Yuchun Pan

Single Leaf Area Measurement Using Digital Camera Image

Leaf area index is one of the most important parameters in ecological and environmental studies. This paper presents a method for single leaf area measurement based on the counting of the leaf pixels in digital leaf image. Initially, the target leaf is put on a piece of white paper on which four endpoints of an equal-length and orthogonal cross are printed. A background color threshold is then set to separate the white background pixels from the leaf pixels. After the removal of the background pixels, the leaf pixels are left; and the ratio of the number of leaf pixels to the number of pixels of the reference facet formed by the four control endpoints is equal to that of their areas. The single leaf area can then be computed easily based on this proportional relation. Analysis and experimental results indicate that the proposed method is an efficient and precise method for single leaf or leaf-like object area measurement.

Even sampling designs generation by charges repulsion simulation

Evenly distributed sampling design is generally considered as an efficient sampling design. It is widely used in sampling for the environmental survey. In this paper, we present a novel method for generating N evenly distributed samples within a given irregular polygon via simulating the movements of some ideal homogeneous point charges. Initially, charges are randomly put into the sampling region; then, they are freed and held orderly; and after enough runs, the charges will finally reach a stable state with all of them having a zero resultant force and velocity; and so they distribute evenly within the region. Their layout can thus be considered as an evenly distributed sampling design. The main advantages of this method are: (1) it is easy to understand and implement; (2) it is efficient in both running and generating better designs. Analysis and experimental results indicate that this method is an efficient and robust method for generating even sampling designs for 2D polygonal sampling region.

A Spatial Conditioned Latin Hypercube Sampling Method for Mapping Using Ancillary Data

For obtaining maps of good precision by the spatial inference method, the distribution of sampling sites in geographical and feature space is very important. For a regional variable with trends, the predicting error comes from trend estimation, variogram estimation and spatial interpolation. Based on the cLHS (conditioned Latin hypercube Sampling) method, a sampling method called scLHS (spatial cLHS) considering all these three aspects with the help of ancillary data is proposed in this article. Its advantage lies in simultaneously improving trend estimation, variogram estimation and spatial interpolation. MODIS data and simulated data were used as sampling fields to draw sample sets using scLHS, cLHS, cLHS with x and y coordinates as covariates, simple random and spatial even sampling methods, and the distribution and prediction errors of sample sets from different methods were evaluated. The results showed that scLHS performed well in balancing spreading in geographic and feature space, and can generate points pairs with small distances, and the sample sets drawn by scLHS produced smaller mapping error, especially when there were trends in the target variable.

Changes in Gross Output Value of Planting Industry and Their Decomposition of Crops in China Based on the LMDI Model

AbstractBased on the logarithmic mean Divisia index (LMDI) method, this study systematically analyzes the change in gross output value of planting industry in China during 1990–2012 , reveals the contribution of total sown areas of farm crops, planting structure, per hectare output of crop and price level of crop on gross output value of planting industry and identifies significant contributors to the changes at different times, thereby providing reference for the rapid growth in gross output value of planting industry in China. The following results are obtained: (1) The gross output value of planting industry in China was increased by 995.31 billion Yuan during 1990–2012; during those nine crops, rice had the maximum increment in gross output value, while peanut increased at the fastest rate; the output value of rice, wheat and maize occupied an important position, but showed overall downward trend with fluctuation. (2) The cumulative contributions of total sown area of farm crops, planting structure, per hectare output of crop and price level of crop on the gross output value were 88.64, −24.18, 228.22 and 702.63 billion Yuan, respectively. Price level of crop and per hectare output of crop were the main contributors to the rapid increase in gross output value of planting industry; from the view of respective crops, the effects of price level of crop and per hectare output of crop in those nine crops were positive; the rapid rise in the price of rice, maize, wheat, cotton and peanut, superimposed with the significant increase in the per hectare output of cotton and the planting proportion of maize, obviously promoted gross output value of planting industry during 1990–2012. (3) The gross output value of planting industry in China was closely related to national macroeconomic policies. The rise of crop price was the major contributor to increase in gross output value of planting industry during 1990–1996; the overall decline in the price of crop and the planting proportion led to significant decline in gross output value during 1997–2003; the rebound rise in the price of crop and the rapid increase in per hectare output of crop resulted in significant increase in gross output value of planting industry during 2004–2012.

Secure Production of Farm Produce-oriented Management and Spatial Decision-making System for Producing Area

To address security of farm produce’s quality, using object-oriented technologies to build multi-purpose database, it meets the current and future data needs of a variety of operational systems. Further, base on WebGIS, to establish management and decision-making system for producing area, This system could be implement digital management for the entire agricultural park, and evaluate individual plots momentarily, can also provide accurate results in the decision-making fertilizer.

