Most farmers think that improving the production of crops and increase in income. Therefore, factors such as optimization of fertilizers, soil moisture, and irrigation techniques, prevention of damage by harmful insects, weather conditions, and management costs have become issues of concern. The distribution of plants, and plant life itself, is dependent on various environmental conditions. A change in environment is often described as “environmental stress.” Damage by harmful insects, under nutrition, and environmental pollution often cause results of environmental stress. If changes in the physiological functions of farm products caused by environmental changes can be measured without any physical contact, then monitoring of the environment, forecast of yield, growth diagnosis, and management of crops will become possible. Remote sensing is a nondestructive technique to observe or measure objects and phenomena remotely, that is without any physical contact, using observation equipment. Remote sensing enables an object to be measured on spatial, temporal, and spectral scales. In particular, satellite remote sensing enables the observation of the entire earth by a consistent measuring method. Remote sensing was expected to have the potential to change the ways of agriculture; however, such utility did not advance as expected. There is a new discovery discovered because of the long temporal observation, for example change of CO2. There are the possibilities of “new discoveries” in agriculture as well as system science because remote sensing enables observation on various scales: spatial, temporal, and spectral.
Utilization of remote sensing technology is expanding in agriculture and environmental fields in accordance with the improvement of satellite sensors on board, hardware- software development, and diffusion of GIS in recent years. 23 subjects (research themes) on agricultural census and crop growth management are included in Chapter 1 of Part 2 in the Handbook. In the first phases, basic researches like acquiring ground truth data and hyperspectral measurements of crops on ground and air-borne sensors are introduced. In the second phases, methodology development for supporting to arrange agricultural census by governments, autonomies, and agricultural communities, are highlighted which include estimation of cultivation acreage, and cropping maps. In the final phases of Chapter 1, researchers reported on high quality low cost crop production applying satellite information on crop growth management. For instance, emphasis were given on technology to estimate protein content of rice grain before harvest for high nutrient quality, or determination of maturity of wheat grain for deciding harvest timing. It was also reported that in some root crops, chemical component such as starch value is detectable, or possible to give effective information for grassland renovation using satellite data. These technologies have been enrolled in a regional agricultural system, and committed for practical use in Hokkaido. In overseas, especially in monsoon Asia, satellite images are being used as useful source of information on paddy distribution, and regional cropping system.
In order to survey agriculture information, such as infrastructure and field crops, there were some examples using satellite images. In these cases, they are categorized three; first one is detailed and high accuracy analysis in Japan, second is Landsat and SPOT image analysis in developing countries, third is judging from high resolution satellite images. High accuracy is demanded in Japan under the complex of land use and many kinds crops. As a result, analysis of a series of satellite images and detailed analysis used by high resolution satellite images (IKONOS) were performed. By the reason of no detailed maps or agricultural statistics in developing country, shifting cultivation, land use analysis and land use change are reported using Landsat and SPOT images. High resolution images (IKONOS or QuickBird images) are useful to judge the condition of detailed land use, small scale ponds, agricultural facilities and so on. These information is useful for planning the usage of water and land resources.
A potential change in climate will increase the number of extreme events. Such events may cause natural disasters and severely affect human lives and agricultural production worldwide. Remote sensing technologies have enabled rapid collection of data where contemporaneous field observations are unavailable or incomplete. The author focuses on satellite remote sensing-based approaches to monitoring and prediction, and outlines methods to estimate environmental parameters and detect and predict natural disasters. This article describes an evaluation of environment, disaster detection and protection against disasters. The scope of evaluation of environment covers from ethology to continental desertification. The scope of disaster detection covers fire, volcanic activity, soil erosion, flood, drought and damage from salty breezes. Many problems still remain as to how to effectively predict a disaster and avert its damage before the disaster actually occurs, using a combination of remote sensing techniques, geographical information system (GIS) and administrative frames.
The interpretations of agricultural characteristics were performed in Japan and the world using satellite data. For the interpretation, we use color image of SWIR. Paddy has the characteristics of flooding, and this phenomenon was easily detecting the color image. Upland-farming fields are determined by the characteristics for mixing vegetated and non-vegetated fields because crop rotation systems are developed at upland farming fields. Grasslands have the color of light green and yellow green at the color image of SWIR, and broadleaf forests have almost same color. For the reason, it is difficult to divide broadleaf forest and upland farming field. L band Synthetic Aperture Radar (SAR) has the ability to divide the forests and the fields. The forests have high back scattering coefficient and the fields have low coefficient. Grasslands are easily extracted using Color image of SWIR and L-band SAR image.
