Agricultural Land Suitability Analysis for Suğla Lake from Multispectral PlanetScope Satellite Data Between 2017–2023

Öz

This study aims to evaluate the sustainability of agricultural areas surrounding Suğla Lake, located in Konya Province, by integrating the Agricultural Land Suitability Analysis (ALSA) approach with remote sensing techniques. Spectral indices such as NDVI, NDWI, EVI, GCI, and SAVI were calculated using PlanetScope satellite imagery from 2017 to 2023. Spatial changes were assessed through a comprehensive approach involving Principal Component Analysis (PCA) and Object-Based Image Analysis (OBIA). Temporal analyses supported by imagery from Google Earth revealed significant annual fluctuations in vegetation density over and around the lake surface. In this context, the data from 2020 and 2023 indicate increased vegetation stress, higher proportions of bare soil, and notable changes in agricultural production patterns. The observed changes around the lake appear to have considerable impacts on both agricultural activities and the ecological balance of surrounding wetlands. The multiyear evaluation of spectral index data using the ALSA method in the Suğla Lake area addresses a notable gap in the literature and stands out as one of the pioneering comprehensive studies in this context. The findings demonstrate that the ALSA approach can be utilized as an effective decision support tool in developing sustainable land use scenarios and in the early detection of environmental risks.

Anahtar Kelimeler

• Lake Suğla
• ALSA
• Spectral Indices
• Remote Sensing
• PCA

Suğla Gölü için 2017-2023 Yılları Arasında Multispektral PlanetScope Uydu Verileri ile Tarımsal Arazi Uygunluk Analizi (ALSA)

Öz

Bu çalışma, Konya ilinde yer alan Suğla Gölü çevresindeki tarım alanlarının sürdürülebilirliğini değerlendirmek amacıyla, Tarımsal Arazi Uygunluk Analizi (ALSA) yaklaşımının uzaktan algılama teknikleriyle entegrasyonunu hedeflemektedir. 2017–2023 yılları arasına ait PlanetScope uydu görüntüleri kullanılarak NDVI, NDWI, EVI, GCI ve SAVI gibi spektral indeksler hesaplanmış; mekânsal değişimler, Temel Bileşen Analizi (PCA) ve Nesneye Dayalı Görüntü Analizi (OBIA) yöntemleriyle bütüncül bir yaklaşımla değerlendirilmiştir. Google Earth üzerinden elde edilen görüntülerle desteklenen zamansal analizler, göl yüzeyi ve çevresindeki bitki örtüsü yoğunluğunda yıllık bazda önemli dalgalanmalar yaşandığını ortaya koymaktadır. Bu bağlamda, 2020 ve 2023 yıllarına ait veriler, bitkisel stresin arttığını, çıplak toprak oranının yükseldiğini ve tarımsal üretim deseninde belirgin değişiklikler yaşandığını göstermektedir. Göl çevresinde gözlemlenen bu değişimlerin hem tarımsal faaliyetler hem de sulak alanların ekolojik dengesi üzerinde dikkate değer etkiler yarattığı görülmektedir. Suğla Gölü çevresinde çok yıllı spektral indeks verilerinin ALSA yöntemiyle kapsamlı biçimde değerlendirilmesi, literatürdeki önemli bir boşluğu doldurmakta ve bu kapsamda detaylı olarak ele alınan öncü çalışmalardan biri olarak öne çıkmaktadır. Elde edilen bulgular, ALSA yaklaşımının sürdürülebilir arazi kullanım senaryolarının geliştirilmesinde ve çevresel risklerin erken tespitinde etkili bir karar destek aracı olarak kullanılabileceğini göstermektedir.

Anahtar Kelimeler

• Suğla Gölü
• ALSA
• Spektral İndeksler
• Uzaktan Algılama
• PCA

Kaynakça

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