Land Suitability Assessment for Some Carbohydrate Food Crops at Wetland Area in Arisan Jaya

Priatna SJ, Rahman D, Supriyadi S. 2020. Land suitability assessment for some carbohydrate food crops at wetland area in Arisan Jaya. Jurnal Lahan Suboptimal : Journal of Suboptimal Lands 9(2): 117-126.The nature condition and lack of knowledge about soil characteristics have become a limitation for crops cultivation and development in Arisan Jaya. This study aimed to determine the type of crops that has potential to be developed in site. The assessment was carried out in Arisan Jaya, Pemulutan Barat Sub-District, Ogan Ilir Regency, South Sumatera from April to August 2015. The study method is 1:30.000 semi-detailed survey. The location of the sample was determined by grid method with one sample for every 1.000 meters with 10 sample sites. A disturbed soil sample was taken as deep as 150 cm from the ground surface. Land characteristics data were matched with crops growth requirements based on the suitability classes set for wetland rice, dry land rice, corn, cassava and sweet potato. The distribution of soil properties was known by IDW (Inverse Distance Weighting) interpolation method, which was overlapped to determine the distribution of land suitability classes. Very acidic soil conditions was a major limiting factor for crops cultivation in general (the actual suitability class is Nf). Wetland rice was relatively more suitable to be cultivated than dryland rice in the site. Corn and cassava could be planted as rotational crops before the rainy season or after rice season, although the productivity would not be optimal (S2 potential suitability class). Climatic conditions was another limiting factor for the development of sweet potato at the site (S3 potential suitability class).

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Reevaluation of Land Fitness For Soybean Plant in Kabamatan Stabat, Langkat District

International Journal of Applied Biology ◽

10.20956/ijab.v4i1.9168 ◽

2020 ◽

Vol 4 (1) ◽

pp. 15-20

Author(s):

Leni Handayani ◽

A Rauf ◽

Rahmawaty Rahmawaty ◽

T Supriana

Keyword(s):

Soil Texture ◽

Land Suitability ◽

Limiting Factors ◽

Organic N ◽

Limiting Factor ◽

Soybean Plant ◽

Marginal Fit ◽

Suitability Assessment ◽

Soybean Plants ◽

Land Suitability Assessment

A decrease in the area of soybean farming has an effect on reducing soybean production from year to year so that it has not been able to meet the needs of national soybean consumption. Land suitability assessment is an effort to be able to optimize land use. In the process of assessing land suitability manually, it is considered inaccurate. The purpose of this study was to determine the land suitability class for soybean plants. The land suitability classification system used is the FAO land suitability classification classified at the sub-class level. Land suitability evaluation uses a matching system, as well as comparing the characteristics of land with plant growing community formulated in the technical evaluation of land guidelines for agricultural commodities. In the matching process Leibig's minimum law is used to determine the limiting factors that will affect the suitability of the class and sub-class of the land. Requirements for growing plants become kiteria in conformity evaluation. The results showed that the limiting factors of land suitability for soybean plants that had to be improved were temperature, rainfall, soil texture, C-Organic, N-Total and P-Available soil. The limiting factor of temperature and soil texture cannot be improved so that the marginal fit class (S3) on actual land suitability remains marginal fit (S3) in terms of potential land suitability.

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KESESUAIAN LAHAN DAN PRODUKTIVITAS UBI CILEMBU SEBAGAI KOMODITAS UNGGULAN DI KABUPATEN SUMEDANG

ZIRAA'AH MAJALAH ILMIAH PERTANIAN ◽

10.31602/zmip.v44i3.2129 ◽

2019 ◽

Vol 44 (3) ◽

pp. 357

Author(s):

Mujiono Mujiono ◽

Kurniawati Sugiyo

Keyword(s):

Sweet Potato ◽

Crop Productivity ◽

Land Suitability ◽

Sweet Potatoes ◽

Suitability Assessment ◽

The North ◽

Land Suitability Assessment ◽

Relationship Of ◽

The Relationship ◽

Area Of Origin

This study aimed to determine the suitability of Cilembu sweet potato land. Land suitability assessment in this study was carried out by a method of matching between crop productivity and land characteristics as parameters with land suitability class criteria that have been prepared based on usage requirements or growing requirements of plants or other commodities evaluated. The results showed that 33% of the area in Sumedang district was physically very suitable for planting Cilembu sweet potato which covers the area of origin of Cilembu sweet potato as well as the surrounding area and areas in the north of the district. High yam productivity is found in the west of the district, including the area of origin of Cilembu sweet potatoes and their surroundings. The relationship of land suitability between Cilembu yam and productivity of Cilembu yam is shown by the alignment areas that are in harmony, (-), not suitable (+) and not suitable. The alignment areas that need attention are the aligned (-) and non-aligned (+) regions.