Recently, China has big environmental problems due to rapid increase in a quality and diversity of waste by the high-economic growth. In this research, it has been shown that the actual conditions especially about the urban waste, the kinds, the assemblage system, the discharges and the harmlessness treatments at present in China. In addition, it was analyzed the cause of increasing the municipal solid waste discharges by the on-site studies in Beijing, Shanghai, and Jilin. It has been investigated that the appropriate disposal system of the municipal waste and the necessarily of composting treatment in Beijing city, Shanghai city, and Jilin province.
To evaluate how human activities affect nitrogen (N) transported to the Changjiang Sanxia Dam, we constructed a database of county-level agricultural statistics collected every five years from 1980 to 2000 for calculating N budget of 350 counties in the upper Changjiang River basin. Using a riverine N transport model, we quantified the N transported to the main upper tributaries of the Changjiang River. The total amount of N transported to the surface drainage waters from the agro-ecosystem, which accounted for about 83% of the total riverine N transport, reached 1.61x10 6t in 2000, which was a 2.9-fold increase over 1980. If the in-river loss rate is considered to be constant at 37%, the total amount of N transported to the Changjiang Sanxia Dam from the agro-ecosystem of the Changjiang river upper basin was about 0.35, 0.47, 0.59, 0.64 and 1.01x10 6t annually in 1980, 1985, 1990, 1995, and 2000 respectively. The amount of riverine N transport of new anthropogenic reactive N approximately quadrupled, from 3.45x10 5 t in 1980 to 1.39x10 6t in 2000, while the amount of riverine N transport due to rural human waste varied between 2.14-2.67x10 5t during the period 1980-2000. Of the total N transported to surface drainage waters in 10 watersheds in 2000, the Jialingjiang watershed accounted for 35%, the Changjiang Sanxia area for 15%, and the Toujiang, Wujiang and Minjiang watersheds each for 11%. In 1980, N sources were mainly focused on the rural areas surrounding Chendu City and Chongqing City, but expanded widely to the whole Sichuan basin and even surrounding mountainous and hilly areas in the 1990s. The increase of synthetic fertilizer use combined with the decrease of fertilizer N-use efficiency is implicated as major causal factors in the large amount of riverine N transport. Furthermore, the calculated riverine N transport for the main tributaries agreed well with the measured data reported in the literature. This work indicates that the riverine N load in the upper reaches of the Changjiang River and Changjiang Sanxia Dam has been increased rapidly by human activities, which might further worsen the local water quality and cause further eutrophication.
In the government control of rice production, the local government checks whether planting was carried out as planned. This is hard work that checks a number of fields on foot in a short term under the severe weather condition. Also, the representative in each check area is required to accompany as a guide of the field. However, it becomes difficult every year to keep enough manpower for the check work. The efficient and laborsaving way of checking out is demanded. We developed a field check system using mobile GIS. This system runs on mobile computers such as a tablet PC and a PDA. The system is easy to operate by a pen device and suitable for outdoor use. In the conventional check work, the farmers place check cards on the fields. We also use the check cards, but we changed the role of check cards. We print only a large symbol on each check card. The symbol is able to identify from the distant place. So we can move by a car and check the fields accurately and efficiently from inside a car. We investigated the efficiency of the check work using this system. In the field trial, we investigated as a pair, one is the driver of the car, and the other is the system operator. As a result, we could check out about 80 fields per an hour in the condition with scattering of the fields. Most of the fields were checked from inside the car and less than 10 percents of the fields were checked outside the car. The efficiency of the check work is about 3 times as much as the conventional way. The conventional way assumes that the investigators walk the same route by the car. Therefore, by using this system, the check work carried out with good efficiency and laborsaving.
Regression equations for estimating rice yield in a field in Hokkaido, Japan using remote sensing data (SPOT5/HRG) are derived. Results of 10-fold cross-validation indicate that multiple linear regression and projection pursuit regression give similar predictive errors (from 55kg/10a to 58kg/10a). These predictive errors may lead to the ability to use the results of such regression equations as alternatives to the visual external examination of rice fields by expert staff dispatched by the National Agricultural Insurance Association. By introducing such techniques, the number of the visual external examination points will be reduced. Further examination shows that the use of a specific cultivar of rice leads to a beneficial regression equation.