumn agricultural drought
area annually decreased by average of 369.64 km2, but the whole
spring of YHV agricultural drought area biggest, next autumn, summer
minimum of YHV agricultural drought is given priority to with spring drought.
The severity of autumn and summer drought is less severe than that of the
spring drought.
Figures 7 shows that in the YHV in the
recent 20 years, the average value of spring VHI is basically less than 40, the
average value of summer VHI is between 50 and 60, and the average value of
autumn VHI is between 40 and 50. In the YHV region, the average value of summer
VHI is the largest, followed by that of the autumn VHI and spring VHI. In the
YHV region, the severity of the agricultural drought is the highest in spring,
followed by autumn and summer. Moreover, the trend fitting of the average VHI
of the three seasons shows that the average VHI of each season increases to
different degrees. Among them, the average VHI of autumn exhibits the largest
increase, followed by summer and spring. Therefore, during the period from 2000
to 2020, the severity of agricultural drought in each season in YHV alleviated,
but spring was the drought prone season in the YHV region.

Figure
6 Agricultural
drought area in Spring, Summer and Autumn 2000–2020

Figure
7 VHI
mean value in Spring, Summer and Autumn 2000–2020
5 Discussion and Conclusion
The study of
agricultural drought in the YHV region is of great practical significance for the
healthy agricultural development in the Qinghai Province. In this study, the
VHI values in the growing season of YHV from 2000 to 2020 were calculated based
on remote sensing data, and the agricultural drought characteristics in this
period were annually and seasonally obtained.
Based on the
research results, the agricultural drought in the entire YHV region is
continuously alleviated, reflecting the continuous improvement of the natural
conditions in this region, which is consistent with the conclusion that the
natural environment of the Qinghai–Tibet Plateau is warming and wetting[15]. Furthermore, from the
interannual and seasonal perspectives, the agricultural arid areas in the YHV
region are all located in the valley region formed by the Datong River,
Huangshui River, and Yellow River, which is the most concentrated agricultural
area in the YHV region. The study results denote that using VHI to identify
agricultural arid areas in the YHV region is reasonable. In the future, VHI can
be used as an indicator to monitor agricultural drought in the YHV region as
well as the Qinghai Province.
Author Contributions
Chen,
Q. proposed the idea; Liu, F. G. and Zhou, Q. designed the framework; Sun, N.
S. and Guo, Y. Y. collected and processed the data; and Sun, N. S. wrote the
paper.
Conflicts of Interest
The
authors declare no conflicts of interest.
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