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Mapping of Land Suitability for Rambutan (Nephelium lappaceum) in Community Agroforestry Land at Gunung Ambat Village and Simpang Kuta Buluh Village

Journal of Tropical Soils ◽

10.5400/jts.2020.v25i2.107-117 ◽

2020 ◽

Vol 25 (2) ◽

pp. 107

Author(s):

Rahmawaty Rahmawaty ◽

Ridwanti Batubara ◽

Abdul Rauf ◽

Sintike Frastika

Keyword(s):

Global Positioning System ◽

Root Zone ◽

Land Suitability ◽

Survey Method ◽

Limiting Factor ◽

Suitability Assessment ◽

Nephelium Lappaceum ◽

Global Positioning ◽

Land Suitability Assessment ◽

North Sumatra

Rambutan (Nephelium lappaceum) is Sapindaceae family, commonly found in agroforestry land, owned by the community in Langkat District, North Sumatra Province as One of Multy Purpose Tree Species. This study aimed to asses and map the distribution land suitability for N. lappaceum. This research was conducted in Gunung Ambat Village and Simpang Kuta Buluh Village, Sei Bingai Sub District, Langkat Regency using survey method. The soil samples data was collected in the field based on the land unit. Land suitability assessment was evaluated using matching method. To map the distribution of land suitability, the Geographic Information System (GIS) was used. Global Positioning System (GPS) also was used in this study to record the coordinate points of each soil sample from the field. The results indicate that the actual land suitability classes for N. lappaceum were dominated by moderately suitable (S2) (97.56%) in Gunung Ambat Village and moderately suitable (S2) (52.92%) in Simpang Kuta Buluh Village. The water availability (wa) and root zone medium (rc) were the dominant limiting factor in this area.

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Land suitability assessment in climate change and sea level rise conditions in Thai Binh provincewith GIS-ALES integration model

Ministry of Science and Technology, Vietnam ◽

10.31276/vjst.63(11).28-33 ◽

2021 ◽

Vol 63 (11) ◽

pp. 28-33

Author(s):

Quoc Nam Hoang ◽

◽

Thi Thuy Nguyen ◽

The Anh Luu ◽

Ngoc Thanh Nguyen ◽

...

Keyword(s):

Climate Change ◽

Sea Level Rise ◽

Sea Level ◽

Agricultural Land ◽

Land Suitability ◽

Assessment Process ◽

Soil Conditions ◽

Suitability Assessment ◽

Land Suitability Assessment ◽

And Sea Level

Land suitability assessment is the scientific basis for rational land use planning. This assessment process relates to natural soil conditions (soil, topography, climate, hydrology, etc.). However, these factors are being changed due to the impacts of climate change and sea level rise, especially in coastal areas (saline intrusion, inundation), which should be included in the assessment. The results of applying the integrated GIS-ALES model for land suitability assessment in climate change and sea level rise in Thai Binh province, showed that the very suitable (S1) and suitable (S2) land area for rice cultivation, aquaculture, crops, and perennial crops (mainly fruit trees) were 92,818.5 ha, 34,518.6 ha, 27,424.9 ha, and 13,104.1 ha respectively. The spatial distribution of the appropriate grades was also shown on a 1/50,000 scale map. The results of this study help to orient planning the rational use of agricultural land for Thai Binh province.

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Agricultural Land Suitability Assessment Using Satellite Remote Sensing-Derived Soil-Vegetation Indices

Land ◽

10.3390/land10020223 ◽

2021 ◽

Vol 10 (2) ◽

pp. 223

Author(s):

Rubaiya Binte Mostafiz ◽

Ryozo Noguchi ◽

Tofael Ahamed

Keyword(s):

Remote Sensing ◽

Satellite Remote Sensing ◽

Agricultural Land ◽

Expert Knowledge ◽

Vegetation Indices ◽

Land Suitability ◽

Assessment System ◽

Yield Estimation ◽

Suitability Assessment ◽

Land Suitability Assessment

Satellite remote sensing technologies have a high potential in applications for evaluating land conditions and can facilitate optimized planning for agricultural sectors. However, misinformed land selection decisions limit crop yields and increase production-related costs to farmers. Therefore, the purpose of this research was to develop a land suitability assessment system using satellite remote sensing-derived soil-vegetation indicators. A multicriteria decision analysis was conducted by integrating weighted linear combinations and fuzzy multicriteria analyses in a GIS platform for suitability assessment using the following eight criteria: elevation, slope, and LST vegetation indices (SAVI, ARVI, SARVI, MSAVI, and OSAVI). The relative priorities of the indicators were identified using a fuzzy expert system. Furthermore, the results of the land suitability assessment were evaluated by ground truthed yield data. In addition, a yield estimation method was developed using indices representing influential factors. The analysis utilizing equal weights showed that 43% of the land (1832 km2) was highly suitable, 41% of the land (1747 km2) was moderately suitable, and 10% of the land (426 km2) was marginally suitable for improved yield productions. Alternatively, expert knowledge was also considered, along with references, when using the fuzzy membership function; as a result, 48% of the land (2045 km2) was identified as being highly suitable; 39% of the land (2045 km2) was identified as being moderately suitable, and 7% of the land (298 km2) was identified as being marginally suitable. Additionally, 6% (256 km2) of the land was described as not suitable by both methods. Moreover, the yield estimation using SAVI (R2 = 77.3%), ARVI (R2 = 68.9%), SARVI (R2 = 71.1%), MSAVI (R2 = 74.5%) and OSAVI (R2 = 81.2%) showed a good predictive ability. Furthermore, the combined model using these five indices reported the highest accuracy (R2 = 0.839); this model was then applied to develop yield prediction maps for the corresponding years (2017–2020). This research suggests that satellite remote sensing methods in GIS platforms are an effective and convenient way for agricultural land-use planners and land policy makers to select suitable cultivable land areas with potential for increased agricultural production.

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