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Micro-level delineation of agro meteorological zones in the Sivagangai district of Southern India using remote sensing and GIS techniques

机译:使用遥感和GIS技术的Sivagangai区南部Sivagangai区农业气象区微型描绘

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Different zonations like agro climatological and agro-ecological zonations are already available for crop planning, but they have not included inventories like length of growing period, soil textures, biomass, etc which are needed for efficient usage for agriculture. The study used the integration of remote sensing and geographical information system based on a weighted overlay approach to demarcate the micro-level agro meteorological zones for agricultural planning of Sivaganga district, Tamil Nadu, India using spatial analysis tools in ArcGIS 10.5 software. Rainfall and satellite images were used to prepare five thematic layers such as land-use/land-cover, length of growing period (LGP), biomass, soil texture, and elevation and generated maps were converted into the raster format. Sivagangai had LGP classes of (L1 (9-13 weeks), and L2 (14-17) weeks, which had a period of two to four months. Biomass was categorized into four classes viz., poor, moderate, good and excellent based an NDVI values of 0.06 - 0.10, 0.10 - 0.20, 0.20 - 0.40 and > 0.4, respectively. In district B4 category (excellent) covered larger area followed by B3 (good). Soil texture was broadly classified under four categories viz., S1, S2, S3 and S4, based on the likely performance of crop in respect of the group. Here the category S4 which had a loamy texture occupied most of the area indicating better suitability for cropping. Elevation was classified under three categories as E1 (<500 m). E2 (501-1000 m) and E3 (>1000 m). Sivagangai had E1category alone, owing to its proximity to east coast. The results revealed that the study area can be categorized into 16 agro-micro meteorological zones. This could be attained by efficient planning and utilization of available natural resources.
机译:不同的区分区,如农业气候和农业生态区间已经可用于作物规划,但他们没有包括生长期限,土壤纹理,生物量等长度的库存,这是有效的农业所需的。该研究采用了基于加权叠加方法的遥感和地理信息系统的集成,以划分了ArcGIS 10.5软件中的空间分析工具划分Sivaganga区的农业规划微级Agro气象区。降雨和卫星图像用于制备五个专题层,如土地使用/陆地覆盖,生长期限(LGP),生物质,土壤质地和升降,并产生地图被转换为光栅格式。 Sivagangai的LGP类(L1(9-13周)和L2(14-17)周,其中持续两到四个月。生物量被分为四类Viz。,差,中等,良好,优秀,优秀NDVI值分别为0.06-0.10,0.10-20,20,20,20,20,40.4。在地区B4类别(优秀)覆盖较大的区域,然后覆盖B3(好)。土壤纹理在四类viz下广泛分类。,s1基于该组的作物的可能性能,S2,S3和S4。这里具有遗传纹理的类别S4占据了大部分区域,表明为裁剪的更好适用性。提升是在三类中被分类为E1(< 500米)。E2(501-1000米)和E3(> 1000米)。Sivagangai独自拥有E1类别,由于其靠近东海岸。结果表明,研究区可以分为16个农业微观气象区。这可以通过有效的规划和利用可用的自然资源来实现。

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