A Comprehensive Review of Application of RS, GIS and GPS in Agriculture India

Food and fibre, two of humanity's most fundamental requirements, are met by agriculture. In the last century, new farming methods have been introduced, such as the Green Revolution, which has enabled agriculture to keep up with the increasing demand for food and other agricultural goods. But population growth, rising income levels, and increased food demand will probably put more stress on the planet's natural resources. As the detrimental effects of agriculture on the environment become more widely acknowledged, new methods and strategies need to be able to meet future food needs while preserving or lessening the environmental footprint of agriculture. Informed management decisions aiming at increasing crop production could be made with the help of emerging technologies like artificial intelligence (AI), Internet of Things (IoT), big data analysis, and geospatial technology. Many scientists, engineers, agronomists, and researchers use a variety of technologies each year to boost agricultural output while minimising pollution, yet these efforts have a negative environmental impact. Precision agriculture examines how technology might be applied to enhance agricultural practises relative to traditional methods while minimising negative environmental effects. Precision agriculture greatly benefits from the deployment of remote sensing technologies, which also presents new chances to enhance agricultural practises. Geographically, latitude and longitude data can be recorded for field data (slope, aspect, nutrients, and yield) using the global positioning system (GPS). Because of its ability to continuously determine and record the right position, it can build a larger database for the user. Geographic Information Systems (GIS), which can handle and store these data, are needed for the additional analysis. This review will offer you an overview of Remote Sensing technology, GPS, and GIS, and how it might be used for precision agriculture.

Regional cultitvation and dynamic change of garden Ginseng in Changbai county based on multi-source and multi-temporal satellite remote sensing data / 中国中药杂志

The dried roots of Panax ginseng are used as medicines. In this paper,multi-time satellite sensing image data are used for image registration by radiometric correction,atmospheric pressure correction,the data of different years were compared. The multiscale segmentation of the sensing image was successively carried out by using object-oriented method. Combining with the characteristics of the sensing image participated in the field survey,the objective was to understand the speckles of the environmental parameters distribution map of Changbai county in 2017 and 2018. The parameter area of Changbai county was calculated by using GIS spatial analysis tools. The union,erase and intersect tools of " analysis to OLS" overlay in " Arc Toolbox" were used to analyze the parametric area of Changbai county from 2017 to 2018. The results showed that the parameter area of Changbai county in 2017 was 27 400 mu( 1 mu≈667 m2),and the parameter area in 2018 was 13 900 mu. The parameter area of the new park in Changbai County in 2018 was 12 500 mu,and the harvested area in 2017 was 27 000 mu. Through the analysis and study of the regional change of the park participating in the training area,it has significance for guiding the park participating in the actual production planning and layout in Changbai county in the next step.

Research on extraction of Zizyphus jujuba planting area in Jia county of Shaanxi / 中国中药杂志

With digital satellite remote sensing image data of GF-1,in 2018 the object-oriented classification method was used to extract Zizyphus jujuba planting area in Jia county of Shaanxi province. The results showed that the remote sensing classification method based on rule set could extract and reckon Z. jujube planting area in the study area effectively. The planting area of Z. jujube in Jia county was about 5. 34×104 hm2 and the area of consistent accuracy was 97. 92%. The method used in this study could provide a technical reference for the area extraction of the same type of medicinal materials. And it is of great significance to provide decision support for the protection and utilization of Z. jujube resources.

Study on Remote Sensing Monitoring Method of Aquatic Medicine Materials Euryale ferox Salisb Based on Multi-source Satellite Remote Sensing Image / 世界科学技术-中医药现代化

Multi-source satellite remote sensing technology can be used to monitor the distribution and growth status of aquatic plant species on a large scale.In this paper,C,aoyou Lake was selected as the research area.Aquatic medicine material Euryaleferox Salisb was used as the research object.The spectral characteristics of plants in Euryaleferox Salisb growing area were analyzed by ASD portable spectrometer and the remote sensing image of Pléiades and GF-1.The spectral range of species was obtained.And the decision tree algorithm model was constructed,which were used to extract the information of Euryale ferox Salisb from remote sensing images.Through verification,the results showed that the accuracy of comprehensive classification was 83％.It was concluded that multi-source satellite remote sensing image and GIS spatial analysis technology can accurately reflect the area and distribution of aquatic medicine material Euryale ferox Salisb.

