Optical remote sensing (RS) is used to provide an effective knowledge base for advanced agriculture research (Ambast et al., 2002). Visible - Near Infrared (NIR) wavelengths offers the ability to monitor landscape process that are controlled by several surface parameters (Jacob et al., 2002; Price, 1992). Most commonly a simple or normalized ratio between the visible red and the NIR spectral wavebands are used for vegetation indices (VI). Several vegetation indices have been developed using the linearity of the NIR versus red reflectance as an indication of the green biomass. Some of the more sophisticated indices attempt to neutralize the soil influence by using a parameter or curve for bare soils. The weighted difference vegetation index (WDVI) developed by Clevers (1988) is one of those that corrects for the soil affects.
During early stages of vegetation stress, the cover might stay relatively constant but the surface temperature (Ts) may vary greatly because of changes in the soil physical properties including moisture and soil color (Bastiaanssen et al., 2000). Some studies have focused on the surface temperature and VI relation (VI/Ts) (Boegh et al., 1999; Nemani and Running, 1989). Moran et al., (2002) showed that scatter plots of remotely sensed (RS) surface temperature and VI often yield trapezoid shapes and explained this, by the differences in surface properties related to the effect on VI/Ts slopes for similar surface and atmospheric conditions. These trapezoid plots span a variety of surface types. The maximum Ts agree with bare soil conditions and the lowest Ts with full vegetation cover (VC). The interpretation of Ts for sparse VC, which is widespread in semi-arid regions, is not straightforward. Studies hav...
... middle of paper ...
... surface energy balance model. Agronomie, 22(6): 669-680.
Moran, M.S., Hymer, D.C., Qi, J.G. and Kerr, Y., 2002. Comparison of ERS-2 SAR and Landsat TM imagery for monitoring agricultural crop and soil conditions. Remote Sensing of Environment, 79(2-3): 243-252.
Moran, M.S. et al., 1997. Combining multifrequency microwave and optical data for crop management. Remote Sensing of Environment, 61(1): 96-109.
Nemani, R.R. and Running, S.W., 1989. Estimation of Regional Surface-Resistance to Evapotranspiration from Ndvi and Thermal-Ir Avhrr Data. Journal of Applied Meteorology, 28(4): 276-284.
Price, J.C., 1992. Estimating vegetation amount from visible and near infrared reflectances. Remote Sensing of Environment, 41(1): 29-34.
Tucker, C.J., 1979. Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Remote Sensing of Environment, 8(2): 127-150.
To compare the mean and variance of the Landsat TM and SPOT 5 HRG FPC Time Series for specific land cover types based on vegetation communities; and
Stephen V. Stehman, “Selecting and interpreting measures of thematic classification accuracy”. Remote Sensing of Environment, Vol. 62, No.1, pp.77–89, 1997.
...re measured using a densimeter. The herbaceous and woody percent coverage of the plot was also recorded.
In order to understand the content of this lab report, some major concepts must first be understood. It was once said that in short, geographers study “what is where, why, and so what”(Fairbanks and Sato). One concept that is needed to be known in order to understand the why aspect of this question is insolation. Insolation or incoming solar radiation is energy intercepted by a unit area on the Earth’s surface (Fairbanks and Sato). Insolation is a term needed to be understood in order to fully comprehend different patterns in climate. Second, within this lab report, potential evapotranspiration will be studied in order to help determine the water budget for each given city. Potential evapotranspiration is the amount of water that would be removed from the surface of a grid cell by evaporation and transpiration, if the amount of water already present in the...
To ensure validity, measure abiotic factors including soil temperature, light intensity, soil texture, and soil pH
Dry lands is a previous stage into what can develop the atrocity of desertification. These plains of ground lack moisture. These areas lose it either to evaporation or by transpiration of plants. Generally the land that is considered dry lands is still used by primitive technologies within herding and farming. This weak land is put on even l...
Jackson, R.D. 1986, Remote sensing of biotic and abiotic plant stress. Annual Review Phytopathology, 24, pp. 265-287.
...amics of marginal steppic vegetation over a 26-year period of substantial environmental change. Journal of Vegetation Science, 20(2), 299-310.