The Synchronized Updating Technology Research of Spatio-temporal Supervision Data Model About Organizing of Construction Landuse Data in Distributed Environment

As China advances toward urbanization, the relation between supply and demand of land use is growing acutely. Effective supervision of various land use has become necessary to achieve reasonable and lawful use of land. The change of land use from farmland or unused land to construction land use in the process of urbanization usually undergoes the following stages: approval, expropriation, provision, application, and supplement. The change to construction land use similarly undergoes this process, and then the outcome before and after the change is compared to determine potential land use problems. The present process-oriented spatio-temporal data model for organization and supervision data management records the supervised spatio-temporal variation process and state by using new-added auxiliary tables. This model can efficiently organize and demonstrate multiple relationships among landuse stages and the evolution process in the life cycle of spatial entities. To achieve effective supervision from the upper to the lower in the three-level “province-city-county” distributed environment and to detect potential land use problems early, data from different places are collected and synthesized for analysis. To ensure that the database is up-to-date, real-time synchronization of spatio-temporal supervision data should be studied and the integrity of the spatio-temporal data model should be maintained. Therefore, this study introduces an updating mechanism based on the trigger technology for data synchronization. When importing basic data from distributed databases into the supervision database, simultaneous updating in related auxiliary tables is performed along with changes in the basic tables. That is, records are added automatically into auxiliary tables that reflect the spatio-temporal change of the process and state when basic data are imported. This method not only achieves and maintains consistency in the database, but also ensures integrity and currency in the auxiliary tables. Change information can be expressed duly in all supervision stages, and highly efficient supervision of construction landuse is guaranteed.

Assessing the Fluctuation Characteristics of Grain Output in China

The characteristics of gross grain output between 1949 and 2012 and the effects of different crops and production regions on fluctuations between 1978 and 2012 in China were analysed using empirical mode decomposition and variance decomposition methods. Grain output has shown a tendency to increase since 1970. Rice, wheat and corn were the primary crops contributing to gross grain output fluctuation, with rice playing the most significant role. The middle–lower reaches of the Yangtze River contributed most to output fluctuation, followed by the northeast and Huang-Huai-Hai regions. The findings provide important evidence concerning trends in grain production in China.

Experimental Study on Estimation of Global Mean with Preferential Spatial Samples

The conventional approach to estimate the global mean under preferential spatial sampling gets a larger deviation and further influences the precision of the subsequent model calculation and analysis. Zoning or declustering methods can effectively improve the estimation precision of preferential sampling. In this paper, we propose a novel method, which uses self-organizing dual-zoning method to estimate the global mean, in which the Self-Organizing Feature Map (SOFM) and the Voronoi diagram are utilized to realize classification and zoning. By comparing with arithmetic mean method, polygonal declustering method, and cell declustering method, we got that arithmetic mean method could not satisfy the special properties of the preferential sampling, and self-organizing dual-zoning method gets more accurate zoning results and more stable global means with different sample sizes and Feature Deviation Index (FDI).

Study on Cultivated Land Concentrated Areas Delineation Based on GIS and Mathematical Morphology: A Case of Miyun County and Pinggu District in Beijing

The basic farmland within the protection areas was required to be of high-quality and connective in the general plans for land use. A new method was developed to delineate the boundaries of high-quality, concentrated and connective cultivated land. Based on mathematical morphology principles and GIS methods, the high quality of cultivated land blocks could be identified through dilation and erosion operations according to this rule that which inside distance was less than threshold d1 and the number of blocks was larger than 3. This method was validated with the farmland classification data of Miyun County and Pinggu District in Beijing City, and 91% of high-quality, concentrated and the connective cultivated land could be identified by this method, so it would provide the reference method for delineating the basic farmland areas scientifically and reasonably in the general plans for land use.

Preliminary Study on Soil Moisture Forecast of Winter Wheat

Using four groups of survey data of soil moisture of winter wheat from returning green stage to harvest stage in Daxing region, the variation laws of soil moisture exponential depletion relations in 0-60cm depths during different growth stage are analyzed ,and based on soil moisture exponential depletion relations the forecast model of soil moisture depletion is built. The results indicate that the soil moisture exponential depletion relations in the same depth layer increase at first and then decrease. Moreover, for different depth layers they decrease with the increase of depth, and the dispersion degree also changes with the depth. Using the exponential depletion relations method, the soil water storage at the 20, 40 and 60cm depth layers are forecasted, and the minimum forecast error is 0.09%, the forecast accuracy in the layer of 60cm is highest, and the absolute error is between 0-1.5%. This method does not need much data, and its results are reliable and precise. So it is a practical method for soil moisture forecast in winter wheat field of Beijing and others whose soil condition is same as Beijing.