Cannot read the Tiff file by GDALRasterSource. Unable to construct dataset dimensions. GDAL Error Code: 4

Describe the bug

Cannot read the Tiff file by GDALRasterSource. Unable to construct dataset dimensions. GDAL Error Code: 4

To Reproduce

Provide as able:

• Steps to reproduce the behavior
• Code example

package com.example.gdalread
import cats.syntax.option._

import geotrellis.layer.{FloatingLayoutScheme, KeyExtractor, LayoutLevel, SpatialKey}
import geotrellis.proj4.LatLng
import geotrellis.raster.RasterSource
import geotrellis.raster.gdal.GDALRasterSource
import geotrellis.raster.resample.{Bilinear, PointResampleMethod}
import geotrellis.spark.{MultibandTileLayerRDD, RasterSourceRDD, RasterSummary}
import org.apache.log4j.{Level, Logger}
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
import geotrellis.raster.gdal._
import com.azavea.gdal._

object gdal_read_test {
  def main(args: Array[String]): Unit = {
    Logger.getLogger("org").setLevel(Level.ERROR)
    System.load("/root/anaconda3/envs/gdal-3.1.2/lib/libgdal.so.27")
    System.getProperty("java.library.path")
    GDALWarp.init(100)
    print("enter country_pop_sgdal_read_test  tatus_____________21.12________________")
    var startTime = System.currentTimeMillis();
    implicit val conf =
      new SparkConf()
        .setAppName("gdal_read_test")
        .setMaster("spark://master:7077")
        .set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
        .set("spark.kryo.registrator", "geotrellis.spark.store.kryo.KryoRegistrator")
        .set("spark.executor.cores", "6")
        .set("spark.executor.memory", "4g")
        .set("spark.driver.memory", "2g")
        .set("spark.num.executors", "3")
        .set("spark.cores.max", "20")
        .set("spark.executorEnv.LD_LIBRARY_PATH", "/root/anaconda3/envs/gdal-3.1.2/lib/:/usr/local/lib")
        .set("spark.dynamicAllocation.enabled","false")
        .set("spark.default.parallelism","600")
        .set("spark.repartitioning","true")
        .set("spark.sql.shuffle.partitions","600")

    implicit val sc = new SparkContext(conf)
    val Path="/geo/file/raster/RS/Landsat/L71149033_03320030531_B10.TIF"
    println("path",Path)
    val targetCRS = LatLng
    println("targetCRS",targetCRS)
    val method: PointResampleMethod = Bilinear
    val tilesize= 256 // 256
    val layoutScheme = FloatingLayoutScheme(tilesize)
    val raster_source_single=GDALRasterSource(Path)
    val raster_source=Seq(raster_source_single)
    val sourceRDD: RDD[RasterSource] =sc.parallelize(raster_source)

    val summary = RasterSummary.fromRDD(sourceRDD)
    val LayoutLevel(zoom, layout) = summary.levelFor(layoutScheme)
    val context_rdd: MultibandTileLayerRDD[SpatialKey] = RasterSourceRDD.tiledLayerRDD(sourceRDD, layout, KeyExtractor.spatialKeyExtractor, rasterSummary = summary.some)
    val sum_resu_rdd: RDD[Int] =context_rdd.map{ single_rdd=>
      single_rdd._2.band(0).toArray().sum

    }
    val sum_resu=sum_resu_rdd.collect()
    println("result: ",sum_resu)

    val endTime = System.currentTimeMillis
    println("total time is ",(endTime - startTime) / 1000,"s")
    sc.stop()
  }
}

• Inputs
• Actual output
• encouter erroe when reading any tiff
• Expected output
• read the tif and output the sum value of exach tile

Expected behavior

A clear and concise description of what you expected to happen.

Screenshots

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Environment

CentOS Linux release 7.9.2009 (Core)

• Java version:

• java version "11.0.12" 2021-07-20 LTS
  Java(TM) SE Runtime Environment 18.9 (build 11.0.12+8-LTS-237)
  Java HotSpot(TM) 64-Bit Server VM 18.9 (build 11.0.12+8-LTS-237, mixed mode)

• Scala version:

• 2.12.8

• GeoTrellis version:

• 3.5.2

Additional context

Add any other context about the problem here.
bugreport.zip
bugreport2.zip
bugreport3.zip
bugreport4.zip

Start with the supplied Scala reproduction and the GDALRasterSource(Path) call, then inspect the GDALRasterSource entry point and the attached bug reports. Verify whether the TIFF failure occurs while constructing dataset dimensions and determine the environment or input condition that causes it. Done means the provided TIFF can be read and the per-tile sums are produced without the GDAL error.