G. Sparovek, Q. De Jong Van Lier and D. Dourado Neto (2006) “Computer assisted Koeppen climate classification” INTERNATIONAL JOURNAL OF CLIMATOLOGY, Wiley InterScience
The first experiment used was that of the Comparative Yield Method. This method requires two sets of data to be collected in order to get relevant inferences about the area. The grass biomasses are classed according to a three-class system. The classes are based on the biomass of the grasses in a given quadrat. The quadrat with a high biomass is a rank 3, whereas a quadrat with a low biomass has a rank of 1. In between these two is obviously a rank 2. If a quadrat has an intermittent value, then a rank of 1.5 or 2.5 can be given. The first set of data collected is to calibrate the classes, so three samples of each rank are cut and dried to be weighed later. This is done to get an idea of how much biomass is present per rank. The second set of data collected is done by taking a random transect of about 25 metres and noting the ranks at each meter interval. These points are recorded used to make inferences on the available biomass in the area.
Improvements in the socio-economic patterns in India, China, Brazil and few other developing countries have opened new channels & opportunities for precision agriculture in these countries (Mondal, P. and Basu, M., 2009)”. India is a land of agriculture with large numbers of crops cultivated and the major pulses like wheat, pulses, rice, cotton, maize within top 10 in the world. However, when you take into consideration the ranking on quality wise it does not reach high. Although crops are being grown in India, The ratio of fertilizers used per area and the nutrition needs of the plants are not met. It is almost 3-5 times lesser to what is used in developed countries. With PA, you can achieve this needs of the plants, but studying the crop, soil and terrains. With the recent advancement in ISRO (Indian Satellite Research Organization) launching GPS and the IT revolution has changed the Indian environment making inroads for new scopes in farm sectors. There is also a misinterpretation that these technologies cannot be used in small scale farms. There are few technologies like chlorophyll meter (SPAD) and leaf colour chart (LCC) hand held portable devices to determine the timing of crop and the nutrient content. Government has been supportive in encouraging growers in small community to use GIS systems, and internet to understand the
If we accept that a farmers choice of land usage is controlled by the physical environment, we must identify the optimum conditions and limits to production of any one crop . This will help to identify the spatial pattern of environmental controls. This was central to the ideas explored by McCarty and Lindberg in the Mid West of the USA and gave rise to the Optima Limits Model in 1966. Away from the optimum physical conditions become hostile and production/ yields decline. The optimum is the area where yields are highest and variability best, where soils are fertile, temperature and rainfall ideal and ground surface level for cultivation.
Toshihiro Sakamoto, Masayuki Yokozawa, Hitoshi Toritani, Michio Shibayama, Naoki Ishitsuka, Hiroyuki Ohno, 2005. A crop phenology detection method using time-series MODIS data, Remote Sensing of Environment, Volume 96, Issues 3–4, 30 June 2005, Pages 366-374, ISSN 0034-4257, http://dx.doi.org/10.1016/j.rse.2005.03.008.
Specht, R. L. (1970). Vegetation. In The Australian Environment, 4th ed. Ed. G. W. Leeper, pp. 46-67. Melbourne: Melbourne University Press.
The backbone of a stable nation, socially and politically, is agriculture. Agriculture is the largest sector that provides a nation with food and employment. Agriculture is currently being affected by climate change and at the same time it is also a contributor to climate change. The drastic elevations in climate change started from the mid to late 20th century and they have been increasing since then (Boisvenue & Running 2006). Climate change is affecting agriculture by interfering with the efficiency of crop production. Agriculture is facing droughts, flooding, sea level elevations, natural disasters, and health hazards for employees. All of these exponents lead to crop failure that creates famines and food prices to rise. On the other side, agriculture is also contributing to climate change through their output of greenhouse gas emissions and carbon footprints. These are caused by the activities that agriculture engages with such as breeding of livestock, ploughing of fields, deforestation, and the use of pesticides and other agrochemicals. Climate change affects countries differently, mainly due to their ability to adapt and their geographical location. Canada and Russia benefit from the changes in climate while Sudan and Bangladesh are affected negatively, struggling to adapt. Agriculture and climate change are interrelated processes that exist mutually making it harder to reduce one without affecting the other.