International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
IMPLEMENTATION OF AN AGRICULTURAL ENVIRONMENTAL INFORMATION
SYSTEM (AEIS) FOR THE SANJIANG PLAIN, NE-CHINA
Q. Zhao **', S. Brocks *, V. Lenz-Wiedemann **, Y. Miao > © , R. Jiang 5, X. Chen ^5, F. Zhang °, and G. Bareth ^^
Institute of Geography (GIS & Remote Sensing Group), University of Cologne, 50923 Cologne, Germany -
zhaoquanying@gmail.com, (g.bareth, sebastian.brocks, victoria.lenz)@uni-koeln.de
? Department of Plant Nutrition, China Agricultural University, Beijing 100094, China -
(ymiao, rfjiang, chenxp, zhangfs)@cau.edu.cn
* ICASD - International Center for Agro-Informatics and Sustainable Development (www.icasd.org)
KEY WORDS: GIS, Spatial, Decision Support, Modelling, Agriculture, Environment, Farming
ABSTRACT:
The Sino-German Project between the China Agricultural University and the University of Cologne, Germany, focuses on regional
agro-ecosystem modelling. One major focus of the cooperation activity is the establishment of joint rice field experiment research in
Jiansanjiang, located in the Sanjiang Plain (Heilongjiang Province, north-eastern part of China), to investigate the different
agricultural practices and their impact on yield and environment. An additional task is to set-up an Agricultural Environmental
Information System (AEIS) for the Sanjiang Plain (SJP), which covers more than 100 000 km?. Research groups from Geography
(e.g. GIS & Remote Sensing) and Plant Nutrition (e.g. Precision Agriculture) are involved in the project. The major aim of the AEIS
for the SJP is to provide information about (i) agriculture in the region, (ii) the impact of agricultural practices on the environment,
and (iii) simulation scenarios for sustainable strategies. Consequently, the AEIS for the SJP provides information for decision support
and therefore could be regarded as a Spatial Decision Support System (SDSS), too. The investigation of agricultural and
environmental issues has a spatial context, which requires the management, handling, and analysis of spatial data. The use of GIS
enables the capture, storage, analysis and presentation of spatial data. Therefore, GIS is the major tool for the set-up of the AEIS for
the SJP. This contribution presents the results of linking agricultural statistics with GIS to provide information about agriculture in
the SJP and discusses the benefits of this method as well as the integration of methods to produce new data.
1. INTRODUCTION
The Sino-German project between the China Agricultural
University (CAU), Beijing, and the University of Cologne,
Germany, focuses on regional agro-ecosystem modeling. Since
2007, research groups from Geography (e.g. GIS & Remote
Sensing) and Plant Nutrition (e.g. Precision Agriculture) are
involved in the project. The International Center for Agro-
Informatics and Sustainable Development (ICASD) was
founded by these groups to contribute to the development of
modern agriculture (ICASD, 2012). Since this group started
working in the Sanjiang Plain (SJP, located in Heilongjiang
Province, the most north-eastern part of China) in 2005, lots of
field campaigns have taken place and quite an amount of first-
hand scientific data has been accumulated.
The SJP in Northeast China (located between 43°49'N to
48727 N and 129°11'E to 135°05'E) covers an area of
10.89 million ha, exceeding the size of the Netherlands almost
by three times. It includes 23 administrative counties and 52
large-scale farms, each responsible for several 10 000 ha. The
average elevation of the SJP is about 45 — 80 m a.s.l.. It is an
alluvial plain of the three rivers Heilong Jiang, Songhua Jiang
and Wusuli Jiang. This region is classified as a temperate humid
and subhumid continental monsoon climate with a mean annual
temperature of ~ 2.5 °C. Winter is long and cold with an
average temperature of -18 °C in January, summer is short but
with an average temperature of 21 — 22 °C in July (Yun et al.,
2005). Annual precipitation ranges from 350 to 770 mm, with
about 80 % occurring in May to September. The most typical
soils are Luvisols, Phaeozems, Cambisols and Histosols
(Huang, Y. et al., 2010).
re
x Corresponding author.
The SJP is one of the most productive agricultural regions of
China. Single-season rice is transplanted in late May and
harvested in late September or early October (Zhang et al.,
2012). Corn and soy bean are other main crops. The SJP plays
an important role in guaranteeing the food security of China. It
is a commercial food production base where most part of the
yield is sold, both domestically and abroad.
There are two administrative systems in the study area. One is
the general administrative system that specifies a Province -
County - Town-Village (PCTV) hierarchy, the other one is the
Nongken administrative system with a Nongken Chief Bureau -
Administrative Farm - Farm-Village/Work Site (NAFV)
hierarchy. Usually, several farms are located in one county,
however, sometimes a farm is located not only in one but in two
or more counties. Jiansanjiang city is the center city of the
Jiansanjiang Administrative Farm, located in the northwest part
of the Qixing Farm. Our experimental station was established in
Jiansanjiang by the CAU and the local bureaus. The working
group focuses on the area of the Qixing Farm (1206 kn»),
located within Fujin County (8227 km?).
Due to the intensive farming, especially the increase of rice
paddy fields, environmental problems, including soil
degradation and greenhouse gas emissions, become more and
more important (Huang & Song, 2010; Yan et al., 2003; Zhang
et al, 2012). Spatially distributed agro-ecosystem modeling
provides an important tool for analyzing agricultural
sustainability under present and future conditions (Lenz-
Wiedemann et al., 2010). An AEIS for the North China Plain
was successfully established and applied for ecosystem
modeling such as the DNDC model (Bareth et al., 2002; 2005).