Proliferaciones algales 2000-2001 en Bahía de Banderas, México según el sensor SeaWiFS

Algal blooms at Banderas Bay, México (2000-2001), from SeaWiFS-sensor-data. Algal blooms for the period of 2000 and 2001 at Banderas Bay, México, were analyzed from SeaWiFS-ocean-color-sensor derived information. These events were related with the maximum chlorophyll week anomalies (ASi; a proxy variable constructed for the analysis of chlorophyll temporal variation in the bay). The winter-spring blooms were multispecific, while the summer-fall blooms were monospecific. Two proposals are made: 1) Winter-spring blooms are strongly related with mesoescale processes, due to their apparent temporal synchrony with the high chlorophyll levels in the coastal region from Sinaloa to Jalisco states; 2) Cochlodinium polykrikoides (Margalef 1961) blooms during the summer-fall periods could be induced by local conditions and the influence of previous events on the ecosystem. Rev. Biol. Trop. 56 (4): 1653-1664. Epub 2008 December 12.

Se analizaron las proliferaciones algales ocurridas en Bahía de Banderas, México, durante los años 2000 y 2001 a partir de información derivada del sensor de color del océano SeaWiFS. Estos eventos estuvieron relacionados con los máximos niveles de Anomalías Semanales de Clorofila’ (As i; variable construida para analizar la variación temporal de la clorofila dentro de la bahía). Las proliferaciones ocurridas en los periodos invierno-primavera fueron multiespecíficos, mientras que en verano-otoño fueron dominadas por una sola especie. Se plantean dos propuestas: 1) las proliferaciones algales de invierno-primavera están fuertemente relacionadas a procesos de mesoescala dada su aparente sincronía temporal con altos niveles de clorofila en las costas de Sinaloa a Jalisco; 2) mientras que las proliferaciones de Cochlodinium polykrikoides durante los periodos verano-otoño son favorecidas por el efecto de otras proliferaciones algales previas sobre el ecosistema y por condiciones predominantemente locales en la bahía.

Leishmaniose tegumentar americana em municípios da região noroeste do estado do Paraná: utilização de sensoriamento remoto para análise do tipo de vegetação e os locais de ocorrência da doença / American cutaneous leishmaniasis in municipalities in the northwestern region of Paraná State: use of remote sensing for analysis of vegetation types and places with disease occurrence

A leishmaniose tegumentar americana, doença endêmica da região noroeste do Paraná, é transmitida por flebotomíneos ao homem e a animais como cães, tatu, gambá e roedores silvestres. A doença vem ocorrendo em locais de derrubadas de matas e às margens de rios e lagoas com vegetação arbórea, onde o homem entra em contato com o inseto infectado. Esta doença constitui-se num problema de saúde pública devido à ocorrência de surtos epidêmicos em todo o Paraná. Em decorrência da importância de se conhecer áreas endêmicas, este trabalho utilizou dados de fichas epidemiológicas de pacientes atendidos no período de 1999 a 2004 associado às áreas de desmatamento identificadas por técnicas e produtos de sensoriamento remoto por satélite. Os resultados mostraram que a ocorrência de casos em municípios da região coincidem com as prováveis áreas supostas de infecção dos pacientes.

American cutaneous leishmaniasis, an endemic disease in the northwestern region of Paraná, Brazil, is transmitted by phlebotomines to man and animals like dogs, armadillos, opossums and wild rodents. This disease has been occurring in places where forests have been felled and on the banks of rivers and lakes with arboreal vegetation, where man comes into contact with infected insects. This disease is a public health problem because of the occurrence of epidemic outbreaks throughout Paraná. Because of the importance of finding out about endemic areas, this study used epidemiological file data on patients attended between 1999 and 2004. These data were correlated with areas of forest felling that were identified by means of satellite remote sensing techniques and products. The results showed that the occurrences of cases in the municipalities of this region coincided with the presumed likely areas for patient infection.

Stratification of density in dry deciduous forest using satellite remote sensing digital data—An approach based on spectral indices.

Forest density expressing the stocking status constitutes the major stand physiognomic parameter of Indian forest. Density and age are often taken as surrogate to structural and compositional changes that occur with the forest succession. Satellite remote sensing spectral response is reported to provide information on structure and composition of forest stands. The various vegetation indices are also correlated with forest canopy closure. The paper presents a three way crown density model utilizing the vegetation indices viz., advanced vegetation index, bare soil index and canopy shadow index for classification of forest crown density. The crop and water classes which could not be delineated by the model were finally masked from normalized difference vegetation index and TM band 7 respectively. The rule based approach has been implemented for land use and forest density classification. The broad land cover classification accuracy has been found to be 91·5%. In the higher forest density classes the classification accuracy ranged between 93 and 95%, whereas in the lower density classes it was found to be between 82 and 85%.