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CROP AREA ESTIMATION USING REMOTE SENSING ON TWO-STAGE STRATIFIED
SAMPLING
Wu Bingfang, Li Qiangzi
Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, 100101, wubf@irsa.ac.cn
Commission VI, WG VII/3
KEY WORDS: crop acreage, remote sensing, and stratified sampling
ABSTRACT:
In this paper, we analyses problems that remote sensing technique met in China. And provide a new methodology on stratified
sampling technique. During the stratification procedure, physical factors, such as temperature, precipitation, soil type, sun eradiation
was considered as well as proportions of main crop types. And then, we first estimate crop proportion using cluster sampling assisted
by remotely sensed images. Secondly, we estimate crop type proportions of different crop types using transect sampling and GVG
survey system. Here, transect sampling is a two-stage sampling in fact. In the first step, PSUs were selected randomly from a 4KM *
4KM area frame. And in the second stage, road segments were selected to survey crop type proportions. At last, crop area was
calculated under the support of current 100,000-scaled land resource database. And a case study of early rice area estimation in 2003
showed this methodology was efficient and accuracy enough to meet the running of CCWS.
1. INTRODUCTION
Monitoring, estimating and forecasting agricultural production
are very important for the management of world / regional or
local food demand and supply balance for social security. China
has made series of progresses from 1983 after tackling key
problems with states plan and researches in some institutes and
universities. Monitoring crop types has increased to including
wheat, maize and rice with monitoring area increased to
including 11 provinces. In 1998, China built a CCWS running
system for crop early monitoring, predicting and estimating.
Every year, CCWS publish the hot information on crop growing
status, crop acreage, crop production, crop structure changing
and multiple-plant index et al.
In China, crop acreage estimation using remote sensing always
met the following problems. (1) Some methods that have great
precise at small area become invalidate at country level. (2)
Crop planting and harvesting time are all concentrated in the
period from April to October every year, time is relatively
shorter when carrying out crop acreage estimation. So crop
acreage estimating-methods must be effective and time saving.
As a result, some method with a large amount of processing
successfully applied in small area cannot meet the request of
large region. (3) Some method that successfully applied in
small area cannot be applied because of their high-cost.
Therefore, country level crop acreage estimation methodology
must have the following properties:
- Accuracy enough to support decision.
- Speedy enough to meet the time that application section
required.
- Frugal enough not to go beyond the ability that application
section could bear.
-- Having unified criterion and can be operated easily.
In this paper, we mainly introduced the crop acreage estimating
methods used in China Crop Watch System, CCWS. Supported
by the arable area data in Chinese Resource and Environment
Database, we constructed a feasible methodology using a two-
sage sampling to meet Chinese crop estimating request. And
283
six years operating practice showed that, this crop acreage
estimating technique is accuracy, reliable and practically.
2. METHDOLOGY
Estimating crop acreage at large region using remotely sensed
data in operating always meet the following 3 obstacles when
there is no other techniques assistant.
---- Remotely sensed data cannot cover the country completely
in crop growing stage. Not only because the input reason, but
also the excessive processing-time. For the running of CCWS,
after image received, only there is 1 or 2 weeks left for image
pre-processing and analyzing before results publishing, and we
have no ability to process a large numbers of images required
for crop acreage estimation in China such a large area.
---- It's difficult to obtain enough images with proper date and
spatial resolution for meteorological conditions and limited time
slot. Sometimes, it is always cloud-covered or raining and we
cannot receive cloud free or high quality images. Nevertheless,
image-receiving date is extremely limited for crop acreage
extraction. In China, the most appreciate image date for
estimating rice acreage is the 2-5 week after moving. For winter
wheat acreage estimation is in March and April. For maize
acreage estimation in Northeast China is the last 10 days in
August or the first 10-day in September. And for Northeast
soybean acreage estimation is during the first 10-day in August.
Because of this, the ratio of acquiring proper remotely sensed
data is much lower.
---- Because of the special land-use system, rotation system and
cadastral pattern in China, there exists the particular cross-
planting and inter-planting phenomena everywhere. Early rice,
single rice and late rice are planted crossly in south China.
Spring wheat, maize and soybean are interlarded in Northeast
China. Maize and cotton are also interlarded in North China. As
a result, it’s very difficult to successfully identify crop patches
by crop type from remotely sensed data directly. As a result,
crop discrimination using remotely sensed data has maintained
a very low accuracy in China. It's very difficult to extract the