With the development of social economy, the current urban traffic problem is more prominent. In order to solve this problem very well, the idea of establishing intelligent traffic management came into being. The establishment of intelligent traffic management, cannot do without the signal launch and reception. Therefore, how to set up some wireless signal transmitting device in time to travel on the road motor vehicles to send traffic information and how to achieve full coverage of the signal and signal stability is our article to discuss the issue. For the first question, we must separate the motorway and non-motorway from all roads. Motorway lanes are usually straight and long. While the bends are usually just sidewalks or bike lanes (non-motorized lanes). So the 121 road can be clustered analysis, clustering of the two indicators for each road length (the distance between the adjacent points) and the collection point of density (by drawing, you can observe the more curved the denser the road collection point, so the road curvature into the collection point of the intensity), the result of clustering can get 48 motor lanes. And then through regress function regression and data fitting to achieve an approximate description of each type of motor vehicle description model, so that each road in a given latitude (latitude) coordinates to determine the latitude (longitude) coordinates and the corresponding altitude. For the problem of two, according to the meaning of the road to know the signal strength is only related to the distance between the sampling point and the launch device, so you can 'the motor vehicle between the signal reception is relatively close to' this indicator into ' The average of the distance between all the sampling points and the transmitting device is close to '. By reading the data will be latitude and longitude conversion distance length, so that the maximum value as small as possible. The position of the launcher can be obtained by programming by MATLAB. When considering the altitude, only the position of the transmitting device can be changed. (9.7824,56.7720), and the position coordinates when considering the altitude are D (9.7459, 56.7586, 73.5645), and the position coordinate of the signal device is B (9.7824, 56.7720). For question three, note the effect of the original signal device A on the result. We still use the average of the distance between all the sampling points of the road and the launcher to characterize the stability of the signal reception. The average distance of all non-motorized trains to the original signal device A is first determined, and then the average distance of all non-motorized lanes from the new signal device B is set, and the signal acceptance strength of the non-motorized lane can be used to characterize. And then use the same method in question two to determine the location of the new signal transmitter. Finally, the coordinates of the position of the new signal device are E (9.7459,56.7586,73.5645).

In order to evaluate the temporal changes in tree diversity of forest vegetation in Xishuangbanna, Yunnan Province, the study collected tree diversity data from four main forest vegetation in the region through a quadrat survey including tropical rainforest (TRF), tropical coniferous forest (COF), tropical lower mountain evergreen broad-leaved forest (TEBF), tropical seasonal moist forest (TSMF). We extracted the distribution of four forest vegetation in the region in four periods of 1992, 2000, 2009, and 2016 in combination with remote sensing images, using simp son Shannon Wiener and scaling species diversity indexes compare to the differences of tree evenness of four forest vegetation and use the scaling ecological diversity index and grey correlation evaluation model to evaluate the temporal changes of forest tree diversity in the region in four periods. The results show that: (1) The proportion of forest area has a trend of decreasing first and then increasing, which is shown by the reduction from 65.5% in 1992 to 53.42% in 2000, to 52.49% in 2009, and then to 54.73% in 2016. However, the tropical rainforest shows a continuous decreasing trend. (2) There are obvious differences in the contributions of the four kinds of forest vegetation to tree diversity. The order of evenness is tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > warm coniferous forest > tropical seasonal humid forest, and the order of richness is tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > tropical seasonal humid forest > warm coniferous forest, The order of contribution to tree diversity in tropical rainforest > tropical mountain (low mountain) evergreen broad-leaved forest > tropical seasonal humid forest > warm tropical coniferous forest. (3) The tree diversity of tropical rainforests and tropical seasonal humid forests showed a continuous decreasing trend. The tree diversity of forest vegetation in Xishuangbanna in four periods was 1992 > 2009 > 2016 > 2000. The above results show that economic activities are an important factor affecting the biodivesity of Xishuangbanna, and the protection of tropical rainforest is of great significance to maintain the biodiversity of the region.

Seawater desalination has been studied with interest due to the scarcity of fresh water for human consumption. Solar distillation is an old method; the productivity, energy consumption of the process and the cost of the desalinated water thus obtained depend on the efficiency achieved in each of the stages of these systems. The limited capacity to absorb solar radiation and transform it into useful heat for evaporation, interaction with the surrounding medium, and heat losses restrict the overall efficiency of the thermal process and productivity. Since the energy comes from solar radiation, the maximum productivity of this process will be constrained by the magnitude of the total solar radiation available in an area of the planet due to its geographic location, time of year and local climatic conditions. The processes of this energy will be thermodynamically limited by the heat transfer coefficients achieved in the equipment, the maximum value that the evaporation heat can reach, as long as the losses to the environment by convection and radiation are minimal. Comparative analyses of several proposed models, reported data of distillers, reported data of solar radiation that reach average values of up to 7.2–7.4 kwh/m² in some regions of the planet are presented and estimates are made for productivity of these equipments that they reach between 6.7 and 6.9 kg/m² day with a theoretical maximum efficiency of about 0.16 of the total solar radiation.

Objective: to achieve accurately and rapidly the mapping of agricultural land use and crop distribution at the township scale. Methods: this study, based on specific methods, such as, time-series remote sensing index threshold classification and maximum likelihood, classifies each land use type and extracts crop spatial information, under the guidance of Sentinel-2A remote sensing images, to carry out agricultural land use mapping at township scale. And the mapping concerned will be verified by comparing with an agricultural spatial information map of a 0.5 m resolution, which is based on WorldVieW-2 fused images. Results: (1) the area accuracy of grain and oil crop land, vegetable land, agricultural facilities land and garden land is fairly good, with 92.93%, 98.98%, 95.71% and 95.14% respectively, and within 8% variation from actual area; (2) the spatial information of plot boundary, farmland road network, and canal network produced by OSM road data and historical high-resolution images was overlayed with the classification results of Sentinel-2A multi-spectral image for mapping, which can improve the accuracy of plot boundary information of classification results for the image with 10 m resolution. Conclusions: the use of multi-source information fusion method, agricultural land use and crop distribution space big data produced by Sentinel-2A optical image, can effectively improve the accuracy and timeliness of land use mapping at the township scale, to provide technical reference for the application of remote sensing big data to carry out agricultural landscape analysis at the township scale, optimization and adjustment of agricultural structure, etc.

With the purpose of knowing the phytosocilogy of weeds associated to a carrot crop (Daucus carota L.) under conditions of the municipalities of Ventaquemada and Jenesano-Boyacá, one lot per municipality destined to carrot cultivation was selected and a W-shaped layout was made covering an area of 500 m². Relative density, relative frequency, relative dominance and the importance value index (IVI) were calculated, as well as the Alpha and Beta diversity indices for the sampled areas. A total of 6 families and 11 species were counted, of which 63.64% were represented by annual plants and 36.36% by perennial plants. The class Liliopsida (Monocotyledon) was represented by the Poaceae family. The Magnoliopsida class (Dicotyledon) was represented by the following families: Asteraceae, Brassicaceae, Boraginaceae, Leguminosaceae, Polygonaceae, the last one being the one with the highest number of species. The species R. crispus and P. nepalense were the ones with the highest values of Importance Value Index (IVI) with 0.953 and 0.959, respectively. According to the Shannon-Wiener diversity and Simpson’s dominance indices, the evaluated areas presented a low species diversity and a high probability of dominant species. The results obtained can serve as a basis and tool for carrot growers in the evaluated areas to define management plans for the associated weeds and thus optimize yields in this crop.